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We present a publicly available dataset of psychophysiological responses to positive and negative emotions of 1157 healthy participants, collected across seven studies. In our studies were continuously recorded affect and physiological activity during resting baseline and emotional responding. We recorded physiological responses using electrocardiography (ECG), impedance cardiography (ICG), electrodermal activity (EDA), photoplethysmography (PPG, the blood pressure measures), respiratory, and temperature sensors. In our studies, we elicited emotions with films, pictures, speech preparation, and expressive writing. We studied a wide range of positive and negative emotions, including amusement, anger, disgust, excitement, fear, gratitude, sadness, tenderness, and threat. To the best of our knowledge, psychophysiology of positive and negative emotions (POPANE) database is the largest, consistent psychophysiological dataset on emotions ever collected and publicly shared. 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We hope that POPANE will provide individuals, companies, and laboratories with the data they need to perform their analyses, corroborate their results, and create robust psychophysiological models of emotions. The individuals data are openly available in POPANE dataset at https://data.psychosensing.psnc.pl/popane/index.html. ", "Subjective experience along with physiological activity are fundamental components of emotional responding. We present a publicly available dataset of psychophysiological responses to positive and negative emotions of 1157 healthy participants, collected across seven studies. In our studies were continuously recorded affect and physiological activity during resting baseline and emotional responding. We recorded physiological responses using electrocardiography (ECG), impedance cardiography (ICG), electrodermal activity (EDA), photoplethysmography (PPG, the blood pressure measures), respiratory, and temperature sensors. 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In these compounds, at least one carbon atom is replaced by one of the heteroatoms oxygen, nitrogen, or sulfur. Examples of non-benzene compounds with aromatic properties are furan, a heterocyclic compound with a five-membered ring that includes a single oxygen atom, and pyridine, a heterocyclic compound with a six-membered ring containing one nitrogen atom."""; "application/ld+json"; "https://w3id.org/ro-id/ba53e480-17bb-466f-b789-3533246d7b43"; ; "Aromatic compounds - snapshot", "Aromatic compounds"; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Wolniewicz, Małgorzata. \"Aromatic compounds.\" ROHub. 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In contrast to compounds that exhibit aromaticity, aliphatic compounds lack this delocalization. The term \"aromatic\" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. Aromatic hydrocarbons, or arenes, are aromatic organic compounds containing solely carbon and hydrogen atoms. The configuration of six carbon atoms in aromatic compounds is called a \"benzene ring\", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. Not all aromatic compounds are benzene-based; aromaticity can also manifest in heteroarenes, which follow Hückel's rule (for monocyclic rings: when the number of its π electrons equals 4n + 2, where n = 0, 1, 2, 3, ...). In these compounds, at least one carbon atom is replaced by one of the heteroatoms oxygen, nitrogen, or sulfur. Examples of non-benzene compounds with aromatic properties are furan, a heterocyclic compound with a five-membered ring that includes a single oxygen atom, and pyridine, a heterocyclic compound with a six-membered ring containing one nitrogen atom."""; "application/ld+json"; "https://w3id.org/ro-id/54c22dc5-ace3-4aaa-be62-b5b4dab97be6"; ; "Aromatic compounds - snapshot", "Aromatic compounds"; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Wolniewicz, Małgorzata. \"Aromatic compounds.\" ROHub. Jan 12 ,2022. https://doi.org/10.24424/x0cn-va37." . a ; dct:conformsTo ; . a ; "chemical compound"; "15.826086956521738"; "9.1" . a ; "The configuration of six carbon atoms in aromatic compounds is called a \"benzene ring\", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound."; "39.015151515151516"; "20.6" . a ; "aromatic hydrocarbon"; "5.94758064516129"; "5.9" . a ; "benzene"; "9.274193548387096"; "9.2" . a ; "carbon atom"; "15.999999999999998"; "9.2" . a ; "chemical compound"; "10.786290322580644"; "10.7" . a ; "electron"; "4.435483870967742"; "4.4" . a ; "oxygen atom"; "4.032258064516129"; "4.0" . a ; "arene"; "4.939516129032259"; "4.9" . a ; "chemistry"; "34.08360128617363"; "21.2" . a ; "organic chemistry"; "65.91639871382637"; "41.0" . a ; "chemistry and materials"; "100.0"; "0.8506659269332886" . a ; "scent"; "4.536290322580645"; "4.5" . a ; "heterocyclic compound"; "9.73913043478261"; "5.6" . a ; "benzene"; "12.695652173913043"; "7.3" . a ; "earth sciences"; "100.0"; "0.4569866955280304" . a ; "geochemistry"; "100.0"; "0.4569866955280304" . a ; "The term \"aromatic\" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds."; "21.401515151515152"; "11.3" . a ; "nitrogen atom"; "29.573934837092732"; "11.8" . a ; "aromatic compound"; "29.739130434782613"; "17.1" . a ; "arene"; "7.304347826086956"; "4.2" . a ; "Jewellery"; "Arts, culture and entertainment/Arts and entertainment/Fashion/Jewellery" . a ; "aliphatic compound"; "4.737903225806451"; "4.7" . a ; "Organic chemical"; "Economy, business and finance/Economic sector/Chemicals/Organic chemical" . a ; "benzene ring"; "3.528225806451613"; "3.5" . a ; "larger compound"; "13.533834586466165"; "5.4" . a ; "nitrogen"; "3.9314516129032255"; "3.9" . a ; "heterocyclic compound"; "6.451612903225806"; "6.4" . a ; "aromatic hydrocarbon"; "8.695652173913043"; "5.0" . a ; "aromatic"; "19.657258064516128"; "19.5" . a ; "organic compound"; "3.8306451612903225"; "3.8" . a ; "carbon atom"; "10.786290322580644"; "10.7" . a ; "monocyclic ring"; "14.285714285714286"; "5.7" . a ; "chemistry and materials (general)"; "100.0"; "0.8506659269332886" . a ; "aromatic compound benzene"; "24.81203007518797"; "9.9" . a ; "Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them."; "39.583333333333336"; "20.9" . a ; "ring"; "3.125"; "3.1" . a ; "oxygen atom"; "17.794486215538846"; "7.1" . a ; ""; "Biology" . a , , ; "10.24424/20ms-v465"; "False"; ; "2025-08-12 08:02:25.321821+00:00"; ; ; ; 0; "https://api.rohub.org/api/ros/07b99b7b-a209-44cc-86fd-327339b2599c/crate/download/"; ; "2022-01-19 13:47:59.181939+00:00"; "2025-10-16 11:12:08.755267+00:00"; "2022-01-19 13:47:59.181939+00:00"; "Attention deficit hyperactivity disorder (ADHD) is a behavioral and neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, which are pervasive, impairing, and otherwise age inappropriate.Some individuals with ADHD also display difficulty regulating emotions, or problems with executive function. For a diagnosis, the symptoms have to be present for more than six months, and cause problems in at least two settings (such as school, home, work, or recreational activities). In children, problems paying attention may result in poor school performance. Additionally, it is associated with other mental disorders and substance use disorders. Although it causes impairment, particularly in modern society, many people with ADHD have sustained attention for tasks they find interesting or rewarding, known as hyperfocus."; "application/ld+json"; "https://w3id.org/ro-id/07b99b7b-a209-44cc-86fd-327339b2599c"; ; "Attention deficit hyperactivity disorder - snapshot", "Attention deficit hyperactivity disorder"; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Wolniewicz, Małgorzata. \"Attention deficit hyperactivity disorder.\" ROHub. Jan 19 ,2022. https://doi.org/10.24424/20ms-v465." . a ; dct:conformsTo ; . a . a ; "life sciences"; "100.0"; "0.989045262336731" . a ; "distraction"; "5.919003115264798"; "5.7" . a ; "neurodevelopmental disorder"; "62.65984654731457"; "49.0" . a ; "environmental science and management"; "100.0"; "0.6445436477661133" . a ; "behavioural disorder"; "7.4766355140186915"; "7.2" . a ; "environmental sciences"; "100.0"; "0.6445436477661133" . a ; "inattention"; "9.515260323159785"; "5.3" . a ; "substance use disorder"; "19.565217391304348"; "15.3" . a ; "life sciences (general)"; "100.0"; "0.989045262336731" . a ; "diagnosis"; "6.645898234683282"; "6.4" . a ; "medicine"; "100.0"; "12.8" . a ; "individual"; "4.7767393561786085"; "4.6" . a ; "behavioral disorder"; "12.208258527827647"; "6.8" . a ; "individuals with ADHD"; "7.416879795396419"; "5.8" . a ; "mental disorder"; "3.426791277258567"; "3.3" . a ; "problem"; "9.345794392523365"; "9.0" . a ; "attention"; "5.815160955347872"; "5.6" . a ; "impulsiveness"; "5.815160955347872"; "5.6" . a ; "diagnosis"; "10.23339317773788"; "5.7" . a ; "disorder"; "10.951526032315979"; "6.1" . a ; "symptom"; "4.569055036344757"; "4.4" . a ; "attention deficit hyperactivity disorder"; "21.599169262720665"; "20.8" . a ; "Mental and behavioural disorder"; "Health/Diseases and conditions/Mental and behavioural disorder" . a ; "mental disorders"; "4.731457800511508"; "3.7" . a ; "Attention deficit hyperactivity disorder (ADHD) is a behavioral and neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, which are pervasive, impairing, and otherwise age inappropriate."; "59.31758530183727"; "45.2" . a ; "difficulty"; "10.412926391382404"; "5.8" . a ; "disorder"; "12.772585669781932"; "12.3" . a ; "For a diagnosis, the symptoms have to be present for more than six months, and cause problems in at least two settings (such as school, home, work, or recreational activities). In children, problems paying attention may result in poor school performance."; "18.11023622047244"; "13.8" . a ; "emotions"; "4.984423676012462"; "4.8" . a ; "School"; "Education/School" . a ; "Some individuals with ADHD also display difficulty regulating emotions, or problems with executive function."; "22.572178477690287"; "17.2" . a ; "difficulty"; "6.853582554517134"; "6.6" . a ; "attention deficit hyperactivity disorder"; "32.85457809694793"; "18.3" . a ; "school performance"; "5.626598465473147"; "4.4" . a ; "problem"; "13.824057450628365"; "7.7" . a ; ""; "Environmental research" . a ; ""; "Applied sciences" . a ; ""; "Ecology" . a ; "biology" . a ; "conservation strategy" . a ; "ecology" . a ; "Mediterranean Sea" . a ; "endangered species" . a ; "endangered species" . a ; "ecosystem" . a ; "habitat" . a ; "strategy" . a ; "connectivity" . a ; "protected area" . a ; "conservation" . a ; "management" . a ; "result" . a ; "Mediterranean Sea" . a ; "expert evaluation" . a ; "shelf-slope connectivity" . a ; "framework" . a ; "want" . a ; "Integrated Approach Benthic" . a ; "results of a multi-criteria decision analysis" . a ; "efficient set" . a ; "Mediterranean Basin" . a ; "priority" . a ; "POLYGON ((-8.789062500000002 28.459033019728068, -8.789062500000002 48.69096039092552, 38.14453125000001 48.69096039092552, 38.14453125000001 28.459033019728068, -8.789062500000002 28.459033019728068))"; "-8.789062500000002 28.459033019728068, -8.789062500000002 48.69096039092552, 38.14453125000001 48.69096039092552, 38.14453125000001 28.459033019728068, -8.789062500000002 28.459033019728068" . a ; ; "ddbd57b9-a8be-4d53-a229-920d58905c5c"; "POLYGON ((-8.789062500000002 28.459033019728068, -8.789062500000002 48.69096039092552, 38.14453125000001 48.69096039092552, 38.14453125000001 28.459033019728068, -8.789062500000002 28.459033019728068))" . a ; "service-account-enrichment" . a , , ; "False"; "https://w3id.org/ro-id/6556cdf7-bcef-43d3-a3ce-3d45d14e4a24"; "2022-03-24 18:37:26.444410+00:00"; "https://orcid.org/0000-0002-2736-0052"; , , ; ; ; 228075; "https://api.rohub.org/api/ros/4fd0f1c2-d58f-4b20-9f12-503c31c607d9/crate/download/"; ; "2022-03-24 17:00:15.895312+00:00"; "2024-03-05 12:18:48.335914+00:00"; "2022-03-24 17:00:15.895312+00:00"; "Benthic habitats of the deep Mediterranean Sea and the biodiversity they host are increasingly jeopardized by increasing human pressures, both direct and indirect, which encompass fisheries, chemical and acoustic pollution, littering, oil and gas exploration and production and marine infrastructures (i.e., cable and pipeline laying), and bioprospecting. To this, is added the pervasive and growing effects of human-induced perturbations of the climate system. International frameworks provide foundations for the protection of deep-sea ecosystems, but the lack of standardized criteria for the identification of areas deserving protection, insufficient legislative instruments and poor implementation hinder an efficient set up in practical terms. Here, we discuss the international legal frameworks and management measures in relation to the status of habitats and key species in the deep Mediterranean Basin. By comparing the results of a multi-criteria decision analysis (MCDA) and of expert evaluation (EE), we identify priority deep-sea areas for conservation and select five criteria for the designation of future protected areas in the deep Mediterranean Sea. Our results indicate that areas (1) with high ecological relevance (e.g., hosting endemic and locally endangered species and rare habitats),(2) ensuring shelf-slope connectivity (e.g., submarine canyons), and (3) subject to current and foreseeable intense anthropogenic impacts, should be prioritized for conservation. The results presented here provide an ecosystem-based conservation strategy for designating priority areas for protection in the deep Mediterranean Sea."; "application/ld+json"; , ; "https://w3id.org/ro-id/4fd0f1c2-d58f-4b20-9f12-503c31c607d9"; ; "Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach - snapshot", "Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach"; "MANUAL"; "https://w3id.org/ro-id/4fd0f1c2-d58f-4b20-9f12-503c31c607d9/9233b6cc-5495-423f-9af0-b60a83db22c0"; "Castellan, Giorgio. \"Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach.\" ROHub. Mar 24 ,2022. https://w3id.org/ro-id/4fd0f1c2-d58f-4b20-9f12-503c31c607d9." . a , ; "POLYGON ((-8.789062500000002 28.459033019728068, -8.789062500000002 48.69096039092552, 38.14453125000001 48.69096039092552, 38.14453125000001 28.459033019728068, -8.789062500000002 28.459033019728068))" . a , , ; ; 265816; "https://api.rohub.org/api/resources/54b2de15-6b33-4374-986d-7c20296c8f22/download/"; ; "2022-03-24 17:02:17.046117+00:00"; "2022-03-24 18:37:25.690510+00:00"; "image/jpeg"; ; "fmars-08-698890-t004.jpg"; "2022-03-24 17:02:17.046117+00:00" . a , , ; ; "https://zenodo.org/record/6382778#.YjykQlXMKHs"; ; "2022-03-24 17:04:39.468927+00:00"; "2022-03-24 18:37:26.331838+00:00"; "Priority deep-sea areas for conservation in the deep Mediterranean Sea"; ; "Resources stored in Zenodo"; "2022-03-24 17:04:39.468927+00:00" . a ; dct:conformsTo ; . a . a ; ""; "Earth sciences" . a ; "geology"; "100.0"; "0.8256934881210327" . a ; "water clarity"; "30.407523510971785"; "29.1" . a ; "earth sciences"; "100.0"; "0.8256934881210327" . a ; "collection"; "13.091922005571032"; "9.4" . a ; "Adriatic Sea"; "https://www.wikidata.org/wiki/Q13924" . a ; "space"; "5.153203342618385"; "3.7" . a ; "service-account-enrichment" . a , , ; "False"; "https://w3id.org/ro-id/d0694eaf-a561-4c9f-9a70-17c296da2140"; "2022-03-24 18:42:55.013290+00:00"; "https://orcid.org/0000-0002-2736-0052"; ; ; 533934; "https://api.rohub.org/api/ros/28ff4f3e-c3f8-4bf0-8591-8fa36c378faa/crate/download/"; ; "2021-12-14 10:41:17.716553+00:00"; "2024-03-05 12:16:56.660585+00:00"; "2021-12-14 10:41:17.716553+00:00"; "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/28ff4f3e-c3f8-4bf0-8591-8fa36c378faa"; ; "Analysis from satellite data – Environmental monitoring from space - snapshot", "Analysis from satellite data – Environmental monitoring from space"; "MANUAL"; "https://w3id.org/ro-id/19dabc1d-b24e-4e7b-bbc2-81f95da2f1ad"; "https://w3id.org/ro-id/14888c37-4830-4fd4-9b58-b7364d3b437e", "https://w3id.org/ro-id/1eddab1d-4fc9-422e-92aa-d523326aa498", "https://w3id.org/ro-id/3eaf4867-0bb2-4018-9eac-85eec6ee1309", "https://w3id.org/ro-id/44252c81-5879-4430-9255-66dd383ed651", "https://w3id.org/ro-id/5d7bef7a-401b-4fa7-a0c0-0960ac13899d", "https://w3id.org/ro-id/94781348-96cf-459a-85de-405cc09226a3", "https://w3id.org/ro-id/a3749fdc-4e70-4f7f-979f-8783827dd636", "https://w3id.org/ro-id/af9e7155-28ad-4842-a304-dddf811c4d74", "https://w3id.org/ro-id/f100fb36-2a32-44ca-82c2-7076c5835fa5"; "https://w3id.org/ro-id/0781334a-7a44-4a75-bae6-9b830ce25370", "https://w3id.org/ro-id/136ded1a-6eba-470a-bd33-d741aee77ada"; "https://w3id.org/ro-id/6b83b885-0507-4e13-b35c-7aa124395fc2"; "https://w3id.org/ro-id/3866bcdc-c291-40bf-b3cc-63b22d75e3d5", "https://w3id.org/ro-id/386c8b2a-a98e-45da-b12a-8aa8d05d4e3b", "https://w3id.org/ro-id/6102d84d-2021-4d87-8ef7-17da4930646b", "https://w3id.org/ro-id/6a7f5310-1a78-453d-ab8b-a5c9b320a4f6", "https://w3id.org/ro-id/84271559-7e77-418f-a01c-b38b283b6183", "https://w3id.org/ro-id/9cb825ce-e452-4549-abe2-2fdb59ae48b6", "https://w3id.org/ro-id/ca4eaea0-0558-4095-b77f-cd7fc8bd1bfa"; "https://w3id.org/ro-id/2c11942c-9936-43aa-a307-fed88ea783c4", "https://w3id.org/ro-id/456025f5-a651-498b-9f0a-15e56cd985bc"; "https://w3id.org/ro-id/0980e44a-005d-4804-8a6f-cb82bd6123e9", "https://w3id.org/ro-id/75705433-1cc5-403c-baec-1bcd78a366a7", "https://w3id.org/ro-id/91973553-ac02-4802-b419-47e6a54e2c06", "https://w3id.org/ro-id/9760a79e-83ec-4e0a-9ee6-eb5ed95998c7", "https://w3id.org/ro-id/f139b59a-eda3-4aab-ace7-68ad65bc1443"; "https://w3id.org/ro-id/c7fe0e0f-b774-44ab-9d23-4ef5608890c4", "https://w3id.org/ro-id/f8b11e82-83e5-4022-ad0e-7f1229396a5c", "https://w3id.org/ro-id/fcc1bbf5-28df-4f6e-b562-bc9fa809d641"; "Castellan, Giorgio. \"Analysis from satellite data – Environmental monitoring from space.\" ROHub. Dec 14 ,2021. https://doi.org/10.5281/zenodo.6383036." . a , ; "Discover, subset, download and visualize satellite data stored in a Data Cube from the ADAM Platform"; ; "Method" . a , ; "Results"; , ; "Results" . a , ; "Satellite data on Chl-a and Kd490"; ; "Satellite_data" . a , , ; ; 68452; "https://api.rohub.org/api/resources/38441693-b827-4108-b4d5-b0d854030c88/download/"; ; "2021-12-14 14:32:01.240770+00:00"; "2022-03-24 18:42:53.767383+00:00"; "image/png"; ; "Diffuse attenuation coefficient at 490 nm (Kd490) in 2018 in the north Adriatic Sea"; "2021-12-14 14:32:01.240770+00:00" . a , , ; ; 449579; "https://api.rohub.org/api/resources/67b0bcab-22ec-4e02-8f28-37670338943c/download/"; ; "2021-12-14 14:38:21.837867+00:00"; "2022-03-24 18:42:50.464712+00:00"; "image/jpeg"; ; "Analysis from satellite data – Environmental monitoring from space during COVID-19 lockdown"; "2021-12-14 14:38:21.837867+00:00" . a , , ; ; "https://w3id.org/ro-id/894d3a33-8340-497d-beaf-5b9d85c9bfc7"; ; "2021-12-14 10:44:17.433059+00:00"; "2022-03-24 18:42:54.929213+00:00"; "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown"; ; "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown"; "2021-12-14 10:44:17.433059+00:00" . a , , ; ; 70005; "https://api.rohub.org/api/resources/85c7ebc3-6c32-4573-a828-96044eb3f9a2/download/"; ; "2021-12-14 14:33:06.849172+00:00"; "2022-03-24 18:42:52.754796+00:00"; "image/png"; ; "Diffuse attenuation coefficient at 490 nm (Kd490) in 2018 in the north Adriatic Sea"; "2021-12-14 14:33:06.849172+00:00" . a , , ; ; "https://w3id.org/ro-id/34d648b3-0014-4a19-8469-40b9380ca4c3"; ; "2021-12-14 10:44:48.894463+00:00"; "2022-03-24 18:42:51.867845+00:00"; "Discover and subset satellite data from the ADAM Platform"; ; "Discover and subset satellite data from the ADAM Platform"; "2021-12-14 10:44:48.894463+00:00" . a ; dct:conformsTo ; . a ; "geosciences"; "100.0"; "0.4130299687385559" . a ; "environmental monitoring"; "11.413748378728926"; "8.8" . a ; "analysis"; "13.618677042801558"; "10.5" . a ; "result"; "4.735376044568246"; "3.4" . a ; "water"; "11.142061281337048"; "8.0" . a ; "geophysics"; "100.0"; "0.4130299687385559" . a ; "lockdown"; "15.459610027855154"; "11.1" . a ; "clarity"; "12.5810635538262"; "9.7" . a ; "collection"; "11.932555123216602"; "9.2" . a ; "Satellite technology"; "Economy, business and finance/Economic sector/Computing and information technology/Satellite technology" . a ; "environmental monitoring from space"; "11.598746081504702"; "11.1" . a ; "satellite data"; "23.47600518806745"; "18.1" . a ; "effects of COVID-19 lockdown"; "15.256008359456635"; "14.6" . a ; "Adriatic Sea"; "11.142061281337048"; "8.0" . a ; "analysis from satellite data"; "17.03239289446186"; "16.3" . a ; "lockdown"; "14.785992217898833"; "11.4" . a ; "analysis"; "14.902506963788301"; "10.7" . a ; "environmental monitoring"; "11.420612813370472"; "8.2" . a ; "Analysis from satellite data –"; "22.02202202202202"; "22.0" . a ; "covid 19"; "12.191958495460442"; "9.4" . a . a ; "clarity"; "12.95264623955432"; "9.3" . a ; "analysis of satellite data"; "25.705329153605014"; "24.6" . a ; "Environmental monitoring from space."; "8.708708708708707"; "8.7" . a ; "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea"; "69.26926926926926"; "69.2" . a . a ; "Music Classification Study musical genre classification" . a ; "music classification study musical genre classification" . a ; "television" . a ; "musical genre classification" . a ; "warning messsage" . a ; "education" . a ; "Linux" . a , ; "http", "http" . a ; "musical genre" . a ; "feature" . a ; "classification" . a ; "Java" . a ; "lib 3" . a ; "audio" . a ; "install" . a ; "classification by ensemble" . a ; "Music" . a ; "libraries in the lib" . a ; "Taverna Workbench 2.3.0 from http" . a ; "user" . a ; "taverna installation" . a ; "Java" . a ; "Classification" . a ; "version" . a ; "directory" . a ; "release" . a ; "ensemble" . a ; "musical genre classification by ensemble" . a ; "lyrics feature" . a ; "classification by ensembles of audio and lyrics feature" . a ; "service-account-enrichment" . a , , ; pav:importedBy ; "http://sandbox.rohub.org/rodl/ROs/musicStudy-5/"; "2014-07-29T15:05:31.747+02:00"; "https://www.google.com/accounts/o8/id?id=AItOawl6miGQ2NYnbP2-gtGZcqRkDRukz5GNfGc"; ; 4451939; "https://api.rohub.org/api/ros/0741085b-b411-4b53-b00e-1311fecc8410/crate/download/"; ; "2014-07-29 12:47:19.237000+00:00"; "2025-03-05 01:04:17.160177+00:00"; "2014-07-29 12:47:19.237000+00:00"; "Musical genre classification by ensembles of audio and lyrics features"; "application/ld+json"; , , , , ; "https://w3id.org/ro-id/0741085b-b411-4b53-b00e-1311fecc8410"; ; "Music Classification Study"; "Raul Palma. \"Music Classification Study.\" ROHub. Jul 29 ,2014. https://w3id.org/ro-id/0741085b-b411-4b53-b00e-1311fecc8410." . a , ; "used" . a , ; , , ; "workflows" . a , ; "setup" . a , ; "produced" . a , ; ; "main" . a , ; , , , ; "config" . a , ; "scripts" . a , ; "components" . a , ; "nested" . a , ; "lib" . a , ; "results" . a , ; "web services" . a , ; , ; "datasets" . a , ; "inputs" . a , ; "software" . a , ; , ; "biblio" . a , , ; ; 160008; "https://api.rohub.org/api/resources/02e2583c-cdb9-4948-b919-be41adaab300/download/"; ; "2014-07-29 13:04:04.741000+00:00"; "2022-03-25 08:54:50.057415+00:00"; ; "MusicClassification_WSDL-final.t2flow"; "2014-07-29 13:04:04.741000+00:00" . a ; dct:conformsTo ; . a ; "Raul Palma" . a , ; "service-account-generation-service", "service-account-generation-service" . a . a ; "Biosemantics" . a ; "memory" . a ; "epigenetic role" . a ; "deregulate in HD" . a ; "chromatin analysis" . a ; "deregulate in HD" . a ; "gene deregulation" . a ; "gene" . a , ; "research", "research" . a ; "chromatin" . a ; "web service" . a ; "interpretation" . a ; "analysis" . a , ; "workflow", "workflow" . a ; "deregulation" . a ; "system" . a ; "HD" . a ; "participate in epigenetic process" . a ; "HD" . a ; "epigenetic process" . a ; "Genoa" . a ; "participate in epigenetic processes" . a ; "HD gene deregulation" . a ; "chromatin data interpretation" . a ; "epigenetic" . a ; "genetics" . a ; "anni web services" . a ; "research" . a ; "have an epigenetic role" . a ; "aim" . a ; "role" . a ; "information" . a ; "HD chromatin analysis" . a ; "Genoa" . a ; "have an epigenetic role" . a ; "service-account-enrichment" . a , , ; pav:importedBy ; "http://sandbox.rohub.org/rodl/ROs/data_interpretation-2/"; "2014-02-26T14:16:20.355+01:00"; "https://www.google.com/accounts/o8/id?id=AItOawlLcpRhy-5MtgIVFxuwLWcFFys5ZTC7w2c"; ; 81314; "https://api.rohub.org/api/ros/d1b1d427-2332-428e-a205-726ac7a0e951/crate/download/"; ; "2014-02-21 13:36:32.163000+00:00"; "2025-03-05 00:48:41.666693+00:00"; "2014-02-21 13:36:32.163000+00:00"; "

This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/d1b1d427-2332-428e-a205-726ac7a0e951"; ; "HD data interpretation", "chromatin data interpretation"; "Eleni Mina. \"chromatin data interpretation.\" ROHub. Feb 21 ,2014. https://w3id.org/ro-id/d1b1d427-2332-428e-a205-726ac7a0e951." . a , ; , , , , ; "data_interpretation" . a , , ; ; 30787; "https://api.rohub.org/api/resources/0390ff51-55a1-4af3-b99c-60ef059d0afc/download/"; ; "2014-02-25 16:10:46.463000+00:00"; "2022-03-25 09:07:52.840714+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "List Predefined Concept Sets"; "2014-02-25 16:10:46.463000+00:00" . a , , ; ; 188023; "https://api.rohub.org/api/resources/45b81758-2d25-4c33-87c8-cb2968fbd849/download/"; ; "2014-02-25 16:12:14.228000+00:00"; "2022-03-25 09:07:51.492625+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2014-02-25 16:12:14.228000+00:00" . a , , ; ; 63; "https://api.rohub.org/api/resources/7a3f5ba3-b292-4c80-b0a1-76a15b20e50c/download/"; ; "2014-02-25 16:03:44.993000+00:00"; "2022-03-25 09:07:53.677489+00:00"; "text/plain"; ; "hypothesis.txt"; "2014-02-25 16:03:44.993000+00:00" . a , , ; ; 203555; "https://api.rohub.org/api/resources/7aa50a5a-bc9a-4639-9e04-1fecc9bb5002/download/"; ; "2014-02-25 16:06:54.756000+00:00"; "2022-03-25 09:07:55.632943+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-25 16:06:54.756000+00:00" . a , , ; ; 69369; "https://api.rohub.org/api/resources/99ba79b8-8172-4026-93b2-affd7320122f/download/"; ; "2014-02-26 13:14:06.663000+00:00"; "2022-03-25 09:07:56.525975+00:00"; """This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group). This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/282 for functional gene and SNP annotation and knowledge discovery."""; ; "Explain concept scores"; "2014-02-26 13:14:06.663000+00:00" . a , , ; ; 67; "https://api.rohub.org/api/resources/da150b5d-9fd0-46fc-9745-06460dbed48e/download/"; ; "2014-02-25 16:03:12.283000+00:00"; "2022-03-25 09:07:49.577479+00:00"; "text/plain"; ; "conclusions.txt"; "2014-02-25 16:03:12.283000+00:00" . a , , ; ; 41692; "https://api.rohub.org/api/resources/dcaecdee-b61a-4d22-9610-be3770345a8e/download/"; ; "2014-02-25 16:09:23.429000+00:00"; "2022-03-25 09:07:54.760474+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2014-02-25 16:09:23.429000+00:00" . a , , ; ; 39476; "https://api.rohub.org/api/resources/f34bc6b5-f6ab-41e7-b2fe-bd83df7041b6/download/"; ; "2014-02-25 16:04:13.823000+00:00"; "2022-03-25 09:07:50.657598+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2014-02-25 16:04:13.823000+00:00" . a ; dct:conformsTo ; . a ; "Eleni Mina" . a ; "Eleni Mina" . a . a ; "D3.1: Workflow Evolution, Sharing and Collaboration Initial Requirements" . a ; "Taverna 2.4" . a ; "HYPERLEDA. I. 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This study characterizes each galaxy of this sample through both the measurement of basic astrophysical properties:  - The equatorial coordinates in J2000 epoch - The velocities in km/s (v) - The dust extinction coefficient (ag) - The axis ratio of the isophote 25 mag/arcsec2 (logr25) - The apparent total B magnitude (BT) - The morphological type (t) and the calculation of the more complex properties: - The distance in Mega parsecs (D) - The corrected apparent B magnitude (btc) - The optical luminosity in B-band (LB) Specifically, this research object is focused on the calculation of the intrinsic luminosity in the Johnson B-band, in order to achieve it the measurement or calculation of all those astrophysical properties is needed. All the data involved in the characterization of the sample are stored in a local relational MySQL database. 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"https://w3id.org/ro-id/5c589b0d-0fd4-4e10-a949-254f733bad51", "https://w3id.org/ro-id/a8bea726-82f1-4049-a93d-facd6d258724", "https://w3id.org/ro-id/d80cc364-e913-48af-842d-45af832e8775"; "Eleni Mina. \"Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/.\" ROHub. Aug 30 ,2013. https://w3id.org/ro-id/3a129ea9-7d50-4d4a-bcce-499729c5f3e0." . a , ; , , , , ; "data_interpretation" . a , ; ; 41573; "https://api.rohub.org/api/resources/4264530f-42e9-45f0-9255-d232a3a558ac/download/"; ; "2013-11-05 13:09:46.561000+00:00"; "2022-03-25 09:24:37.622734+00:00"; "Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group)."; ; "Explain Scores"; "2013-11-05 13:09:46.561000+00:00" . a , , ; ; 67; "https://api.rohub.org/api/resources/4e604e6a-6c92-414d-a49e-4e67a8b39116/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:24:40.710743+00:00"; "text/plain"; ; "conclusion"; "2013-08-31 15:11:30.970000+00:00" . a , , ; ; 188023; "https://api.rohub.org/api/resources/55c4a47f-eb4d-4461-aaf3-f718a38bc803/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:24:47.224634+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; 214639; "https://api.rohub.org/api/resources/5872d7d2-57d6-4b92-854a-815c2dc665b4/download/"; ; "2014-02-11 15:25:01.110000+00:00"; "2022-03-25 09:24:49.007856+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-11 15:25:01.110000+00:00" . a , , ; ; 39476; "https://api.rohub.org/api/resources/7a77bf73-c2d0-41ca-8a13-b91c31de14d8/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:24:39.842471+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; 63; "https://api.rohub.org/api/resources/97a1ffa9-8d56-4499-827b-8d4e2d313fbc/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:24:28.805556+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a , , ; ; 30787; "https://api.rohub.org/api/resources/ab98dfb6-be33-4c6d-bb69-1ecccdac03b8/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:24:44.673277+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; 41692; "https://api.rohub.org/api/resources/f0c4d8f6-4ef6-43bd-806f-f6ee04fe6cbf/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:24:48.176013+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a ; dct:conformsTo ; . a ; "gene"; "3.399327605528577"; "9.1" . a ; "earth sciences"; "47.691405491207696"; "0.9814894795417786" . a ; "role"; "5.363204344874406"; "15.8" . a ; "missing link"; "4.514596062457569"; "13.3" . a ; "analyzation"; "1.4596062457569585"; "4.3" . a ; "life sciences"; "35.76177208527657"; "0.9203993678092957" . a ; "HD"; "4.632050803137841"; "12.4" . a ; "analysis of Ro"; "3.843514070006863"; "11.2" . a ; "Animal"; "Human interest/Animal" . a ; "system"; "3.6320434487440596"; "10.7" . a ; "deregulation"; "9.911744738628649"; "29.2" . a ; "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/. This RO is an extension of the HD chromatin analysis to interpret the results and reveal missing links that can according to literature explain HD gene deregulation"; "33.333333333333336"; "100.0" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "HD"; "3.8696537678207736"; "11.4" . a ; "deregulation"; "3.598099117447386"; "10.6" . a ; "geochemistry"; "27.692441186701984"; "0.5699106454849243" . a ; "hard drive"; "4.107264086897488"; "12.1" . a ; "earth sciences"; "27.692441186701984"; "0.5699106454849243" . a ; "life sciences"; "35.87466373187602"; "0.9233048558235168" . a ; "epigenetic"; "1.357773251866938"; "4.0" . a ; "HD gene deregulation"; "11.358956760466711"; "33.1" . a ; "deregulation"; "11.31864026895779"; "30.3" . a ; "analysis"; "3.0257751214045574"; "8.1" . a ; "Genoa"; "25.476279417258127"; "68.2" . a ; "linguistics"; "100.0"; "7.7" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "HD"; "8.06873365707882"; "21.6" . a ; "genes involved in HD gene deregulation have an epigenetic role"; "33.333333333333336"; "100.0" . a ; "deregulation"; "4.333208815838626"; "11.6" . a ; "http"; "2.0706042090970804"; "6.1" . a ; "gene"; "14.60590212924916"; "39.1" . a ; "gene deregulation"; "1.8188057652711047"; "5.3" . a ; "Ro"; "4.989816700610998"; "14.7" . a ; "chromatin analysis"; "0.857927247769389"; "2.5" . a ; "HD gene deregulation"; "25.806451612903224"; "75.2" . a ; "geology"; "24.616153322090323"; "0.5066006183624268" . a ; "earth sciences"; "24.616153322090323"; "0.5066006183624268" . a ; "Ro"; "5.790063503922301"; "15.5" . a ; "outcome"; "1.2219959266802443"; "3.6" . a ; "Language"; "Arts, culture and entertainment/Culture/Language" . a ; "Genes deregulated in HD, are participating in epigenetic processes"; "33.333333333333336"; "100.0" . a ; "HD chromatin analysis"; "14.13864104323953"; "41.2" . a ; "life sciences (general)"; "28.363564182847412"; "0.7299919724464417" . a ; "gene"; "13.06856754921928"; "38.5" . a ; "results from the analysis"; "1.3040494166094714"; "3.8" . a ; "deregulate in HD"; "16.197666437886067"; "47.2" . a ; "gene"; "2.919212491513917"; "8.6" . a , ; "Eleni Mina", "Eleni Mina" . a , ; "service-account-generation-service", "service-account-generation-service" . a . a ; "involve in HD gene deregulation" . a , ; "HD", "HD" . a ; "participate in epigenetic processes" . a , ; "genetics", "genetics" . a , ; "genes", "genes" . a ; "have an epigenetic role" . a , ; "Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group)."; "Explain Scores" . a ; "testing"; "2.545824847250509"; "7.5" . a ; "HD"; "8.06873365707882"; "21.6" . a ; "life sciences (general)"; "35.87466373187602"; "0.9233048558235168" . a ; "hard drive"; "4.107264086897488"; "12.1" . a ; "http"; "2.0706042090970804"; "6.1" . a ; "analysis of Ro"; "3.843514070006863"; "11.2" . a ; "Ro"; "5.790063503922301"; "15.5" . a ; "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/. This RO is an extension of the HD chromatin analysis to interpret the results and reveal missing links that can according to literature explain HD gene deregulation"; "33.333333333333336"; "100.0" . a ; "genes involved in HD gene deregulation have an epigenetic role"; "33.333333333333336"; "100.0" . a ; "deregulation"; "4.333208815838626"; "11.6" . a ; "gene deregulation"; "1.8188057652711047"; "5.3" . a ; "gene"; "2.919212491513917"; "8.6" . a ; "Ro"; "4.989816700610998"; "14.7" . a ; "system"; "3.6320434487440596"; "10.7" . a ; "earth sciences"; "24.616153322090323"; "0.5066006183624268" . a ; "earth sciences"; "27.692441186701984"; "0.5699106454849243" . a ; "HD"; "4.632050803137841"; "12.4" . a ; "epigenetic"; "1.357773251866938"; "4.0" . a ; "geology"; "47.691405491207696"; "0.9814894795417786" . a ; "role"; "5.491221516623086"; "14.7" . a ; "results from the analysis"; "1.3040494166094714"; "3.8" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "deregulate in HD"; "16.197666437886067"; "47.2" . a ; "life sciences (general)"; "28.363564182847412"; "0.7299919724464417" . a ; "gene"; "14.60590212924916"; "39.1" . a ; "deregulation"; "11.31864026895779"; "30.3" . a ; "life sciences (general)"; "35.76177208527657"; "0.9203993678092957" . a ; "epigenetic"; "1.5274949083503053"; "4.5" . a ; "geology"; "24.616153322090323"; "0.5066006183624268" . a ; "epigenetic process"; "17.84488675360329"; "52.0" . a ; "service-account-enrichment" . a , , ; pav:importedBy ; "http://sandbox.rohub.org/rodl/ROs/data_interpretation/"; "2014-02-11T16:00:29.893+01:00"; "https://www.google.com/accounts/o8/id?id=AItOawnOAeiyuU0cZ91YBD1EW7d43AlWw8xdALU"; ; 81525; "https://api.rohub.org/api/ros/95a9036b-bee9-48fb-81eb-7e9a90014293/crate/download/"; ; "2013-08-30 16:15:52.229000+00:00"; "2025-03-05 00:55:19.037479+00:00"; "2013-08-30 16:15:52.229000+00:00"; "This RO is an extension of the HD chromatin analysis to interpret the results and reveal missing links that can according to literature explain HD gene deregulation"; 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"https://w3id.org/ro-id/0ef41513-eaa9-4e76-994a-e90587f4069e", "https://w3id.org/ro-id/80f188fc-a15a-40e1-9843-303b0be67656", "https://w3id.org/ro-id/8978ed0f-74e3-4ca4-bea3-c366b5ac4a27", "https://w3id.org/ro-id/b8bcb4cf-ba2b-438b-a8e3-d9e460152a09", "https://w3id.org/ro-id/cb11d942-fce9-459d-bfe2-4a4ed9d1fe1d", "https://w3id.org/ro-id/e24af000-2fbd-4820-bf60-bd01890f4b89"; "https://w3id.org/ro-id/15ba1d7a-c420-4e56-870a-99df018d8907", "https://w3id.org/ro-id/2b8c0d56-d5b4-4689-a663-1752b449dc0a", "https://w3id.org/ro-id/78cd33c6-3425-4ecf-a833-00cf96855d21", "https://w3id.org/ro-id/7f465c71-cf0c-4f7d-8406-3eaef5ad7c0b", "https://w3id.org/ro-id/93f1ab58-022a-4598-97f7-7807f93f2aa1", "https://w3id.org/ro-id/9d438ec7-40ed-4892-a79f-86270050c4f8", "https://w3id.org/ro-id/a852c4bf-efeb-436b-951e-b4dc59e1e4b7", "https://w3id.org/ro-id/aa30e810-a7cf-4844-9c02-c5f2cb97b671", "https://w3id.org/ro-id/af8a543b-f09a-4484-9a01-66fdcadbd631", "https://w3id.org/ro-id/d6a3e45a-7fea-4bce-89ce-e0c2574d972f", "https://w3id.org/ro-id/e907a28b-718c-45b7-9531-0e556e167c0c", "https://w3id.org/ro-id/f8fb6331-272a-4818-ad9a-1fa334ce7606"; "https://w3id.org/ro-id/1b53e2a7-75e0-4b9a-97e0-c61af6f89d96", "https://w3id.org/ro-id/1da386ca-5f4b-4458-9db0-2dfb98944d22", "https://w3id.org/ro-id/fa01854e-8511-436f-9f73-5e8db98dec87"; "Eleni Mina. \"Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/.\" ROHub. Aug 30 ,2013. https://w3id.org/ro-id/95a9036b-bee9-48fb-81eb-7e9a90014293." . a , ; , , , ; "data_interpretation" . a , , ; ; 67; "https://api.rohub.org/api/resources/207ea21e-4180-4f98-a6e9-9906672c0f49/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:26:52.370638+00:00"; "text/plain"; ; "conclusions.txt"; "2013-08-31 15:11:30.970000+00:00" . a , , ; ; 30787; "https://api.rohub.org/api/resources/2328b548-0032-4dfb-97dd-2892668282c5/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:27:02.866468+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; 41692; "https://api.rohub.org/api/resources/574c5f85-a2ea-484f-92e6-f11fe184661d/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:27:05.517990+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a , , ; ; 203555; "https://api.rohub.org/api/resources/71f79523-cf5b-48fb-b7b9-92ec04636326/download/"; ; "2013-11-05 13:07:17.887000+00:00"; "2022-03-25 09:27:03.799736+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2013-11-05 13:07:17.887000+00:00" . a , , ; ; 39476; "https://api.rohub.org/api/resources/a220e0d8-7cdd-40ba-a8a5-6b264086dde3/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:26:58.184590+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; 188023; "https://api.rohub.org/api/resources/a8461986-76a4-49b2-8153-4c899df13854/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:27:04.663380+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; 63; "https://api.rohub.org/api/resources/e60c67e6-6657-4ddf-99ed-b47687ce684c/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:26:50.571966+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a ; dct:conformsTo ; . a ; "Language"; "Arts, culture and entertainment/Culture/Language" . a ; "Animal"; "Human interest/Animal" . a ; "analysis"; "3.0257751214045574"; "8.1" . a ; "have an epigenetic role"; "0.06863417982155112"; "0.2" . a ; "participate in epigenetic process"; "0.20590253946465337"; "0.6" . a ; "chromatin analysis"; "0.857927247769389"; "2.5" . a ; "HD"; "3.9596563317146063"; "10.6" . a ; "HD gene deregulation"; "11.358956760466711"; "33.1" . a ; "geochemistry"; "27.692441186701984"; "0.5699106454849243" . a ; "HD"; "3.8696537678207736"; "11.4" . a ; "chromatin"; "4.59469555472544"; "12.3" . a ; "life sciences"; "35.87466373187602"; "0.9233048558235168" . a ; "missing link"; "4.514596062457569"; "13.3" . a ; "Genoa"; "25.476279417258127"; "68.2" . a ; "missing link"; "5.304445274561076"; "14.2" . a ; "life sciences"; "35.76177208527657"; "0.9203993678092957" . a ; "Genoa"; "20.570264765784113"; "60.6" . a ; "gene"; "13.06856754921928"; "38.5" . a ; "analyzation"; "1.4596062457569585"; "4.3" . a ; "earth sciences"; "47.691405491207696"; "0.9814894795417786" . a ; "chromatin"; "4.039375424304141"; "11.9" . a ; "epigenetic role"; "6.554564172958133"; "19.1" . a ; "deregulation"; "3.598099117447386"; "10.6" . a ; "gene"; "3.399327605528577"; "9.1" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "life sciences"; "28.363564182847412"; "0.7299919724464417" . a ; "role"; "5.363204344874406"; "15.8" . a ; "HD gene deregulation"; "25.806451612903224"; "75.2" . a ; "outcome"; "1.2219959266802443"; "3.6" . a ; "deregulation"; "9.911744738628649"; "29.2" . a ; "HD"; "8.146639511201629"; "24.0" . a ; "HD chromatin analysis"; "14.13864104323953"; "41.2" . a ; "Genes deregulated in HD, are participating in epigenetic processes"; "33.333333333333336"; "100.0" . a ; "linguistics"; "100.0"; "7.7" . a . a ; "gene deregulation" . a ; "Huntington's disease gene deregulation" . a ; "HepG Permuted HNF" . a ; "channel subunit" . a ; "cell change" . a ; "mRNAs encod ing proton channel subunit" . a ; "frontal cortex" . a ; "HD brain" . a ; "Johann Sebastian Bach" . a ; "aberrantprotein protein interaction" . a ; "United States of America" . a ; "New Hampshire" . a ; "unfolded protein response protein" . a ; "anatomy" . a ; "enrichment" . a ; "enhancers" . a ; "activity" . a ; "caudate nucleus" . a ; "a number of mRNA" . a ; "mRNA change" . a ; "HepG HUVECHSMMNHLFNHEKHMEC" . a ; "chromatin" . a ; "motif" . a ; "cell type" . a ; "BA" . a ; "changes" . a ; "cell" . a ; "clusters" . a ; "state" . a ; "islands" . a ; "kB" . a ; "s disease brain" . a ; "disease" . a ; "mRNA" . a ; "disease"; "2.4802890932982917"; "15.1" . a ; "cortices"; "1.7575558475689883"; "10.7" . a ; "epigenetic phenomena"; "2.56078634247284"; "9.9" . a ; "epigenetic dataset"; "1.0346611484738748"; "4.0" . a ; "Genetics"; "Science and technology/Natural science/Biology/Genetics" . a ; "genetics"; "19.45945945945946"; "43.2" . a ; "caudate nucleus"; "1.3961892247043366"; "8.5" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "Overall, the regional changes in gene expression areconsistent with the neuropathology in early grade HD, withcaudate being the most affected area, the cerebellum andBA cortex being relatively spared and the BA cortexshowing an intermediate pathology."; "2.9443254817987152"; "11.0" . a ; "Nova Scotia"; "https://www.wikidata.org/wiki/Q1952" . a ; "Ro"; "1.9077901430842608"; "7.2" . a ; "cerebellum"; "1.5768725361366625"; "9.6" . a ; "sample"; "1.806833114323259"; "11.0" . a ; "experiment document"; "2.56078634247284"; "9.9" . a ; "workflow"; "2.3582405935347115"; "8.9" . a ; "recentneuroimaging data"; "1.5002586652871184"; "5.8" . a ; "Mental and behavioural disorder"; "Health/Diseases and conditions/Mental and behavioural disorder" . a ; "biology"; "6.126126126126126"; "13.6" . a ; "chemistry"; "5.585585585585585"; "12.4" . a ; "Diseases and conditions"; "Health/Diseases and conditions" . a ; "gene"; "11.990801576872537"; "73.0" . a ; "University of California, Berkeley"; "https://www.wikidata.org/wiki/Q168756" . a ; "biochemistry"; "17.34234234234234"; "38.5" . a ; "Huntington's disease gene deregulation"; "44.43869632695292"; "171.8" . a ; "Auckland City"; "https://www.wikidata.org/wiki/Q758634" . a ; "deregulation"; "9.937582128777924"; "60.5" . a ; "Vinh Yên"; "https://www.wikidata.org/wiki/Q36088" . a ; "geophysics"; "5.460552638139745"; "0.20815198123455048" . a ; "disease"; "2.888182299947006"; "10.9" . a ; "Genetics"; "Science and technology/Natural science/Biology/Genetics" . a ; "change"; "2.266754270696452"; "13.8" . a ; "Mental and behavioural disorder"; "Health/Diseases and conditions/Mental and behavioural disorder" . a ; "Hutchinson"; "https://www.wikidata.org/wiki/Q958555" . a ; "brain"; "1.192368839427663"; "4.5" . a ; "Wales"; "https://www.wikidata.org/wiki/Q25" . a ; "geology"; "72.8531489829241"; "2.6746557652950287" . a ; "epigenetic mechanism"; "1.810657009829281"; "7.0" . a ; "Columbia University"; "https://www.wikidata.org/wiki/Q49088" . a ; "environmental sciences"; "27.1468510170759"; "0.9966416358947754" . a ; "gene deregulation"; "2.8453181583031557"; "11.0" . a ; "Organic chemical"; "Economy, business and finance/Economic sector/Chemicals/Organic chemical" . a ; "Huntington's disease"; "17.6205617382088"; "66.5" . a ; "l Globin"; "1.5002586652871184"; "5.8" . a ; "In addition we include all related to our experiment documents, papers and datasets"; "2.43576017130621"; "9.1" . a ; "data comefrom"; "1.577858251422659"; "6.1" . a ; "phenomenon"; "2.266754270696452"; "13.8" . a ; "chicken chicken e Globin c Globin"; "0.6725297465080186"; "2.6" . a ; "Huntington s disease (HD) pathology is well understood at a histological level but a comprehensivemolecular analysis of the effect of the disease in the human brain has not previously been available."; "3.747323340471092"; "14.0" . a ; "life sciences"; "94.53944736186025"; "3.603769540786743" . a ; "Lausanne"; "https://www.wikidata.org/wiki/Q807" . a ; "medicine"; "23.73873873873874"; "52.7" . a ; "earth sciences"; "72.8531489829241"; "2.6746557652950287" . a ; "epigenetic information"; "2.1986549405069837"; "8.5" . a ; "Animal"; "Human interest/Animal" . a ; "Massachusetts"; "https://www.wikidata.org/wiki/Q771" . a ; "Cardiff"; "https://www.wikidata.org/wiki/Q3398450" . a ; 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Release Date : Start Field Description Dot character identifier for a given station GAGE Number sec phase epochs in hours for combined RMS calculation PRMS Root mean square (RMS) scatter of combined phase residuals, mm CWU Number sec phase epochs in hours for CWU RMS calculation CRMS Root mean square (RMS) scatter of CWU phase residuals, mm NMT Number sec phase epochs in hours for NMT or BSL (prior to Feb ) RMS calculation NRMS Root mean square (RMS) scatter of NMT or BSL phase residuals, mm A Coefficient from model fit RMS (elev) A B /sin(elev) where elev is elevation angle, mm B Coefficient from model fit, mm GPSW GPS Week for hour processing day D GPS Day of week for hour processing day YYYYMMDD Year, month, day of month for hour processing day End Field Description Dot GAGE PRMS CWU CRMS NMT NRMS A B GPSW D YYYYMMDD NSU . . . . . ULM . . . . . ODM . . . . . AB . . . . . AB . . . . . ZME . . . . . ZMP . . . . . ZNY . . . . . ZSE . . . . . 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The time series LS analysis is the one that generates the monthly GAGE SNAPSHOT fields."""; "1.5412511332728922"; "1.7" . a ; "geosciences"; "43.04185052089376"; "0.643273115158081" . a ; "UNAVCO"; "4.046997389033943"; "6.2" . a ; "Musical instrument"; "Arts, culture and entertainment/Arts and entertainment/Music/Musical instrument" . a ; "Southern California Integrated GPS Network"; "3.9164490861618804"; "6.0" . a ; "Space programme"; "Science and technology/Research/Scientific exploration/Space programme" . a ; "GPS"; "5.1566579634464755"; "7.9" . a ; "standard deviation"; "2.93733681462141"; "4.5" . a ; "file format"; "3.133159268929504"; "4.8" . a ; "list"; "3.7206266318537864"; "5.7" . a ; "Science and technology"; "Science and technology" . a ; "PBO GKNA PBO GKI G"; "2.037617554858934"; "2.6" . a ; "PbO"; "9.725848563968668"; "14.9" . a ; "GKNA NMT GKNA"; "2.115987460815047"; "2.7" . a ; "PBO GKNA PBO TSLS"; "3.2915360501567394"; "4.2" . a ; "rms calculation NRMS root mean square" . a ; "scatter of NMT" . a ; "site coordinate information" . a ; "file naming" . a ; "GAGE GPS data analysis plan" . a ; "geodetic products" . a ; "GPS data analysis method" . a ; "Musical instrument"; "Arts, culture and entertainment/Arts and entertainment/Music/Musical instrument" . a ; "gage reference frame"; "2.3510971786833856"; "3.0" . a ; "Jet Propulsion Laboratory"; "https://www.wikidata.org/wiki/Q189325" . a ; "geology"; "41.24948833068723"; "0.9902867078781128" . a ; "GPS"; "5.1566579634464755"; "7.9" . a ; "PbO"; "9.725848563968668"; "14.9" . a ; "of the Aug-23-2011" . a ; "netsel.use list"; "2.664576802507837"; "3.4" . a ; "Treaty"; "Politics/International relations/Diplomacy/Treaty" . a ; "Scripps Orbit and Permanent Array Center"; "7.915360501567398"; "10.1" . a ; "list"; "3.7206266318537864"; "5.7" . a ; "mathematics"; "14.896755162241888"; "20.2" . a ; "geology"; "27.293525495972574"; "0.6552424430847168" . a ; "GKNA NMT GKNA"; "2.115987460815047"; "2.7" . a ; "earth sciences"; "27.293525495972574"; "0.6552424430847168" . a ; "field"; "4.308093994778068"; "6.6" . a ; "noise"; "3.149350649350649"; "9.7" . a ; "Data from GPS stations not archived by UNAVCO are obtained from the NOAA National Geodetic Survey (NGS) Continuously Operating Reference Station (CORS) data center, the NASA Crustal Dynamics Data Information System (CDDIS), the U.S. Geological Survey, the Scripps Orbit and Permanent Array Center (SOPAC), and the International GNSS Service (IGS)"; "22.665457842248415"; "25.0" . a ; """GLOBK SINEX combinations, GK ( ) time series analyses using weighted least squares (LS) and ( ) time series analyses using a Kalman filter of the time series (KF). The time series LS analysis is the one that generates the monthly GAGE SNAPSHOT fields."""; "1.5412511332728922"; "1.7" . a ; "database"; "2.359882005899705"; "3.2" . a ; "University"; "Education/School/Higher education/University" . a ; "Global Geodetic Network"; "4.112271540469974"; "6.3" . a ; "data"; "3.2142857142857144"; "9.9" . a ; "The NMT RMS files also contain information on the elevation angle dependence for the phase residuals."; "3.445149592021759"; "3.8" . a ; "Cwu rms calculation CRMS root mean square"; "2.664576802507837"; "3.4" . a ; "engineering"; "41.26573884859473"; "0.6167286038398743" . a ; "Non-Aligned Movement"; "https://www.wikidata.org/wiki/Q83201" . a ; "gage GPS Data analysis plan"; "1.8808777429467083"; "2.4" . a ; "NASA Global Geodetic Network"; "7.68025078369906"; "9.8" . a ; "velocity"; "4.503916449086162"; "6.9" . a ; "list"; "2.272727272727273"; "7.0" . a ; "velocity"; "3.6363636363636362"; "11.2" . a ; "system"; "2.3051948051948052"; "7.1" . a ; "discontinuity"; "3.524804177545692"; "5.4" . a ; "The GAGE GPS Analysis Centers process data from more than 2,000 GPS stations."; "34.2701722574796"; "37.8" . a ; "gauge"; "4.6103896103896105"; "14.2" . a ; "University"; "Education/School/Higher education/University" . a ; "root mean square"; "3.4595300261096606"; "5.3" . a ; "The final entries PBO and PBO are the earlier and PBO full solution generated in November and . is the number of common sites in the solutions."; "2.2665457842248413"; "2.5" . a ; "mathematics"; "16.44542772861357"; "22.3" . a ; "PBO GKNA CWU TSKF"; "1.8808777429467083"; "2.4" . a ; "aeronautics"; "15.692410630511509"; "0.23452769219875336" . a ; "file"; "2.9545454545454546"; "9.1" . a ; "process"; "3.279220779220779"; "10.1" . a ; "Organic chemical"; "Economy, business and finance/Economic sector/Chemicals/Organic chemical" . a ; "time series"; "4.765013054830288"; "7.3" . a ; "noise"; "3.4595300261096606"; "5.3" . a ; "UNAVCO"; "4.046997389033943"; "6.2" . a ; "PBO GKNA PBO GKI G"; "2.037617554858934"; "2.6" . a ; "Chur"; "https://www.wikidata.org/wiki/Q69007" . a ; "National Aeronautics and Space Administration"; "2.5974025974025974"; "8.0" . a ; "Space programme"; "Science and technology/Research/Scientific exploration/Space programme" . a ; "data from GPS station"; "8.620689655172413"; "11.0" . a ; "National Aeronautics and Space Administration"; "4.308093994778068"; "6.6" . a ; "Virginia"; "https://www.wikidata.org/wiki/Q1370" . a ; "geophysics"; "43.04185052089376"; "0.643273115158081" . a ; "coordinate file"; "2.7429467084639496"; "3.5" . a ; "statistics"; "10.103244837758112"; "13.7" . a ; "geosciences"; "43.04185052089376"; "0.643273115158081" . a ; "The process noise statistics are generated from the time series using the GAMIT/GLOBK script sh gen stats based on tsfit fits to the time series with the realistic sigma algorithm used to account for correlated noise."; "11.786038077969176"; "13.0" . a ; "reference frame"; "2.741514360313316"; "4.2" . a ; "service-account-enrichment" . a , , , ; "10.5072/ro-id.3RRRUMSLRG"; pav:importedBy ; "https://www.unavco.org/data/web-services/documentation/gps-position-documentation.html"; "false"; "http://sandbox.rohub.org/rodl/ROs/UNAVCO_GPS_Timeseries/"; "2017-09-04T12:48:59.459+02:00"; "http://everest.psnc.pl/users/jmgomez"; ; 1166176; "https://api.rohub.org/api/ros/911a1b7c-c3f8-4a5d-a692-080237dbcf8d/crate/download/"; "http://connect.unavco.org/display/org253530"; ; "2017-09-04 10:48:59.459000+00:00"; "2025-03-05 02:47:01.120606+00:00"; "2017-09-04 10:48:59.459000+00:00"; "The GAGE GPS Analysis Centers process data from more than 2,000 GPS stations. 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"6.8" . a ; "Discrimination"; "Society/Discrimination" . a ; "Computer crime"; "Crime, law and justice/Crime/Computer crime" . a ; "researcher"; "4.42211055276382"; "8.8" . a ; "computer science"; "40.26315789473684"; "15.3" . a ; "GPS"; "5.226130653266332"; "10.4" . a ; "GPS site velocity"; "5.811015664477009"; "11.5" . a ; """Workflow Title: SBAS InSAR data processing using SarScape"""; "7.98514391829155"; "17.2" . a ; """Workflow Title: Validation of ground velocities using InSAR ground deformation and GPS"""; "12.070566388115134"; "26.0" . a ; "input file"; "3.9184326269492207"; "9.8" . a ; "raster"; "2.814070351758794"; "5.6" . a ; "deformation"; "11.959798994974875"; "23.8" . a ; "Volcano deformation mapping."; "13.50974930362117"; "29.1" . a ; "statistics"; "2.279088364654138"; "5.7" . a ; "InSAR ground deformation"; "4.143506821627084"; "8.2" . a ; "user"; "2.9588164734106357"; "7.4" . a ; "deformation"; "9.636145541783288"; "24.1" . a ; "SBAS InSAR"; "2.71356783919598"; "5.4" . a ; "different volcano"; "1.010611419909045"; "2.0" . a ; "rule"; "2.279088364654138"; "5.7" . a ; """Input data Ground velocity file in raster format Ground velocity file(s) resulting from different analysis methods (e.g. PS, SBAS, mixed), different time periods, or different datasets (e.g. Sentinel-1, ALOS 2, GPS, optical levelling)"""; "9.192200557103064"; "19.8" . a ; "processing method"; "3.1328954017180393"; "6.2" . a ; "geophysics"; "100.0"; "0.8578767776489258" . a ; "Capital punishment"; "Crime, law and justice/Law enforcement/Punishment (criminal)/Capital punishment" . a ; "script"; "2.838864454218313"; "7.1" . a ; "digital elevation model"; "2.663316582914573"; "5.3" . a ; "velocity file"; "1.819100555836281"; "3.6" . a ; "researcher"; "3.358656537385046"; "8.4" . a ; "software"; "35.78947368421053"; "13.6" . a , ; "service-account-enrichment", "service-account-enrichment" . a , ; "service-account-generation-service", "service-account-generation-service" . a . a ; "memory" . a ; "deregulate in HD" . a ; "HD" . a ; "participate in epigenetic processes" . a ; "genetics" . a ; "research" . a ; "have an epigenetic role" . a ; "aim"; "3.7729318103149883"; "10.9" . a ; "gene deregulation"; "1.8138261464750172"; "5.3" . a ; "genes involved in HD gene deregulation have an epigenetic role"; "33.34444814938313"; "100.0" . a ; "participate in epigenetic process"; "0.20533880903490762"; "0.6" . a ; "web service"; "4.084458290065767"; "11.8" . a ; "have an epigenetic role"; "0.06844626967830253"; "0.2" . a ; "life sciences"; "100.0"; "2.662090003490448" . a ; "chromatin"; "5.430210325047801"; "14.2" . a ; "HD chromatin analysis"; "10.095824777549623"; "29.5" . a ; "http"; "3.530633437175493"; "10.2" . a ; "deregulation"; "11.586998087954111"; "30.3" . a ; "analysis"; "2.076843198338526"; "6.0" . a ; "http"; "4.053537284894838"; "10.6" . a ; "chromatin data interpretation"; "9.68514715947981"; "28.3" . a ; "HD gene deregulation"; "25.735797399041754"; "75.2" . a ; "deregulate in HD"; "16.1533196440794"; "47.2" . a ; "earth sciences"; "67.21141059758304"; "1.1682264804840088" . a ; "epigenetic role"; "6.536618754277893"; "19.1" . a ; "research object"; "5.6125941136208075"; "16.4" . a ; "Animal"; "Human interest/Animal" . a ; "geochemistry"; "32.78858940241696"; "0.5699106454849243" . a ; "Genoa"; "20.976116303219108"; "60.6" . a ; "epigenetic"; "2.942194530979578"; "8.5" . a ; "chromatin"; "4.7767393561786085"; "13.8" . a ; "workflow"; "3.6711281070745696"; "9.6" . a ; "chromatin data interpretation."; "4.268089363121041"; "12.8" . a ; "geology"; "67.21141059758304"; "1.1682264804840088" . a ; "role"; "5.469020422291451"; "15.8" . a ; "information"; "2.872966424368294"; "8.3" . a ; "system"; "3.703703703703704"; "10.7" . a ; "web service"; "4.7036328871892925"; "12.3" . a ; "earth sciences"; "32.78858940241696"; "0.5699106454849243" . a ; "research"; "4.091778202676864"; "10.7" . a ; "research"; "4.534440983039114"; "13.1" . a ; "HD"; "12.313575525812622"; "32.2" . a ; "role"; "5.621414913957935"; "14.7" . a ; "chromatin analysis"; "1.0609171800136894"; "3.1" . a ; "object"; "4.130019120458891"; "10.8" . a ; "workflow"; "3.0806507442021465"; "8.9" . a ; "interpretation"; "2.492211838006231"; "7.2" . a ; "Science and technology"; "Science and technology" . a ; "life sciences (general)"; "100.0"; "2.662090003490448" . a ; "epigenetic process"; "17.796030116358658"; "52.0" . a ; "anni web services"; "5.236139630390144"; "15.3" . a ; "HD"; "12.253374870197302"; "35.4" . a ; "Genes deregulated in HD, are participating in epigenetic processes"; "33.34444814938313"; "100.0" . a ; "Genoa"; "26.080305927342256"; "68.2" . a ; "gene"; "14.952198852772467"; "39.1" . a ; "deregulation"; "10.107303565247491"; "29.2" . a ; "

This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

"; "29.043014338112705"; "87.1" . a ; "data"; "3.365200764818356"; "8.8" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; "gene"; "13.326410522672205"; "38.5" . a , , ; pav:importedBy ; ; "2014-02-26T14:16:20.355+01:00"; ; ; 81201; "https://api.rohub.org/api/ros/f84d00ef-47b2-40b3-af26-099ed7e82f5b/crate/download/"; ; "2014-02-21 13:36:32.163000+00:00"; "2025-10-18 11:54:49.104646+00:00"; "2014-02-21 13:36:32.163000+00:00"; "

This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/f84d00ef-47b2-40b3-af26-099ed7e82f5b"; ; "chromatin data interpretation"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Eleni Mina. \"chromatin data interpretation.\" ROHub. Feb 21 ,2014. https://w3id.org/ro-id/f84d00ef-47b2-40b3-af26-099ed7e82f5b." . a , ; , , , , ; "data_interpretation" . a , , ; ; 30787; "https://api.rohub.org/api/resources/2ea2f7b6-1c15-454f-b62a-e7656bb81db4/download/"; ; "2014-02-25 16:10:46.463000+00:00"; "2022-03-25 16:50:57.659485+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "List Predefined Concept Sets"; "2014-02-25 16:10:46.463000+00:00" . a , , ; ; 69369; "https://api.rohub.org/api/resources/473e57ab-4056-427a-a8d9-b2c62e9b34d4/download/"; ; "2014-02-26 13:14:06.663000+00:00"; "2022-03-25 16:51:01.271983+00:00"; """This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group). This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/282 for functional gene and SNP annotation and knowledge discovery."""; ; "Explain concept scores"; "2014-02-26 13:14:06.663000+00:00" . a , , ; ; 63; "https://api.rohub.org/api/resources/5b168f58-186e-4335-8079-2c917c3173e3/download/"; ; "2014-02-25 16:03:44.993000+00:00"; "2022-03-25 16:50:58.525827+00:00"; "text/plain"; ; "hypothesis.txt"; "2014-02-25 16:03:44.993000+00:00" . a , , ; ; 203555; "https://api.rohub.org/api/resources/7f5b48a1-083d-4891-b311-b4627ceaa7ab/download/"; ; "2014-02-25 16:06:54.756000+00:00"; "2022-03-25 16:51:00.400167+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-25 16:06:54.756000+00:00" . a , , ; ; 188023; "https://api.rohub.org/api/resources/840546e9-eecd-455e-b3f7-b1893b29e083/download/"; ; "2014-02-25 16:12:14.228000+00:00"; "2022-03-25 16:50:56.779303+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2014-02-25 16:12:14.228000+00:00" . a , , ; ; 39476; "https://api.rohub.org/api/resources/cb796e52-689f-4e9e-8842-09612588af02/download/"; ; "2014-02-25 16:04:13.823000+00:00"; "2022-03-25 16:50:55.921582+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2014-02-25 16:04:13.823000+00:00" . a , , ; ; 41692; "https://api.rohub.org/api/resources/ccd9b022-3e2d-422b-a5c5-1e12af73b5c7/download/"; ; "2014-02-25 16:09:23.429000+00:00"; "2022-03-25 16:50:59.349734+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2014-02-25 16:09:23.429000+00:00" . a , , ; ; 67; "https://api.rohub.org/api/resources/f97e8e56-b0de-4fda-9e37-352412aa2d3c/download/"; ; "2014-02-25 16:03:12.283000+00:00"; "2022-03-25 16:50:54.643219+00:00"; "text/plain"; ; "conclusions.txt"; "2014-02-25 16:03:12.283000+00:00" . a ; dct:conformsTo ; . a ; "Eleni Mina" . a ; "Eleni Mina" . a ; ""; "Earth sciences" . a ; "environmental monitoring"; "11.420612813370472"; "8.2" . a ; "environmental monitoring from space"; "11.598746081504702"; "11.1" . a ; "service-account-enrichment" . a , , ; "False"; "https://w3id.org/ro-id/d0694eaf-a561-4c9f-9a70-17c296da2140"; "2022-03-29 07:03:12.340483+00:00"; "https://orcid.org/0000-0002-2736-0052"; ; ; 533964; "https://api.rohub.org/api/ros/15e9432f-53ee-4ea8-b1a3-6fdcaca7cf9e/crate/download/"; ; "2021-12-14 10:41:17.716553+00:00"; "2024-03-05 12:16:56.530781+00:00"; "2021-12-14 10:41:17.716553+00:00"; "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/15e9432f-53ee-4ea8-b1a3-6fdcaca7cf9e"; ; "Analysis from satellite data – Environmental monitoring from space - snapshot", "Analysis from satellite data – Environmental monitoring from space"; "MANUAL"; "https://w3id.org/ro-id/81696625-5dc7-413b-a2c5-0815dee8dc2a"; "https://w3id.org/ro-id/08e10088-5d06-4d9a-a7a0-7a6bf4a0d199", "https://w3id.org/ro-id/4266cc91-2256-44f6-b790-90445838a46e", "https://w3id.org/ro-id/5549dbaf-583c-4c8c-8dfa-a39ad54b848e", "https://w3id.org/ro-id/6c915ada-20b3-43cf-a69c-8773c78a0eaa", "https://w3id.org/ro-id/6f7e5fac-e969-4048-9f37-c6b31a3c612e", "https://w3id.org/ro-id/70d4f966-c4d0-48f5-9fa5-811f884e7b1e", "https://w3id.org/ro-id/97bb139d-ef31-4724-96c5-ea9425fc7c37", "https://w3id.org/ro-id/d2a7c5cc-1102-43cd-8f62-288373b07b06", "https://w3id.org/ro-id/f3594549-487e-496f-9517-0860ce40f088"; "https://w3id.org/ro-id/74dd5244-227a-4a04-b482-735a591fd8c1", "https://w3id.org/ro-id/b72312be-71d7-47a7-b84c-4bfe2e2e23dd"; "https://w3id.org/ro-id/7b96142d-d1dc-4dd2-9f96-5dd9fb851416"; "https://w3id.org/ro-id/32c4e511-07a6-4aed-8e1e-484785703c49", "https://w3id.org/ro-id/3ee3f89c-1f32-41b6-a676-baa8abd9d56f", "https://w3id.org/ro-id/63bbaf66-12ba-4747-88a4-b84d914c3b7e", "https://w3id.org/ro-id/ac96b0ba-720f-47cb-a2fe-a19e3e7e7713", "https://w3id.org/ro-id/c922ffbe-2d7f-4489-aaa7-b1aae735efc5", "https://w3id.org/ro-id/cf67ee27-302a-48bc-a5ee-904c4e50fa3e", "https://w3id.org/ro-id/d6fe7e21-0924-4201-b407-8df494f726ed"; "https://w3id.org/ro-id/5b45c2e1-bd6d-494f-8f0b-71842e9ff0c6", "https://w3id.org/ro-id/aa125d6d-2a3d-4e86-a386-fca35f89cfff"; "https://w3id.org/ro-id/14db60f4-ba75-4054-8b25-9588535e5441", "https://w3id.org/ro-id/3a19afd2-96fe-46f3-a8ff-a00267cec7a9", "https://w3id.org/ro-id/3bea0d90-d8aa-4e43-9a10-49f192c86cf9", "https://w3id.org/ro-id/99a7f0a1-d957-45a2-b2db-21a5a4d52bee", "https://w3id.org/ro-id/ecb76892-a19f-4944-bdbc-7859c36c5de9"; "https://w3id.org/ro-id/6b907ad3-41f5-4c92-a60a-fa30c01895d6", "https://w3id.org/ro-id/d95b93a0-106a-483a-af39-2d4e03335ad7", "https://w3id.org/ro-id/f5db11a5-bf5a-4f0e-8924-4cef9408845f"; "Castellan, Giorgio. \"Analysis from satellite data – Environmental monitoring from space.\" ROHub. Dec 14 ,2021. https://doi.org/10.5281/zenodo.6392772." . a , ; "Discover, subset, download and visualize satellite data stored in a Data Cube from the ADAM Platform"; ; "Method" . a , ; "Results"; , ; "Results" . a , ; "Satellite data on Chl-a and Kd490"; ; "Satellite_data" . a , , ; ; 70005; "https://api.rohub.org/api/resources/190680da-e8f0-45d9-91e0-504523674f2a/download/"; ; "2021-12-14 14:33:06.849172+00:00"; "2022-03-29 07:03:09.363944+00:00"; "image/png"; ; "Diffuse attenuation coefficient at 490 nm (Kd490) in 2018 in the north Adriatic Sea"; "2021-12-14 14:33:06.849172+00:00" . a , , ; ; 449579; "https://api.rohub.org/api/resources/34811ef9-67ba-4917-a0f5-a601d5d4f582/download/"; ; "2021-12-14 14:38:21.837867+00:00"; "2022-03-29 07:03:07.276437+00:00"; "image/jpeg"; ; "Analysis from satellite data – Environmental monitoring from space during COVID-19 lockdown"; "2021-12-14 14:38:21.837867+00:00" . a , , ; ; "https://w3id.org/ro-id/894d3a33-8340-497d-beaf-5b9d85c9bfc7"; ; "2021-12-14 10:44:17.433059+00:00"; "2022-03-29 07:03:12.216426+00:00"; "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown"; ; "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown"; "2021-12-14 10:44:17.433059+00:00" . a , , ; ; "https://w3id.org/ro-id/34d648b3-0014-4a19-8469-40b9380ca4c3"; ; "2021-12-14 10:44:48.894463+00:00"; "2022-03-29 07:03:08.528464+00:00"; "Discover and subset satellite data from the ADAM Platform"; ; "Discover and subset satellite data from the ADAM Platform"; "2021-12-14 10:44:48.894463+00:00" . a , , ; ; 68452; "https://api.rohub.org/api/resources/d1404599-300c-4572-971f-90a3a6a5e72a/download/"; ; "2021-12-14 14:32:01.240770+00:00"; "2022-03-29 07:03:10.497073+00:00"; "image/png"; ; "Diffuse attenuation coefficient at 490 nm (Kd490) in 2018 in the north Adriatic Sea"; "2021-12-14 14:32:01.240770+00:00" . a ; dct:conformsTo ; . a ; "environmental monitoring"; "11.413748378728926"; "8.8" . a ; "effects of COVID-19 lockdown"; "15.256008359456635"; "14.6" . a ; "water clarity"; "30.407523510971785"; "29.1" . a ; "collection"; "11.932555123216602"; "9.2" . a ; "analysis"; "14.902506963788301"; "10.7" . a ; "water"; "11.142061281337048"; "8.0" . a ; "geosciences"; "100.0"; "0.4130299687385559" . a ; "analysis"; "13.618677042801558"; "10.5" . a ; "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea"; "69.26926926926926"; "69.2" . a ; "collection"; "13.091922005571032"; "9.4" . a ; "space"; "5.153203342618385"; "3.7" . a ; "Adriatic Sea"; "11.142061281337048"; "8.0" . a ; "earth sciences"; "100.0"; "0.8256934881210327" . a ; "Satellite technology"; "Economy, business and finance/Economic sector/Computing and information technology/Satellite technology" . a ; "Adriatic Sea"; "https://www.wikidata.org/wiki/Q13924" . a ; "clarity"; "12.95264623955432"; "9.3" . a ; "analysis from satellite data"; "17.03239289446186"; "16.3" . a ; "geophysics"; "100.0"; "0.4130299687385559" . a ; "satellite data"; "23.47600518806745"; "18.1" . a ; "geology"; "100.0"; "0.8256934881210327" . a ; "clarity"; "12.5810635538262"; "9.7" . a ; "lockdown"; "14.785992217898833"; "11.4" . a . a ; "result"; "4.735376044568246"; "3.4" . a ; "covid 19"; "12.191958495460442"; "9.4" . a ; "Analysis from satellite data –"; "22.02202202202202"; "22.0" . a ; "analysis of satellite data"; "25.705329153605014"; "24.6" . a ; "lockdown"; "15.459610027855154"; "11.1" . a ; "Environmental monitoring from space."; "8.708708708708707"; "8.7" . a , ; "", ""; "Applied sciences", "Applied sciences" . a , ; "", ""; "Climatology", "Climatology" . a ; "10.13039/501100000781"; "European Commission" . a , , ; ; "https://doi.org/10.5281/zenodo.4543739"; ; "2022-03-28 14:18:39.324751+00:00"; "2022-03-29 18:08:07.800368+00:00"; """By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool, we are aiming at bridging the gap between climate scientists and non-climate specialists. Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational research. One of the strength of Galaxy is that it does not require programming experience and allow researchers to easily upload data, run complex tools and workflows in a reproducible manner, and visualize results. Galaxy Climate is quite new and aims at offering tools to everyone interested in Climate Science so that they can analyse and visualize climate data produced by climate scientists. However, climate scientists and in particular climate modellers have very different working practices: they often like to use command lines for running climate models and thanks to the PANGEO community (a community platform for Big Data geoscience) the Jupyter ecosystem has become very popular with several deployments of JupyterHubs dedicated to climate data analysis. By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool (https://live.usegalaxy.eu/?tool_id=interactive_tool_climate_notebook), we are aiming at bridging the gap between climate scientists and non-climate specialists. On this poster, we will show typical use cases both for research (https://nordicesmhub.github.io/eosc-nordic-climate-demonstrator/02-use-cases/) and for teaching (https://nordicesmhub.github.io/NEGI-Abisko-2019/intro)."""; ; "Climate JupyterLab as an interactive tool in Galaxy"; "2022-03-28 14:18:39.324751+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.6394185"; ; "2022-03-29 17:55:05.034625+00:00"; "2022-03-29 18:08:05.535928+00:00"; """This is a tarball for the Docker climate-JupyterLab image - Version 2021-03-18. To use it: download the image file docker-climate-notebook-2021-03-18.tar load it with docker with the command: docker load --input docker-climate-notebook-2021-03-18.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-climate-notebook for more details"""; ; "Docker climate-JupyterLab image Version 2021-03-18"; "2022-03-29 17:55:05.034625+00:00" . a , , ; ; "https://github.com/NordicESMhub/docker-climate-notebook"; ; "2022-03-29 12:01:31.834492+00:00"; "2022-03-29 18:08:06.488065+00:00"; "This github repository contains all the sources required for building the docker containers that are made available in Quay Container Registry."; ; "Source code for building the docker container (github repository)"; "2022-03-29 12:01:31.834492+00:00" . a , , ; ; "https://jupyterlab.readthedocs.io/en/stable/"; ; "2022-03-28 14:14:45.648769+00:00"; "2022-03-29 18:08:02.576584+00:00"; "Link to the online JupyterLab documentation."; ; "JupyterLab Documentation"; "2022-03-28 14:14:45.648769+00:00" . a ; "University of Freiburg, Freiburg (Germany)"; "bjoern.gruening@gmail.com"; "Björn Grüning"; "0000-0002-3079-6586" . a , , ; ; "https://quay.io/repository/nordicesmhub/docker-climate-notebook"; ; "2022-03-29 11:58:28.213223+00:00"; "2022-03-29 18:08:06.281346+00:00"; """These docker images (different tags) correspond to the docker images built for Galaxy Climate JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-climate-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18"""; ; "Docker images for Galaxy Climate JupyterLab (Quay Container Registry)"; "2022-03-29 11:58:28.213223+00:00" . a , , ; ; "https://raw.githubusercontent.com/NordicESMhub/docker-climate-notebook/ie2/climate-jupyter-galaxy_web.gif"; ; "2022-03-29 11:41:30.552728+00:00"; "2022-03-29 18:08:02.662870+00:00"; "This is a gif animated image showing how to start the Galaxy Climate JupyterLab in Galaxy Europe"; "image/gif"; ; "How to start Galaxy Climate JupyterLab (gif animated)"; "2022-03-29 11:41:30.552728+00:00" . a , , ; ; "https://raw.githubusercontent.com/NordicESMhub/docker-climate-notebook/ie2/map_vis_Galaxy.gif"; ; "2022-03-29 11:43:11.075459+00:00"; "2022-03-29 18:08:03.597880+00:00"; "This is a gif animated image showing some of the functionalities of the Galaxy Climate JupyterLab"; "image/gif"; ; "Demo of some of the functionalities of the Galaxy Climate JupyterLab (gif animated)"; "2022-03-29 11:43:11.075459+00:00" . a , ; "01xtthb56"; "University of Oslo" . a , , , ; "04jcwf484", "04jcwf484"; "Nordic e-Infrastructure Collaboration", "Nordic e-Infrastructure Collaboration" . a ; ; "857652"; "EOSC-Nordic"; "EOSC-Nordic" . a ; ; "01840e60-5480-4d82-a6e0-ba8713e1ccc8"; "POINT (7.8337097307667145 48.01044395569975)" . a ; "10.766601562500002"; "59.921531172441085"; "POINT (10.766601562500002 59.921531172441085)" . a ; "7.8337097307667145"; "48.01044395569975"; "POINT (7.8337097307667145 48.01044395569975)" . a ; ; "900c168d-9825-4521-a718-87b8ac6bf711"; "POINT (10.766601562500002 59.921531172441085)" . a , , , , ; "False"; ; "2022-03-29 18:08:11.857053+00:00"; ; , ; ; , ; 30283; "https://api.rohub.org/api/ros/cb869c7a-7a89-49dd-9038-b8a05a91dc6e/crate/download/"; ; ; ; "2022-03-26 09:45:54.364171+00:00"; "2025-10-18 11:54:14.993216+00:00"; "2022-03-26 09:45:54.364171+00:00"; "🐳 🔬 📚 Jupyter running in a docker container. This image can be used to integrate Jupyter into Galaxy. This Jupyter Docker container is used by the Galaxy Project and can be installed from the quay.io index (https://quay.io/repository/nordicesmhub/docker-climate-notebook)."; "application/ld+json"; ; ; , , , ; "https://w3id.org/ro-id/cb869c7a-7a89-49dd-9038-b8a05a91dc6e"; "cesm", "climate", "docker", "esmvaltool", "jupyterlab", "pangeo"; ; "Docker Climate Analysis Jupyter Container - snapshot", "Docker Climate Analysis Jupyter Container Version 2021-03-18"; , ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Anne Foilloux, and Björn Grüning. \"Docker Climate Analysis Jupyter Container Version 2021-03-18.\" ROHub. 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It builds on previous efforts within NICEST (a 3-year NeIC project as of 2017-01) and NordicESM (3-year NordForsk funded project from 2014-12). NICEST2 activities include: 1) Enhance the performance and optimize and homogenize workflows used, so climate models (like EC-EARTH and NorESM) can be run in an efficient way on future computing resources (like EuroHPC); 2) Widen the usage and expertise on evaluating Earth System Models and develop new diagnostic modules for the Nordic region within the ESMValTool; 3)Create a roadmap for FAIRification of Nordic climate model data."""; "application/ld+json"; ; ; , , , , ; "https://w3id.org/ro-id/ed4e6aa2-9db8-452d-9301-ba1606361034"; "EC-EARTH", "HPC", "NorESM", "Nordic", "climate", "earth system modelling", "esm"; ; "NeIC NICEST2 Project - snapshot", "NeIC NICEST2 Project"; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; , , , ; "Anne Foilloux, Hamish Struthers, Risto Makkonen, Oskar Landgren, Antti-Ilari Partanen, Elina Miinalainen, Jean Iaquinta, et al. \"NeIC NICEST2 Project.\" ROHub. Apr 01 ,2022. https://doi.org/10.24424/chnf-4g76." . a , ; "POINT (5.328369140625001 60.413852350464936)" . a , ; "POINT (24.672546386718754 60.203663175350826)" . a , ; "POINT (16.18921279907227 58.59026697919618)" . a , ; "POINT (10.72265625 59.94400716933027)" . a , ; "POINT (12.555999755859377 55.67835873246176)" . a , , ; ; 438353; "https://api.rohub.org/api/resources/4ed7f241-959a-41e5-bfb8-a4d53d3d1fa6/download/"; ; "2022-04-01 14:26:58.230734+00:00"; "2022-04-01 15:20:39.864804+00:00"; "Initial Collaboration agreement for the NICEST2 project"; "application/pdf"; ; "NICEST2 Collaboration Agreement"; "2022-04-01 14:26:58.230734+00:00" . a , , ; ; 1182910; "https://api.rohub.org/api/resources/9ea437fd-1af0-4a1d-bc68-7af1c3bed34a/download/"; ; "2022-04-01 15:18:04.647336+00:00"; "2022-04-01 15:20:30.258581+00:00"; "Achievements of the NeIC NICEST2 project at the beginning of January 2022. This slide is part of a presentation that has been shown during the NeIC AHM22."; "image/png"; ; "NICEST2 project outcomes (24th January 2022)"; "2022-04-01 15:18:04.647336+00:00" . a , , ; ; 191598; "https://api.rohub.org/api/resources/a51d3ea3-89a6-443b-8d22-06f4c3ec71ee/download/"; ; "2022-04-01 14:27:49.687557+00:00"; "2022-04-01 15:21:09.531085+00:00"; "Business Case for the NICEST2 project."; "application/pdf"; ; "NICEST2 Business Case"; "2022-04-01 14:27:49.687557+00:00" . a , , ; ; 610336; "https://api.rohub.org/api/resources/cc821096-f0f1-4a81-afd2-e311c899250c/download/"; ; "2022-04-01 14:25:00.118897+00:00"; "2022-04-01 15:20:37.652753+00:00"; "The submitted project proposal for the NICEST2 project."; "application/pdf"; ; "NICEST2 Project proposal (submitted)"; "2022-04-01 14:25:00.118897+00:00" . a , , ; ; 667263; "https://api.rohub.org/api/resources/fd0ced6b-bfec-49bd-99b8-cb2db9f5c3f9/download/"; ; "2022-04-01 14:22:43.959817+00:00"; "2022-04-01 15:20:32.410941+00:00"; "NICEST2 project plan. Please note that some changes may have been agreed during the course of the project."; "application/pdf"; ; "Project Plan (as agreed initially)"; "2022-04-01 14:22:43.959817+00:00" . a ; dct:conformsTo ; . a ; "Earth System Modeling Tools"; "2.7037933817594832"; "6.7" . a ; "Greenland"; . a ; "Budgets and budgeting"; "Economy, business and finance/Economy/Macro economics/Budgets and budgeting" . a ; "project manager"; "2.4616626311541565"; "6.1" . a ; "Weather"; "Weather" . a ; "obligation"; "2.58272800645682"; "6.4" . a ; "data"; "4.3205317577548"; "23.4" . a ; "European Community"; "3.1476997578692494"; "7.8" . a ; "Weather"; "Weather" . a ; "Earth system model"; "11.910029498525073"; "32.3" . a ; "Project outcome"; "1.9174041297935105"; "5.2" . a ; "Rivers"; "Environment/Natural resources/Water/Rivers" . a ; "physical geography and environmental geoscience"; "19.57903756400082"; "0.9382504224777222" . a ; "diagnostic"; "2.806499261447563"; "15.2" . a ; "NICEST-2"; "3.510895883777239"; 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EC EARTH and NorESM can scale on new architectures (performance analysis numbers compared to initially on HPC national providers and LUMI when available). Number of users running EC EARTH and NorESM on their own national facilities."; "2.391171060698958"; "3.9" . a ; "Norway"; "2.94592413236481"; "7.3" . a ; "Po River"; . a ; "Nordic"; "2.9862792574656982"; "7.4" . a ; "Coupled Model Intercomparison Project"; "2.7441485068603715"; "6.800000000000001" . a ; "Nordic"; "2.5480059084194977"; "13.8" . a ; "earth sciences"; "40.744573414005764"; "1.9525277018547058" . a ; "NeIC NICEST2 Project"; "2.8652138821630344"; "7.1" . a ; "climate model"; "5.059084194977843"; "27.400000000000002" . a ; "Esgf system"; "1.9542772861356934"; "5.3" . a ; "climate model data"; "4.793510324483776"; "13.0" . a ; "agreement"; "3.452732644017725"; "18.7" . a ; """If not defined otherwise in the project description the project owner does not require the right to conclude a contract on behalf of the other partners through this collaboration agreement."""; "2.023298589822195"; "3.3" . a ; "Commercial contract"; "Economy, business and finance/Business information/Strategy and marketing/Commercial contract" . a ; "European Community"; "4.062038404726735"; "22.0" . a ; "NICEST2 activities include: 1) Enhance the performance and optimize and homogenize workflows used, so climate models (like EC-EARTH and NorESM) can be run in an efficient way on future computing resources (like EuroHPC); 2) Widen the usage and expertise on evaluating Earth System Models and develop new diagnostic modules for the Nordic region within the ESMValTool; 3)Create a roadmap for FAIRification of Nordic climate model data."; "12.875536480686696"; "21.0" . a ; "NORCE (Norway)"; "algu@norceresearch.no"; "Alok Kumar Gupta" . a ; "Nordic e-Infrastructure Collaboration (NeIC)"; "annefou@geo.uio.no"; "Anne Fouilloux"; "0000-0002-1784-2920" . a ; "CSC (Finland)"; "elina.miinalainen@csc.fi"; "Elina Miinalainen" . a ; "USIT, University of Oslo (Norway)"; "j.h.nordmoen@usit.uio.no"; "Jørgen Halvorsen Nordmoen" . a ; "CSC (Finland)"; "kimmo.ervasti@csc.fi"; "Kimmo Ervasti" . a ; "USIT, University of Oslo (Norway)"; "maikenp@usit.uio.no"; "Maiken Pedersen" . a ; "Norwegian Meteorological Institute (Norway)"; "oyvind.seland@met.no"; "Øyvind Seland" . a ; "NSC (Sweden)"; "pchengi@nsc.liu.se"; "Prashanth Dwarakanath" . a , ; "service-account-enrichment", "service-account-enrichment" . a ; "NORCE (Norway)"; "tylo@norceresearch.no"; "Tyge Løvseth" . a ; ""; "Applied sciences" . a , ; "", ""; "Earth sciences", "Earth sciences" . a ; ""; "Earth observation" . a ; "10.13039/501100000781"; "European Commission" . a , , ; "10.24424/DXFH-X940"; ; "https://doi.org/10.24424/dxfh-x940"; ; "2022-04-07 19:22:56.289678+00:00"; "2022-04-10 17:18:00.927096+00:00"; "Application of VSM to the M7.1 Van Earthquake (Turkey) of 2011"; ; "M 7.1 Van Earthquake (Turkey) 2011"; "2022-04-07 19:22:56.289678+00:00" . a , , ; "10.24424/WESR-P505"; ; "https://doi.org/10.24424/wesr-p505"; ; "2022-04-07 13:26:39.214963+00:00"; "2022-04-10 17:18:32.214160+00:00"; "Data modelling related to the 2021 eruption at Nyiragongo volcano (DR Congo) using VSM"; ; "Nyiragongo volcano (DR Congo) 22 May 2021 eruption"; "2022-04-07 13:26:39.214963+00:00" . a , , ; ; "https://github.com/EliTras/VSM"; ; "2022-04-07 13:56:11.176692+00:00"; "2022-04-10 17:18:11.929153+00:00"; "Link to the GitHub repository with the VSM code"; ; "VSM code in GitHub"; "2022-04-07 13:56:11.176692+00:00" . a , , ; ; "https://github.com/EliTras/VSM_test"; ; "2022-04-07 13:59:08.278250+00:00"; "2022-04-10 17:18:01.227419+00:00"; "Tests of VSM in GitHub using InSAR and GNSS data at Campi Flegrei caldera (Italy)"; ; "VSM tests in GitHub using InSAR and GNSS data at Campi Flegrei caldera (Italy)"; "2022-04-07 13:59:08.278250+00:00" . a , ; , ; "101017502", "101017502"; "Reliance", "RELIANCE"; "RESEARCH LIFECYCLE MANAGEMENT FOR EARTH SCIENCE COMMUNITIES AND COPERNICUS USERS", "Research Lifecycle Management for Earth Science Communities and Copernicus Users" . a , , ; ; "https://w3id.org/ro-id/a25c47c7-f4dd-44d2-be2c-ab74b6a99070"; ; "2022-04-07 14:32:55.665484+00:00"; "2022-04-10 17:18:06.415001+00:00"; "Modelling of the 2011-2012 unrest at Santorini (Greece)."; ; "Santorini (Greece) 2011-2012 unrest"; "2022-04-07 14:32:55.665484+00:00" . a . a , , , , ; "False"; ; "2022-04-10 17:18:34.475111+00:00"; ; , , ; ; 503834; "https://api.rohub.org/api/ros/e97e6ada-276b-4406-b2ee-d3ec36e096c3/crate/download/"; ; "2022-04-07 13:12:37.521036+00:00"; "2025-10-18 11:49:47.795813+00:00"; "2022-04-07 13:12:37.521036+00:00"; """Volcanic and Seismic source Modelling (VSM) is an open source Python tool to model ground deformation detected by satellite and terrestrial geodetic techniques. The VSM tool allows the user to choose one or more geometrical sources as forward model among sphere, spheroid, ellipsoid, fault, and sill. It supports multiple datasets from most satellite and terrestrial geodetic techniques: interferometric SAR, GNSS, levelling, Electro-optical Distance Measuring, tiltmeters and strainmeters. Two sampling algorithms are available, one is a global optimization algorithm based on the Voronoi cells and the second follows a probabilistic approach to parameters estimation based on the Bayes theorem. VSM can be executed as Python script, in Jupyter Notebook environments or by its Graphical User Interface. Version 1.0 April 2022. For any inquires, please write to elisa.trasatti@ingv.it"""; "application/ld+json"; ; ; , , ; "https://w3id.org/ro-id/e97e6ada-276b-4406-b2ee-d3ec36e096c3"; "SAR data", "deformation modelling", "geodetic data inversion", "open science", "seismic cycle", "volcanic activity"; ; "Volcanic and Seismic source Modelling (VSM). The Python toolkit for modelling geodetic data - snapshot", "Volcanic and Seismic source Modelling (VSM). The Python toolkit for modelling geodetic data"; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Trasatti, Elisa. \"Volcanic and Seismic source Modelling (VSM). The Python toolkit for modelling geodetic data.\" ROHub. Apr 07 ,2022. https://doi.org/10.24424/t83f-5t97." . a , ; , ; "Figures" . a , ; , , , , ; "Examples" . a , ; , ; "VSM_src" . a , , ; ; 9282; "https://api.rohub.org/api/resources/42037fe1-50cc-4751-9e39-4ee003202c34/download/"; ; "2022-04-07 13:23:18.481402+00:00"; "2022-04-10 17:18:08.362148+00:00"; "image/gif"; ; "VSM logo"; "2022-04-07 13:23:18.481402+00:00" . a dct:BibliographicResource, , ; ; 3243; "https://api.rohub.org/api/resources/d159c0a2-bb4c-4e9b-b558-4f8334993357/download/"; ; "2022-04-07 14:03:09.752317+00:00"; "2022-04-10 17:18:33.705787+00:00"; "License of use of VSM"; ; "License of use of VSM"; "2022-04-07 14:03:09.752317+00:00" . a , , ; ; 492577; "https://api.rohub.org/api/resources/d480c9fe-ccdd-492a-a0c4-609fe30bd217/download/"; ; "2022-04-07 13:15:18.286359+00:00"; "2022-04-10 17:18:09.966348+00:00"; "image/png"; ; "figure2.png"; "2022-04-07 13:15:18.286359+00:00" . a ; dct:conformsTo ; . a ; "sampling"; "6.392045454545455"; "4.5" . a ; "computer operations and hardware"; "100.0"; "0.5582033395767212" . a ; "Software"; "Economy, business and finance/Economic sector/Computing and information technology/Software" . a ; "Language"; "Arts, culture and entertainment/Culture/Language" . a ; "algorithm"; "13.443830570902394"; "7.3" . a ; "VSM tool"; "28.545119705340703"; "15.5" . a ; "deformation"; "9.208103130755065"; "5.0" . a ; "earth sciences"; "100.0"; "0.76500004529953" . a ; "software"; "27.699530516431924"; "5.9" . a ; "computer programming"; "38.49765258215962"; "8.2" . a ; "algorithm"; "12.357954545454545"; "8.7" . a ; "Volcanic and Seismic source Modelling (VSM) is an open source Python tool to model ground deformation detected by satellite and terrestrial geodetic techniques."; "59.339080459770116"; "41.3" . a ; "Python toolkit"; "20.626151012891345"; "11.2" . a ; "environment"; "6.818181818181819"; "4.8" . a ; "VSM"; "22.467771639042358"; "12.2" . a ; "geophysics"; "100.0"; "0.76500004529953" . a ; "geology"; "16.901408450704224"; "3.6" . a ; "source Modelling"; "14.917127071823206"; "8.1" . a ; "open source Python tool"; "21.17863720073665"; "11.5" . a ; "Volcanic and Seismic source Modelling (VSM). 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SPL data were calculated from wav data recorded by Develogic SonoVault Hydrophones (https://w3id.org/ro-id/6640422d-57ed-4814-b0d0-8eb4ee85f501)."; "application/ld+json"; , , , , ; "https://w3id.org/ro-id/7b86ece5-b588-416b-9c98-30bb63a5b9bc"; "Underwater Noise, SPLs, Soundscape"; ; "Sound Pressure Levels Post Processing within the Soundscape project - snapshot", "Sound Pressure Levels Post Processing within the Soundscape project"; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Petrizzo, Antonio, Fantina Madricardo, Marta Picciulin, and Michol Ghezzo. \"Sound Pressure Levels Post Processing within the Soundscape project.\" ROHub. Dec 13 ,2021. https://doi.org/10.24424/tkqc-zr42." . a , ; "data input"; , ; "input" . a , ; "Jupyter notebooks here"; , ; "notebook" . a , ; "Here some information"; , , ; "metadata" . a , ; "Here some results"; ; "results" . a , , ; ; 5833087; "https://api.rohub.org/api/resources/63076219-d95a-4ffa-be04-e8c9ead051b7/download/"; ; "2022-07-06 10:25:59.163869+00:00"; "2022-07-06 15:27:12.295310+00:00"; "Jupyter notebook for processing SPL data."; "application/zip"; ; "Jupyter notebook for processing SPL data."; "2022-07-06 10:25:59.163869+00:00" . a , , ; ; 1095417; "https://api.rohub.org/api/resources/7cdcd447-39c2-4d6c-8982-4e3b30a4e216/download/"; ; "2022-07-06 15:07:05.061088+00:00"; "2022-07-06 15:27:00.351667+00:00"; "image/png"; ; "workflowPostProcessing.png"; "2022-07-06 15:07:05.061088+00:00" . a , , ; ; 4863608; "https://api.rohub.org/api/resources/912d02f1-4c08-46ce-8d75-ea2f16520385/download/"; ; "2022-07-05 12:05:48.435779+00:00"; "2022-07-06 15:27:14.989305+00:00"; "Example of SPL input file. HDF5 format, according to to ICES (International Council for the Exploration of the Sea) continuous noise data portal specification (https://www.ices.dk/data/data-portals/Pages/Continuous-Noise.aspx)."; ; "Example of SPL input file"; "2022-07-05 12:05:48.435779+00:00" . a , , ; ; 1628249; "https://api.rohub.org/api/resources/a124318c-b696-4515-a1a1-6b37818b6db0/download/"; ; "2022-07-05 12:44:30.318843+00:00"; "2022-07-06 15:27:04.720891+00:00"; "Map of stations with their coordinates"; "image/png"; ; "Stations map"; "2022-07-05 12:44:30.318843+00:00" . a , , ; ; 3034992; "https://api.rohub.org/api/resources/b0fadc73-e542-4e0e-be88-473cd883bbf9/download/"; ; "2022-07-05 12:33:28.328984+00:00"; "2022-07-06 15:27:09.185481+00:00"; "Some examples of output files"; "application/zip"; ; "Some examples of output files"; "2022-07-05 12:33:28.328984+00:00" . a ; dct:conformsTo ; . a ; "http"; "8.760330578512397"; "5.3" . a ; "data"; "20.729684908789388"; "12.5" . a ; "information"; "11.074380165289256"; 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"https://w3id.org/ro-id/1dce6c51-6e53-4110-8f85-7ab5b694f80d", "https://w3id.org/ro-id/31a6ed78-c6c3-4f9a-b3c6-4c96e9cb8eb0", "https://w3id.org/ro-id/6820ba72-9f8f-479f-9206-4d8500274ce9", "https://w3id.org/ro-id/7f306457-62d2-4dd4-8930-11c3b9129c1d", "https://w3id.org/ro-id/818b2c20-be83-4c6f-9191-2aab81b47d9b", "https://w3id.org/ro-id/856d187d-c96a-4da1-8743-3c477106be9b", "https://w3id.org/ro-id/b05ec41f-e5e5-45d5-8957-17891e714f81", "https://w3id.org/ro-id/bc1a37b6-03ee-4000-9f8a-8966cf1f5924", "https://w3id.org/ro-id/c050e1ee-d288-4cea-bab6-26c978ade3a3", "https://w3id.org/ro-id/d7842191-ae53-44bd-996c-6a56e6dc663c", "https://w3id.org/ro-id/d9f3778f-9f3d-43e6-9e5a-36b75a4b96ac"; "https://w3id.org/ro-id/45b83962-460b-40a8-8bcb-de6e2ff1294a", "https://w3id.org/ro-id/64ca15de-e2eb-465e-8469-0c28a6df89ef"; "Petrizzo, Antonio, Valentina Grande, Vanessa Moschino, and Fantina Madricardo. \"Automatic detection of MLs targets from the bathymetry.\" ROHub. May 09 ,2022. https://doi.org/10.24424/w5qx-b223." . a , ; "POLYGON ((12.308206558227539 45.42613630538257, 12.307777404785156 45.42538332041329, 12.315845489501953 45.42345563312358, 12.32764720916748 45.42216043125598, 12.32764720916748 45.42327490906539, 12.323012351989746 45.423425512487384, 12.316746711730955 45.425835112600126, 12.31241226196289 45.424901404761854, 12.308206558227539 45.42613630538257))" . a , ; "Here some results"; , , , ; "Results" . a , ; "Related documents and resources"; , , , , , ; "Document" . a , ; "Data input"; , ; "Input" . a , ; "It contains Jupyter notebook"; , ; "Notebooks" . a , , ; ; 1747374; "https://api.rohub.org/api/resources/09e78055-8aad-4a02-8c5d-2574c53c6011/download/"; ; "2022-05-09 10:57:07.579893+00:00"; "2022-08-30 14:29:55.484341+00:00"; "application/pdf"; ; "EASME/EMFF/2017/1.2.1.12/S2/05/SI2.789314 MarGnet official document with description of the application of the tool."; "2022-05-09 10:57:07.579893+00:00" . a , , ; ; 4845062; "https://api.rohub.org/api/resources/13faac2d-213a-45de-8936-09c728df7396/download/"; ; "2022-05-09 10:55:40.290485+00:00"; "2022-08-30 14:30:06.537698+00:00"; "image/png"; ; "Marine Litter Identification from Bathymetry"; "2022-05-09 10:55:40.290485+00:00" . a , , ; ; 726695; "https://api.rohub.org/api/resources/20119b4f-da6f-4723-8c5c-0f3367af1ec6/download/"; ; "2022-05-09 10:57:14.645946+00:00"; "2022-08-30 14:29:53.745052+00:00"; "application/pdf"; ; "EASME/EMFF/2017/1.2.1.12/S2/05/SI2.789314 MarGnet official document with description of ROs developed within MarGnet Project."; "2022-05-09 10:57:14.645946+00:00" . a , , ; ; "http://gismarcloud.myqnapcloud.com:8080/share.cgi?ssid=d0c16040872e4a47aee5b6664873057f"; ; "2022-08-29 09:49:06.931474+00:00"; "2022-08-30 14:29:48.715389+00:00"; "Shape file with targets detected from bathymetry"; ; "Arcgis workflow output"; "2022-08-29 09:49:06.931474+00:00" . a , , ; ; 3737442; "https://api.rohub.org/api/resources/2fcce231-9d47-4ec7-98d0-f11ce56703b4/download/"; ; "2022-05-09 10:57:00.318622+00:00"; "2022-08-30 14:29:57.372213+00:00"; 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The general formula of a carboxylic acid is R−COOH or R−CO2H, with R referring to the alkyl, alkenyl, aryl, or other group. Carboxylic acids occur widely. Important examples include the amino acids and fatty acids. 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Jan 19 ,2022. https://doi.org/10.24424/k5t9-z972." . a , ; , , ; "Pictures" . a , , ; ; "https://upload.wikimedia.org/wikipedia/commons/thumb/b/b5/Carboxylic-acid.svg/300px-Carboxylic-acid.svg.png"; ; "2022-01-19 19:49:17.752475+00:00"; "2022-09-21 19:38:00.155957+00:00"; "image/png"; ; "300px-Carboxylic-acid.svg.png"; "2022-01-19 19:49:17.752475+00:00" . a , , ; ; "https://upload.wikimedia.org/wikipedia/commons/thumb/8/87/Carboxyl-3D-space-filling-labelled.png/300px-Carboxyl-3D-space-filling-labelled.png"; ; "2022-01-19 19:49:57.141598+00:00"; "2022-09-21 19:38:03.215000+00:00"; "image/png"; ; "300px-Carboxyl-3D-space-filling-labelled.png"; "2022-01-19 19:49:57.141598+00:00" . a , , ; ; "https://upload.wikimedia.org/wikipedia/commons/thumb/8/8e/Carboxylate-resonance-hybrid.png/300px-Carboxylate-resonance-hybrid.png"; ; "2022-01-19 19:49:42.590787+00:00"; "2022-09-21 19:38:02.473015+00:00"; "image/png"; ; "300px-Carboxylate-resonance-hybrid.png"; "2022-01-19 19:49:42.590787+00:00" . a ; 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"anion"; "5.690200210748156"; "5.4" . a ; "Deprotonation of a carboxylic acid gives a carboxylate anion."; "26.175548589341695"; "16.7" . a ; "contain a carboxyl group"; "2.976846747519294"; "2.7" . a ; "A carboxylic acid is an organic acid that contains a carboxyl group (C(O)OH) attached to an R-group."; "54.858934169278996"; "35.0" . a ; "Organic chemical"; "Economy, business and finance/Economic sector/Chemicals/Organic chemical" . a ; "organic acid"; "12.750263435194942"; "12.1" . a ; "earth sciences"; "100.0"; "0.9274783134460449" . a ; "group"; "8.827404479578393"; "6.7" . a ; "protonation"; "5.163329820864067"; "4.9" . a ; "chemical formula"; "5.5848261327713375"; "5.3" . a ; "geochemistry"; "100.0"; "0.9274783134460449" . a ; "The general formula of a carboxylic acid is R?"; "18.96551724137931"; "12.1" . a ; "alkyl"; "3.898840885142255"; "3.7" . a ; "fatty acid"; "14.756258234519104"; "11.2" . a ; ""; "Applied sciences" . a ; ""; "Earth sciences" . a , , ; ; "https://discourse.pangeo.io/t/september-1-2022-handling-large-geo-data-with-julia/2656"; ; "2022-09-02 19:15:52.939627+00:00"; "2022-10-05 11:05:10.738946+00:00"; "You will find here all the information published to advertise the Pangeo Show & Tell Talk frm Felix Cremer on \"Handling large geo data with Julia \"."; ; "Pangeo discourse post announcing 1st September Show & Tell by Felix Cremer."; "2022-09-02 19:15:52.939627+00:00" . a , , ; ; "https://github.com/JuliaDataCubes/ESDLTutorials"; ; "2022-09-02 19:36:28.455672+00:00"; "2022-10-05 11:05:08.571565+00:00"; "This will become a selection of tutorials on the use of ESDL.jl and YAXArrays.jl julia packages for the handling of large scale out-of-core geospatial datasets."; "github"; ; "ESDLtutorial Github repository."; "2022-09-02 19:36:28.455672+00:00" . a , , ; ; "https://github.com/JuliaDataCubes/ESDLTutorials/raw/main/data/ne_50m_admin_0_countries.dbf"; ; "2022-09-02 19:27:25.914754+00:00"; "2022-10-05 11:04:59.380562+00:00"; "Part of ne_50m_admin_0_countries shapefile."; ; "ne_50m_admin_0_countries.dbf"; "2022-09-02 19:27:25.914754+00:00" . a , , ; ; "https://github.com/JuliaDataCubes/ESDLTutorials/raw/main/data/ne_50m_admin_0_countries.shp"; ; "2022-09-02 19:28:35.477795+00:00"; "2022-10-05 11:05:01.072396+00:00"; "Part of ne_50m_admin_0_countries shapefile."; "application/x-qgis"; ; "ne_50m_admin_0_countries.shp"; "2022-09-02 19:28:35.477795+00:00" . a , , ; ; "https://github.com/JuliaDataCubes/ESDLTutorials/raw/main/data/ne_50m_admin_0_countries.shx"; ; "2022-09-02 19:29:06.833916+00:00"; "2022-10-05 11:05:08.283815+00:00"; "Part of ne_50m_admin_0_countries shapefile."; "application/x-qgis"; ; "ne_50m_admin_0_countries.shx"; "2022-09-02 19:29:06.833916+00:00" . a , , , , , ; , ; "https://hackmd.io/@pangeo/showandtell", "https://hackmd.io/@pangeo/showandtell"; , ; "2022-09-20 12:05:09.775445+00:00", "2022-10-25 07:27:19.067533+00:00"; "2022-10-05 11:05:12.569218+00:00", "2022-10-25 15:48:28.394740+00:00"; """This is the shared document we use for all the Pangeo Show and Tell. We collect information, Q&A and feedback. Each Show and Tell has its own sub-section.""", """This is the shared document we use for all the Pangeo Show and Tell. We collect information, Q&A and feedback. Each Show and Tell has its own sub-section."""; , ; "HackMD Pangeo Show and Tell", "HackMD Pangeo Show and Tell"; "2022-09-20 12:05:09.775445+00:00", "2022-10-25 07:27:19.067533+00:00"; "hackmd" . a , , ; ; "https://juliadatacubes.github.io/YAXArrays.jl/dev/"; ; "2022-09-02 19:18:10.607898+00:00"; "2022-10-05 11:05:10.000002+00:00"; """YAXArrays.jl is another xarray-like Julia package. A package for operating on out-of-core labeled arrays, based on stores like NetCDF, Zarr or GDAL. Package Features: - open datasets from a variety of sources (NetCDF, Zarr, ArchGDAL) - interoperability with other named axis packages through YAXArrayBase - efficient mapslices(x) operations on huge multiple arrays, optimized for high-latency data access (object storage, compressed datasets)"""; ; "YAXArrays.jl Documentation"; "2022-09-02 19:18:10.607898+00:00" . a , , ; ; "https://raw.githubusercontent.com/JuliaDataCubes/ESDLTutorials/main/data/ne_50m_admin_0_countries.README.html"; ; "2022-09-02 19:23:40.734491+00:00"; "2022-10-05 11:05:10.091697+00:00"; "Admin 0 & Countries | Natural Earth"; "text/html"; ; "ne_50m_admin_0_countries.README.html"; "2022-09-02 19:23:40.734491+00:00" . a , , ; ; "https://raw.githubusercontent.com/JuliaDataCubes/ESDLTutorials/main/data/ne_50m_admin_0_countries.VERSION.txt"; ; "2022-09-02 19:24:56.813174+00:00"; "2022-10-05 11:05:08.830771+00:00"; "Version"; "text/plain"; ; "ne_50m_admin_0_countries.VERSION.txt"; "2022-09-02 19:24:56.813174+00:00" . a , , ; ; "https://raw.githubusercontent.com/JuliaDataCubes/ESDLTutorials/main/data/ne_50m_admin_0_countries.cpg"; ; "2022-09-02 19:26:00.758390+00:00"; "2022-10-05 11:05:10.411799+00:00"; "cpg file from shapefile dataset."; ; "ne_50m_admin_0_countries.cpg"; "2022-09-02 19:26:00.758390+00:00" . a , , ; ; "https://raw.githubusercontent.com/JuliaDataCubes/ESDLTutorials/main/data/ne_50m_admin_0_countries.prj"; ; "2022-09-02 19:27:59.472971+00:00"; "2022-10-05 11:05:12.806251+00:00"; "Part of ne_50m_admin_0_countries shapefile (projection information)."; ; "ne_50m_admin_0_countries.prj"; "2022-09-02 19:27:59.472971+00:00" . a , , ; ; "https://raw.githubusercontent.com/JuliaDataCubes/ESDLTutorials/main/overallintro.ipynb"; ; "2022-09-02 19:19:48.682613+00:00"; "2022-10-05 11:05:09.458760+00:00"; """Jupyter Notebook used by Felix during the Pangeo Show & Tell to demonstrate how to use EarthDataLab.jl to do large scale computations. To execute this Jupyter Notebook, data contained in the \"input folder\" is needed (please create a folder called \"data\" in the folder where you have stored the notebook)."""; ; "How to use EarthDataLab.jl to do large scale computations (Jupyter Notebook)"; "2022-09-02 19:19:48.682613+00:00" . a , ; "04jcwf484"; "Nordic e-Infrastructure Collaboration" . a ; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))"; "6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953" . a ; ; "c23c13de-3616-4fe4-9df0-64c0c303b28b"; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))" . a , , , , ; dct:doi "10.24424/2byf-7r07"; "False"; ; "2022-10-05 11:05:15.777066+00:00"; ; , ; ; ; 163759; "https://api.rohub.org/api/ros/77a61d94-3318-4d33-a3c0-4730e7026fdb/crate/download/"; ; ; "2022-09-02 19:02:01.731061+00:00"; "2024-03-05 12:18:33.627372+00:00"; "2022-09-02 19:02:01.731061+00:00"; """This talk is part of the Pangeo Show & Tell series and was given on September 1st 2022 by Felix Cremer. Bio Felix Cremer received his diploma in mathematics from the University of Leipzig in 2014. In 2016 he started his PhD study on time series analysis of hypertemporal Sentinel-1 radar data. He currently works at the Max-Planck-Institute for Biogeochemistry on the development of the JuliaDataCubes ecosystem in the scope of the NFDI4Earth 5 project. Abstract The Earth Data Lab (EDL) is a data cube framework in Julia for the efficient handling of raster data. It is based on the YAXArrays.jl package. YAXArrays.jl provides functionality to deal with labelled arrays, similar to the xarray python package and it also provides efficient and easy multithreading and distributed computation of user defined functions along arbitrary slices of the data. EarthDataLab.jl uses DiskArrays.jl in the backend to deal with out of memory datasets. In this Show-and-Tell Felix is going to give a short introduction into the EarthDataLab.jl package for raster data handling in Julia."""; "application/ld+json"; , , , ; "https://w3id.org/ro-id/77a61d94-3318-4d33-a3c0-4730e7026fdb"; "geodata", "julia"; ; "Video"; "Handling large geo data with Julia - snapshot", "Handling large geo data with Julia"; ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Felix Cremer, and Pangeo Europe. \"Handling large geo data with Julia.\" ROHub. Sep 02 ,2022. https://doi.org/10.24424/2byf-7r07." . a , ; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))" . a , ; , , ; "output" . a , ; , ; "tool" . a , ; , ; "biblio" . a , ; , , , , , , ; "input" . a , , ; ; 138593; "https://api.rohub.org/api/resources/9b5c569a-f9bd-4147-9844-4d856bd858db/download/"; ; "2022-09-02 19:30:37.195378+00:00"; "2022-10-05 11:05:15.216316+00:00"; "Plot from the Julia Jupyter notebook."; "image/png"; ; "plot_italy_julia_pangeo_ST.png"; "2022-09-02 19:30:37.195378+00:00" . a ; dct:conformsTo ; . a . a , ; "A community platform for Big Data geoscience", "A community platform for Big Data geoscience"; "pangeo-europe@gmail.com", "pangeo-europe@gmail.com"; "Pangeo", "Pangeo"; "https://pangeo.io/", "https://pangeo.io/" . a ; "raster data"; "13.14031180400891"; "5.9" . a ; "memory dataset"; "14.823008849557521"; "6.7" . a ; "computer operations and hardware"; "100.0"; "0.9168391823768616" . a ; "on Sep-1-2022" . a ; "diploma"; "7.854406130268199"; "4.1" . a ; "In this Show-and-Tell Felix is going to give a short introduction into the EarthDataLab.jl package for raster data handling in Julia."; "35.1981351981352"; "15.1" . a ; "time series"; "10.727969348659006"; "5.6" . a ; "YAXArrays.jl package"; "24.557522123893804"; "11.1" . a ; "earth sciences"; "100.0"; "0.9773926138877869" . a ; "data"; "18.262806236080177"; "8.2" . a ; "Library and museum"; "Arts, culture and entertainment/Culture/Library and museum" . a ; "mathematical and computer sciences"; "100.0"; "0.9168391823768616" . a ; "EarthDataLab.jl"; "16.70378619153675"; "7.5" . a ; "handling"; "12.694877505567929"; "5.7" . a ; "Plovdiv"; . a ; "treatment"; "15.708812260536398"; "8.2" . a ; "data"; "21.839080459770116"; "11.4" . a ; "functionality"; "8.045977011494253"; "4.2" . a ; "in 2014" . a ; "computer science"; "51.54639175257732"; "5.0" . a ; "Science and technology"; "Science and technology" . a ; "other earth sciences"; "100.0"; "0.9773926138877869" . a ; "The Earth Data Lab (EDL) is a data cube framework in Julia for the efficient handling of raster data."; "31.934731934731936"; "13.7" . a ; "dataset"; "10.244988864142538"; "4.6" . a ; "This talk is part of the Pangeo Show & Tell series and was given on September 1st 2022 by Felix Cremer."; "32.86713286713287"; "14.1" . a ; "raster data handling"; "26.106194690265486"; "11.8" . a ; "multithreading"; "6.8965517241379315"; "3.6" . a ; "geo data"; "19.469026548672566"; "8.8" . a ; "YAXArrays.jl"; "13.585746102449889"; "6.1" . a ; "In 2016" . a ; "Felix Cremer"; "15.367483296213809"; "6.9" . a ; "calculation"; "7.662835249042146"; "4.0" . a ; "dataset"; "12.452107279693488"; "6.5" . a ; "parcel"; "8.812260536398467"; "4.6" . a ; "database"; "48.453608247422686"; "4.7" . a ; "series analysis"; "15.044247787610619"; "6.8" . a , , ; ; "https://youtu.be/18_e8wmI9Os"; ; "2022-09-02 19:13:04.311770+00:00"; "2022-10-05 11:05:08.693363+00:00"; "This is the recorded talk from Felix Cremer during the Pangeo Show & Tell in September 1st, 2022. Felix is going through his Julia Notebook and explain us about handling large geo data with Julia."; ; "Youtube video \"Handling large geo data with julia by Felix Cremer.\""; "2022-09-02 19:13:04.311770+00:00" . a ; "Max-Planck-Institute (Germany)"; "fcremer@bgc-jena.mpg.de"; "Felix Cremer" . a , ; "pangeo.europe@gmail.com", "pangeo.europe@gmail.com"; "Pangeo Europe", "Pangeo Europe" . a ; ""; "Applied sciences" . a ; ""; "Earth sciences" . a , ; "", ""; "Earth observation", "Earth observation" . a , , ; ; "https://discourse.pangeo.io/t/discrete-global-grid-systems-dggs-use-with-pangeo/2274"; ; "2022-10-07 12:57:56.628114+00:00"; "2022-10-25 15:48:28.199436+00:00"; "Discussion from Pangeo Discourse on DGGS use with Pangeo."; "discussion"; ; "Pangeo discourse on \"Discrete Global Grid Systems (DGGS) use with Pangeo\""; "2022-10-07 12:57:56.628114+00:00" . a , , ; ; "https://discourse.pangeo.io/t/october-6-2022-dggs-and-their-potential-impact-in-geoscience-and-geospatial-communities/2759"; ; "2022-10-25 15:45:23.831383+00:00"; "2022-10-25 15:48:40.680580+00:00"; "Pangeo discourse announcement."; "discourse"; ; """Pangeo discourse announcement Show & Tell on \"October 6, 2022: DGGS and their potential impact in Geoscience and Geospatial communities\""""; "2022-10-25 15:45:23.831383+00:00" . a , , ; ; "https://github.com/allixender/pangeo_dggs_2022"; ; "2022-10-07 12:51:00.692996+00:00"; "2022-10-25 15:48:26.907094+00:00"; """Github repository with examples used during the Pangeo Show and Tell - 06. Oct., 2022 on \"DGGS and their potential impact in Geoscience and Geospatial\" by Alexander Kmoch (Landscape Geoinformatics Lab, University of Tartu, Estonia). 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"Anne Foilloux, Federica Foglini, and Elisa Trasatti. \"FDO Conference 2022: FAIR Research Objects for realizing Open Science with RELIANCE EOSC project.\" ROHub. 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While the signing will take place at the end of the conference, in Leiden, we would like to invite you to add your name to the movement initiated by FDO2022 by signing the declaration online. It is an opportunity for all of us working in research, technology, policy and beyond to support an unprecedented effort to further develop FAIR digital objects, open standards and protocols, and increased reliability and trustworthiness of data. In short, a new environment that works as a truly meaningful data space. You can sign the declaration using the button at the end of the page. 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This presentation gives an overview of the PAngeo Community and perspectives on creating Open Source user workflows."; "application/ld+json"; , , , ; "https://w3id.org/ro-id/042f0584-c14d-4374-9158-d84f4677c9fe"; "earth observation", "open innovation", "open source", "user pathways"; ; "Presentation"; "Perspective from the Pangeo Community on creating Open Source user workflows - ESA-NASA Open Innovation for EO Programmes 2022 - snapshot", "Perspective from the Pangeo Community on creating Open Source user workflows - ESA-NASA Open Innovation for EO Programmes 2022"; ; , ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Anne Foilloux, and Pangeo Europe. \"Perspective from the Pangeo Community on creating Open Source user workflows - ESA-NASA Open Innovation for EO Programmes 2022.\" ROHub. 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"3.79746835443038"; "5.4" . a , , ; "Nordic e-Infrastructure Collaboration (NeIC)", "Nordic e-Infrastructure Collaboration (NeIC)", "Nordic e-Infrastructure Collaboration (NeIC)"; "annefou@geo.uio.no", "annefou@geo.uio.no", "annefou@geo.uio.no"; "Anne Fouilloux", "Anne Fouilloux", "Anne Fouilloux"; "0000-0002-1784-2920", "0000-0002-1784-2920", "0000-0002-1784-2920" . a ; "pangeo.europe@gmail.com"; "Pangeo Europe" . a ; "service-account-enrichment" . a , , , ; "", "", "", ""; "Environmental research", "Environmental research", "Environmental research", "Environmental research" . a , , ; "", "", ""; "Applied sciences", "Applied sciences", "Applied sciences" . a , ; "", ""; "Earth sciences", "Earth sciences" . a ; ""; "Climatology" . a ; ""; "Earth observation" . a , ; "jeani@uio.no", "jeani@uio.no"; "Jean Iaquinta", "Jean Iaquinta"; "0000-0002-8763-1643", "0000-0002-8763-1643" . a , , , , , ; "post@simula.no", "post@simula.no", "post@simula.no"; "00vn06n10", "00vn06n10", "00vn06n10"; "Simula Research Laboratory", "Simula Research Laboratory", "Simula Research Laboratory" . a ; 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The presentation and demo were given during the pan-europeans digital assets supporting research communities. Agenda of the event: On 5-6 December 2022, EOSC Future and the INFRAEOSC-07 projects (C-SCALE, DICE, EGI-ACE, OpenAIRE Nexus, Reliance) are hosting an online use case showcase. Check out the agenda and register for this online interactive event by 4 December, 23.59 CET. Over 2 half-day webinars, actual EOSC users will present how their research communities are using EOSC digital assets to address scientific and societal challenges related to 3 UN Sustainable Development Goals (SDGs): • Climate action (SDG 13) • Industry, Innovation & infrastructure (SDG 9) • Good health & well-being (SDG 3) There will also be a session with use cases related to Open Science more broadly. Why ‘use cases’? The demonstrative, first-hand format of the event will enable real research communities to show how their work can be leveraged by EOSC. Researchers, disciplinary groups and anyone interested to learn about both EOSC-related tools and services for data sharing and discoverability as well as discipline-related solutions are invited to the webinar. Attendees will also hear first-hand accounts from early-adopter communities that have integrated some of these core EOSC services. 1 programme, 2 days Check out the agenda to get a glimpse of the cases in the programme, in addition to a at the users, EU and UN officials who will be weighing in on discussions. Day 1 – 5 December • 09.30-11.00: Digital assets supporting SDG 13: Climate action • 11.15-12.00: Digital assets supporting SDG 3: Good health and well-being • 12:15-13:00: Discovering services for open science Day 2 – 6 December • 09.00-09.45: Digital assets supporting SDG 9 Industry, innovation and infrastructure • 10.00-10.45: Experiences from Early Adopters approaching EOSC: the RELIANCE Open challenge • 11.00-12.00: Lessons Learnt from use cases and Looking forward"""; "application/ld+json"; , , , , , , , ; "https://w3id.org/ro-id/107487d2-a9d5-4224-8b00-b321e133b6c8"; "deep learning", "forecasting", "sea-ice"; ; "Presentation"; "Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC - snapshot", "Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC"; ; "MANUAL"; "https://w3id.org/ro-id/107487d2-a9d5-4224-8b00-b321e133b6c8/1c144684-1ea3-4cb5-93e6-8cffecf3b849"; "Anne Foilloux, Jean Iaquinta, and Alejandro Coca-Castro. \"Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC.\" ROHub. 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This demo goes with the presentation (slides) and show how the original work was published s a paper in nature communications. The code and data were available and Alejandro Coca-Castro re-used it to create an executable Research Object with a Jupyter Notebook. This Jupyter Notebook examplifies the use of IceNet (probabilistic deep learning to forecast sea-ice). This executable Research Object was forked and deviated work was created e.g. the Jupyter notebook was updated to make it more accessible to people that are not from the Climate community. We use B2DROP to store the new Jupyter notebook and the results to share while doing. Whenever we update the notebook or add figures, the corresponding Research Object is updated live on RoHub. We are now getting close to Open Science e.g. sharing while doing."; "video/mp4"; "mp4"; ; "Demo showing the usage of RELIANCE service for seasonal sea-ice forecasting."; "2022-12-05 12:33:43.590961+00:00" . a , , ; ; "https://docs.google.com/presentation/d/1QPrWh-PuW514mGsVrc9GEIrKYGY7k0L_/edit?usp=sharing&ouid=117642930190987755261&rtpof=true&sd=true"; ; "2022-12-05 12:24:19.690502+00:00"; "2022-12-05 13:24:34.792481+00:00"; """Climate change: Collaborative, reproducible and transparent science for seasonal sea-ice forecasting. 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The example shown is about the \"impact of the Covid-19 Lockdown on Air quality over Europe using Copernicus and EOSC project services\"."; "youtube"; ; "Turning FAIR and Open Science into Reality (demo, video)"; "2022-11-21 14:52:01.754759+00:00" . a , , ; ; "https://eoscfuture.eu/newsfuture/answering-research-questions-with-eosc/"; ; "2022-11-21 15:36:19.837234+00:00"; "2022-12-11 18:54:52.850465+00:00"; """Answering research questions with EOSC, March 10, 2022. Climate Data Scientist Anne Fouilloux and her team were faced with a research question: In France, have there been changes in air quality over the course of the COVID-19 pandemic? With the help of compute services available through EOSC, Anne was able to search for European air quality data analysis. 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With advancements in computing, software, and data management, the tools are available to transform science into a truly open, collaborative, and inclusive space. By following open science practices, we can increase accessibility of scientific research and findings, improve collaboration, and facilitate high quality, reproducible science. This session will showcase success stories in the Earth and space sciences and highlight a range of open science platforms, datasets, and computational tools. Join this session for real-world examples of how open science practices have empowered and enabled scientists across disciplines to carry out successful research projects."""; "session"; ; "ED16B - Open Science Practices and Success Stories Across the Earth, Space, and Environmental Sciences IV Oral"; "2022-12-09 18:50:29.467565+00:00" . a , , ; ; "https://w3id.org/ro-id/18269477-c1b8-4aa8-9b0e-372c7bb6b65c"; ; "2022-12-08 08:54:10.991302+00:00"; "2022-12-23 17:56:59.163701+00:00"; "This research object is a fork from RO examplifying Sea ice forecasting using IceNet notebook published in the Environmental Data Science book. 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The Environmental Data Science book is a living, open and community-driven online resource to showcase and support the publication of data, research and open-source tools for collaborative, reproducible and transparent Environmental Data Science. The Environmental Data Science is: a book a community a global collaboration We target to make sense of: environmental systems environmental data and sensors innovative research in Environmental Data Science open-source tools for Environmental Data Science We hope you find the content in the resource helpful. The resource and executable notebooks are free under a CC-BY licence and OSI-approved MIT license, respectively."""; "application/ld+json"; , , , , , , ; "https://w3id.org/ro-id/871a1786-bc6a-4e60-a160-3f57e3869d35"; "open science", "reproducible", "sea-ice"; ; "Video"; "AGU 2022 - Environmental Data Science Book: a community-driven resource showcasing open-source Environmental science - snapshot", "AGU 2022 - Environmental Data Science Book: a community-driven resource showcasing open-source Environmental science"; , ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Anne Foilloux, Alejandro Coca-Castro, Environmental Data Science Book Community, Jean Iaquinta, Tom Andersson, Nick Barlow, and . Scott Hosking. \"AGU 2022 - Environmental Data Science Book: a community-driven resource showcasing open-source Environmental science.\" ROHub. 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Scott Hosking" . a , ; "service-account-enrichment", "service-account-enrichment" . a , ; "", ""; "Applied sciences", "Applied sciences" . a , , ; ; "https://docs.google.com/presentation/d/1jxxwEGLiyuqYRJlH5VswekPJVoe5oxjlxVQrEiOojfI/edit?usp=sharing"; ; "2023-01-08 20:47:05.281382+00:00"; "2023-02-19 13:17:27.238629+00:00"; "Poster on experiences from the NICEST2 project for NeIC All hands meeting 2023."; "google-doc"; ; "Poster on our experiences from the NICEST2 project"; "2023-01-08 20:47:05.281382+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.4749515"; ; "2023-01-08 21:06:32.125399+00:00"; "2023-02-19 13:17:19.315916+00:00"; """Report on the bottlenecks that would hinder the efficient usage of Nordic ESMs on EuroHPC and possible remediation actions (I/Os, adding GPU support, etc.) with clear information on costs in terms of manpower. ESMs used in the Nordic countries are clearly not ready for EuroHPC and very little dedicated funding from the scientific community is used for porting existing codes to future architectures. Providers have hired several specialists to support the scientific community but the commitment from the scientific community is not there. Exchange of knowledge of involved staff (scientists, RSEs, technical support) would be very helpful. For instance, being able to organize meetings/hackathons (online or face to face) with both experts from NorESM and EC-EARTH has been highlighted as an important requirements by those involved in the GPU hackathon. Code refactoring and best software practices are the most important component for efficient usage of new architecture, including EuroHPC."""; ; "NICEST2 - D4.5: First report on the identified bottlenecks for an efficient usage of Nordic ESMs on EuroHPC"; "2023-01-08 21:06:32.125399+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.4944686"; ; "2023-01-08 21:03:28.636733+00:00"; "2023-02-19 13:17:22.369015+00:00"; "This report summarizes the first NICEST2 hackathon with FAIR experts and Earth System Model specialists to understand what needs to be done to make climate data FAIR. It will help us to define our roadmap for FAIR Climate in the Nordics."; ; "NICEST2 - D3.3: Report on NICEST2 FAIR climate data hackathon"; "2023-01-08 21:03:28.636733+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5571344"; ; "2023-01-08 21:08:01.968412+00:00"; "2023-02-19 13:17:27.394767+00:00"; "The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system Models (ESMs) that is not widely used in the Nordics yet. A hackathon/workshop was held on March 12, 2021 as a joint event between the INES, NICEST2 and IS-ENES3 projects. During this hackathon, we identified the needs for specific diagnostics for the Nordics that could help researchers to diagnose strengths and deficiencies of current ESMs. We also discussed how to better organize access to data and share resources within the Nordics."; ; "NICEST2 - D2.1: Short report from the Nordic ESM diagnostics hackathon"; "2023-01-08 21:08:01.968412+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5571416"; ; "2023-01-08 21:10:14.737755+00:00"; "2023-02-19 13:17:27.065885+00:00"; "The Nordic climate modeling community consists of research groups at universities, national meteorological institutes and research institutes, and holds demonstrable world class excellence in the field. Several of these groups contribute to the development of both global and regional climate models (GCMs and RCMs,respectively) in international projects with collaborations within Europe and the US. However, many users, including PhDs and postdocs, are developing and/or running Earth System Models (ESMs) for more fundamental scientific research and sensitivity studies, and/or cross-disciplinary research (economy & climate, biodiversity, etc.) and they do not always benefit from the advances, technologies or resources leveraged by these large projects/consortiums. One concrete example is IS-ENES project (https://is.enes.org/) where only one university, namely Linköpings Universitet (not part of the NICEST2 consortium) from the Nordics is involved; Nordic contributions are mostly from Meteorological services and Research Institutes. From a practical point of view this translates in a lot of time/energy wasted “reinventing the wheel”, repeated simulations, lack of transparency, suboptimal use of the infrastructures, etc. In this context, supporting these researchers and realizing the benefits of Open Science and EOSC are our priorities within NICEST2 and WP4."; ; "NICEST2 - D4.1: Identification of the Nordic ESM community needs for ESM workflows"; "2023-01-08 21:10:14.737755+00:00" . a , , ; ; "https://nordicesmhub.github.io/NorESM_user_workshop_2021/intro.html"; ; "2023-01-08 20:50:23.537300+00:00"; "2023-02-19 13:17:27.609612+00:00"; "Training material on containers for ESM. This training material uses the Norwegian Earth System Model (NorESM) and has been delivered in 2021 as part of the NorESM user meeting."; "text/html"; "training"; ; "Running NorESM in a container"; "2023-01-08 20:50:23.537300+00:00" . a , , ; ; "https://nordicesmhub.github.io/nicest2-fair-hackathon/"; ; "2023-01-08 20:52:04.176203+00:00"; "2023-02-19 13:17:18.829914+00:00"; "First NICEST2 hackathon to understand the FAIR concept and how they can apply to the Nordic Earth System Modelling Community."; ; "NICEST2 hackathon on FAIR climate data"; "2023-01-08 20:52:04.176203+00:00" . a , , ; ; "https://nordicesmhub.github.io/nicest2/2020/05/04/plan.html"; ; "2023-01-09 08:28:36.495799+00:00"; "2023-02-19 13:17:20.174631+00:00"; "Link to the NICEST2 project plan."; "text/html"; ; "Project plan"; "2023-01-09 08:28:36.495799+00:00" . a ; "Finnish Meteorological Institute (Finland)"; "antti-ilari.partanen@fmi.fi"; "Antti-Ilari Partanen"; "0000-0002-0883-8161" . a , ; "Simula Research Laboratory", "Simula Research Laboratory"; "annef@simula.no", "annef@simula.no"; "Anne Fouilloux", "Anne Fouilloux"; "0000-0002-1784-2920", "0000-0002-1784-2920" . a ; "NSC (Sweden)"; "struthers@nsc.liu.se"; "Hamish Struthers"; "0000-0002-4214-2213" . a ; "NERSC (Norway)"; "yanchun.he@nersc.no"; "Yanchun He"; "0000-0002-5932-3627" . a ; "Finnish Meteorological Institute (Finland)"; "tommi.bergman@fmi.fi"; "Tommi Bergman"; "0000-0002-6133-2231" . a ; "Norwegian Meteorological Institute (Norway)"; "oskaral@met.no"; "Oskar Landgren"; "0000-0002-6264-8502" . a , ; "jeani@uio.no", "jeani@uio.no"; "Jean Iaquinta", "Jean Iaquinta"; "0000-0002-8763-1643", "0000-0002-8763-1643" . a ; "Finnish Meteorological Institute (Finland)"; "risto.makkonen@fmi.fi"; "Risto Makkonen"; "0000-0002-8961-3393" . a , , , ; "post@simula.no", "post@simula.no"; "00vn06n10", "00vn06n10"; "Simula Research Laboratory", "Simula Research Laboratory" . a , ; "04jcwf484"; "Nordic e-Infrastructure Collaboration" . a ; ; "8fc9a20e-fa82-43a8-93f4-cd4cc4a45ac8"; "POINT (10.138547627793743 61.47037998202813)" . a ; "10.138547627793743"; "61.47037998202813"; "POINT (10.138547627793743 61.47037998202813)" . a , , ; dct:doi "https://doi.org/10.24424/9y3x-hg89"; "False"; ; "2023-02-19 13:17:31.060596+00:00"; ; ; , , , , ; ; 763258; "https://api.rohub.org/api/ros/b62e5267-8fe1-4fe1-ada2-47e484c2b107/crate/download/"; , , , , , , , , , ; , ; ; "2023-01-08 20:41:20.579173+00:00"; "2024-03-05 12:18:19.992972+00:00"; "2023-01-08 20:41:20.579173+00:00"; "Overview of the NICEST2 project and reflection on the successes, failures and possible improvements for follow-up projects."; "application/ld+json"; , , , , , , ; "https://w3id.org/ro-id/b62e5267-8fe1-4fe1-ada2-47e484c2b107"; "climate", "e-infrastructure"; ; "Poster"; "Experience from the NeIC NICEST2 project - NeIC All-Hands meeting (23–26 Jan 2023)", "Experience from the NeIC NICEST2 project - snapshot"; , ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Iaquinta, Jean, Oskar Landgren, Alok Kumar Gupta, Prashanth Dwarakanath, Anne Fouilloux, Tommi Bergman, Tyge Løvseth, et al. \"Experience from the NeIC NICEST2 project - NeIC All-Hands meeting (23–26 Jan 2023).\" ROHub. Jan 08 ,2023. https://doi.org/10.24424/9y3x-hg89." . a , ; "POINT (10.138547627793743 61.47037998202813)" . a , ; "This folder contains NICEST2 deliverables."; , , , ; "deliverables" . a , ; "Folder containing training material developed and delivered within the NICEST2 projects (either as training or hackathons)."; , ; "training" . a , , ; ; 771062; "https://api.rohub.org/api/resources/565cfd17-f309-4a85-9bdd-c0161f486c55/download/"; ; "2023-01-08 20:45:29.648781+00:00"; "2023-02-19 13:17:29.630057+00:00"; "Overall view of the NICEST2 poster for the NeIC all-hands meeting. It is mostly used for the sketch."; "image/png"; ; "NICEST2 poster for NeIC AHM2023.png"; "2023-01-08 20:45:29.648781+00:00" . a . a , ; ; 771062; "https://api.rohub.org/api/resources/bcfaae33-8fd4-4978-ad7a-e88940436d2d/download/"; ; "2023-02-23 21:50:55.971537+00:00"; "2023-02-23 21:50:58.608624+00:00"; "image/png"; ; "NICEST2 poster for NeIC AHM2023.png"; "2023-02-23 21:50:55.971537+00:00" . a , ; ; 771062; "https://api.rohub.org/api/resources/f43ff13a-adb1-4dae-8d5d-7de044a923d6/download/"; ; "2023-01-17 14:38:23.066910+00:00"; "2023-02-19 13:17:30.657154+00:00"; "image/png"; ; "NICEST2 poster for NeIC AHM2023.png"; "2023-01-17 14:38:23.066910+00:00" . a . a ; dct:conformsTo ; . a , ; "NICEST-2 - the second phase of the Nordic Collaboration on e-Infrastructures for Earth System Modeling focuses on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing initiatives.", "NICEST-2 - the second phase of the Nordic Collaboration on e-Infrastructures for Earth System Modeling focuses on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing initiatives."; "Nordic Collaboration on e-Infrastructures for Earth System Modeling Tools", "Nordic Collaboration on e-Infrastructures for Earth System Modeling Tools"; "https://w3id.org/ro-id/ed4e6aa2-9db8-452d-9301-ba1606361034", "https://w3id.org/ro-id/ed4e6aa2-9db8-452d-9301-ba1606361034" . a . a ; "experience"; "10.18735362997658"; "8.7" . a ; "success"; "14.528593508500773"; "9.4" . a ; "26 Jan 2023). 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In view of COVID-19 pandemic, lockdowns were imposed in India. Travel, fishing, tourism and religious activities were halted, while domestic and industrial activities were restricted. Comparison of the pre- and post-lockdown data shows that water parameters such as turbidity, nutrient concentration and microbial levels have come down from pre- to post-lockdown period, and parameters such as dissolved oxygen levels, phytoplankton and fish densities have improved. The concentration of macroplastics has also dropped from the range of 138 ± 4.12 and 616 ± 12.48 items/100 m2 to 63 ± 3.92 and 347 ± 8.06 items/100 m2. Fish density in the reef areas has increased from 406 no. 250 m−2 to 510 no. 250 m−2. The study allows an insight into the benefits of effective enforcement of various eco-protection regulations and proper management of the marine ecosystems to revive their health for biodiversity conservation and sustainable utilization."; "Reef fish", "covid-19", "environmental health", "plastic pollution"; ; "COVID-19 lockdown improved the health of coastal environment and enhanced the population of reef-fish"; "2023-01-08 19:24:00.526730+00:00" . a , , ; ; "https://earthobservatory.nasa.gov/images/83394/parting-the-sea-to-save-venice"; ; "2023-01-08 19:58:47.516622+00:00"; "2023-02-19 13:22:55.402245+00:00"; "The natural-color Landsat images above show some of the MOSE engineering efforts that are visible above the water line near the Lido Inlet. The top image was acquired on June 20, 2000, by the Enhanced Thematic Mapper+ on Landsat 7. The second image, from the Operational Land Imager on Landsat 8, was collected on September 4, 2013. Turn on the image comparison tool to make the changes easier to see. (Note that Landsat 8 has a greater dynamic range than Landsat 7, so the Landsat 8 image is crisper the Landsat 7 image.)"; ; "Parting the Sea to Save Venice"; "2023-01-08 19:58:47.516622+00:00" . a ; "giorgio.castellan@bo.ismar.cnr.it"; "Giorgio Castellan"; "0000-0001-6084-1504" . a ; "federica.foglini@ismar.cnr.it"; "Federica Foglini"; "0000-0002-2736-0052" . a ; "CNR-ISMAR"; "malek.belgacem@ve.ismar.cnr.it"; "Malek Belgacem"; "0000-0003-0745-4155" . a ; "Małgorzata Wolniewicz" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69623:EU_CAMS_SURFACE_NO2_G"; ; "2023-01-08 19:40:14.176174+00:00"; "2023-02-19 13:22:52.387115+00:00"; "CAMS NITROGEN DIOXIDE"; "2022-12-27T23:00:00Z"; "NO2"; ; "CAMS European air quality forecasts: NO2"; "2023-01-08 19:40:14.176174+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[1.354510459350422e-07]"; "[0.0]" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69625:EU_CAMS_SURFACE_O3_G"; ; "2023-01-08 19:41:17.789149+00:00"; "2023-02-19 13:22:49.529744+00:00"; "CAMS OZONE"; "2022-12-27T23:00:00Z"; "O3"; ; "CAMS European air quality forecasts: O3"; "2023-01-08 19:41:17.789149+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[2.2007016298175586e-07]"; "[0.0]" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69627:EU_CAMS_SURFACE_PM25_G"; ; "2023-01-08 19:42:25.690080+00:00"; "2023-02-19 13:22:51.053690+00:00"; "CAMS SURFACE PARTICULATE METTER D<2.5"; "2022-12-27T23:00:00Z"; "PM2.5"; ; "CAMS European air quality forecasts: PM25"; "2023-01-08 19:42:25.690080+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[709.8012084960938]"; "[0.0]" . a , , ; ; "https://w3id.org/ro-id/0869e396-3733-4aff-8fb2-94c8937b28aa"; ; "2023-01-08 19:15:20.212877+00:00"; "2023-02-19 13:22:55.556680+00:00"; "This is a case study of snapshot project http://snapshot.cnr.it/ to investigate the lockdown impact on the water quality at a selected site in the northern Adriatic Sea, precisely in Northern Adriatic Sea, the case of the Gulf of Venice using Machine Learning model."; ; "Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality"; "2023-01-08 19:15:20.212877+00:00" . a , , ; ; "https://w3id.org/ro-id/53aa90bf-c593-4e6d-923f-d4711ac4b0e1"; ; "2023-01-08 19:14:03.311972+00:00"; "2023-02-19 13:22:50.947789+00:00"; "The COVID-19 pandemic has led to significant reductions in economic activity, especially during lockdowns. Several studies has shown that the concentration of nitrogen dioxyde and particulate matter levels have reduced during lockdown events. Reductions in transportation sector emissions are most likely largely responsible for the NO2 anomalies. In this study, we analyze the impact of lockdown events on the air quality using data from Copernicus Atmosphere Monitoring Service over Europe and at selected locations."; ; "Impact of the Covid-19 Lockdown on Air quality over Europe"; "2023-01-08 19:14:03.311972+00:00" . a , , ; ; "https://w3id.org/ro-id/53aa90bf-c593-4e6d-923f-d4711ac4b0e1/resources/2a2b6f01-be2e-414e-af08-d882aa995a71"; ; "2023-01-08 19:21:48.221333+00:00"; "2023-02-19 13:22:50.794426+00:00"; "In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to estimate the change in air quality in 20 major cities on six continents. Our results show significant declines of AQI in NO2, SO2, CO, PM2.5 and PM10 in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. This work shows the reduction of primary pollutants, especially NO2, is mainly due to lockdown policies. However, preexisting local environmental policy regulations also contributed to declining NO2, SO2 and PM2.5 emissions, especially in Asian countries. In addition, higher rainfall during the lockdown period could cause decline of PM2.5, especially in Johannesburg. By contrast, the changes of AQI in ground-level O3 were not significant in most of cities, as meteorological variability and ratio of VOC/NOx are key factors in ground-level O3 formation."; ; "Impact of the COVID-19 Pandemic Lockdown on Air Quality Pollution in 20 Major cities around the World"; "2023-01-08 19:21:48.221333+00:00" . a . a , , ; ; "https://w3id.org/ro-id/c2c64bf9-7625-4442-9ca9-dcd978b1d38b"; ; "2023-01-08 19:19:35.675216+00:00"; "2023-02-19 13:22:48.215320+00:00"; "Integration of data on Air and Water quality in the Venice Lagoon to assess the impact of the Covid-19 Lockdown"; ; "Impact of the Covid-19 Lockdown on Air and Water quality in the Venice Lagoon"; "2023-01-08 19:19:35.675216+00:00" . a ; "The main interest is upon marine litter pollution and in particular ranging from marco to mirco and nano size. 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We are re-using existing Research Objects, and in particular Jupyter Notebooks that were created in previous studies."; "application/ld+json"; , , , , ; "https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654"; "air", "water"; ; "Jupyter Notebook"; "Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon - snapshot", "Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon"; ; , ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "https://w3id.org/ro/terms/earth-science#ExecutableResearchObjectTemplate"; "Fouilloux, Anne, Federica Foglini, Giorgio Castellan, Malek Belgacem, Jean Iaquinta, and Simone Mantovani. \"Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon.\" ROHub. 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; "2022-10-14 12:43:21.299002+00:00"; "2023-02-19 13:45:14.242980+00:00"; """This paper is from Gisela H. Govaart, Simon M. Hofmann, Evelyn Medawar. Ever-increasing anthropogenic greenhouse gas emissions narrow the timeframe for humanity to mitigate the climate crisis. Scientific research activities are resource demanding and, consequently, contribute to climate change; at the same time, scientists have a central role in advancing knowledge, also on climate-related topics. In this opinion piece, we discuss (1) how open science – adopted on an individual as well as on a systemic level – can contribute to making research more environmentally friendly, and (2) how open science practices can make research activities more efficient and thereby foster scientific progress and solutions to the climate crisis. While many building blocks are already at hand, systemic changes are necessary in order to create academic environments that support open science practices and encourage scientists from all fields to become more carbon-conscious, ultimately contributing to a sustainable future."""; "climate crisis", "open science", "sustainability"; ; "The Sustainability Argument for Open Science"; "2022-10-14 12:43:21.299002+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.6589624"; ; "2022-10-14 13:44:35.094465+00:00"; "2023-02-19 13:45:14.339103+00:00"; """Sharan, Malvika In this talk, I discuss open science as a framework to ensure that all our research components can be easily accessed, openly examined and built upon by others. I will introduce The Turing Way - an open source, open collaboration and community-driven guide to reproducible, ethical and inclusive data science and research. Drawing insights from the project, I will share best practices that researchers should integrate to ensure the highest reproducible and ethical standards from the start of their projects so that their research work is easy to reuse and reproduce at all stages of the development. All attendees will leave the talk understanding the many dimensions of openness and how they can participate in an inclusive, kind and inspiring open source ecosystem as they collaboratively seek to improve research culture. All questions and contributions are welcome at the GitHub repository: https://github.com/alan-turing-institute/the-turing-way. Home page: https://malvikasharan.github.io/ This was a closing keynote at Concordia University in Montreal on 27 May 2022."""; ; "Open science for enabling reproducible, ethical and collaborative research: Insights from The Turing Way"; "2022-10-14 13:44:35.094465+00:00" . a , , ; ; "https://en.wikipedia.org/wiki/Climate_justice"; ; "2022-10-15 08:03:53.413292+00:00"; "2023-02-19 13:45:22.058293+00:00"; "Definition of Climate Justice from Wikipedia."; "wikipedia"; ; "Climate Justice (Wikipedia)"; "2022-10-15 08:03:53.413292+00:00" . a , , ; ; "https://en.wikipedia.org/wiki/Environmental_justice"; ; "2022-10-15 08:02:56.218937+00:00"; "2023-02-19 13:45:11.910714+00:00"; "Definition of Environmental Justice from Wikipedia"; "wikipedia"; ; "Environmental Justice (Wikipedia)"; "2022-10-15 08:02:56.218937+00:00" . a ; "Simula Research Laboratory"; "annef@simula.no"; "Anne Fouilloux"; "0000-0002-1784-2920" . a ; "jeani@uio.no"; "Jean Iaquinta"; "0000-0002-8763-1643" . a , ; "post@simula.no"; "00vn06n10"; "Simula Research Laboratory" . a . a ; "POLYGON ((-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837))"; "-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837" . a ; ; "bf216e0e-aa84-449a-9cc2-dc6454de6d14"; "POLYGON ((-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837))" . a , , , , ; dct:doi "https://doi.org/10.24424/pm9w-vq46"; "False"; ; "2023-02-19 13:45:25.668867+00:00"; ; , ; ; ; 5188278; "https://api.rohub.org/api/ros/0e6ee388-ce22-4237-bf54-74336d1215ce/crate/download/"; , ; ; ; "2022-10-14 12:24:09.298835+00:00"; "2024-03-05 12:22:11.007454+00:00"; "2022-10-14 12:24:09.298835+00:00"; """OpenAIRE OAWeek - Research communities & climate action; being open to drive change Description This session will invite expert researchers to discuss their scientific impact in climate related topics. Why are they embracing open science practices in their current research workflows? How are they using the resources provided in the European Open Science Cloud (EOSC)? Is open access enabling researchers to contribute better to Climate Change solutions? If you’re curious about these innovative initiatives by the research communities, make sure you attend! Speakers: Anne Fouilloux (RELIANCE) Anabela de Oliveira (EGI-ACE) Bjorn Backeberg (C-SCALE) Prof Spyridon Rapsomanikis, Athena RC, NEANIAS"""; "application/ld+json"; , , , , , , ; "https://w3id.org/ro-id/0e6ee388-ce22-4237-bf54-74336d1215ce"; "climate change", "climate justice", "open science"; ; "Presentation"; "OpenAIRE OAWeek: Open for Climate Justice - snapshot", "OpenAIRE OAWeek: Open for Climate Justice"; ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "http://w3id.org/ro/earth-science#BibliographyCentricResearchObjectTemplate"; ; "Fouilloux, Anne, Jean Iaquinta, and Pangeo Europe. \"OpenAIRE OAWeek: Open for Climate Justice.\" ROHub. 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Mar 26 ,2022. https://doi.org/10.24424/f0q9-8e35." . a , ; "POINT (7.8337097307667145 48.01044395569975)" . a , ; "POINT (10.766601562500002 59.921531172441085)" . a , ; , ; "output" . a , ; , ; "input" . a , ; , , ; "biblio" . a , ; , , ; "tool" . a , , ; ; 448436; "https://api.rohub.org/api/resources/039f0e1f-ddb5-4a6b-8047-094aeb37b259/download/"; ; "2022-03-30 16:49:24.424570+00:00"; "2023-02-19 13:50:03.407487+00:00"; "Copernicus Atmosphere Monitoring Service PM2.5, 2 day forecasts, 24th December 2021 at 12:00 UTC"; "image/png"; ; "CAMS PM2.5, 2 day forecasts, 24th December 2021 at 12:00 UTC"; "2022-03-30 16:49:24.424570+00:00" . a . a , , ; ; "https://training.galaxyproject.org/training-material/topics/climate/tutorials/pangeo-notebook/tutorial.html"; ; "2022-03-30 15:59:56.246391+00:00"; "2023-02-19 13:49:56.427998+00:00"; """Training material (hands-on) where Pangeo Notebook is used to learn Xarray. This training is part of the Galaxy Training Network (GTN). In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem. We will be using data from Copernicus Atmosphere Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. Parallel data analysis with Pangeo is not covered in this tutorial."""; "text/html"; ; "Pangeo Notebook in Galaxy - Introduction to Xarray (GTN)"; "2022-03-30 15:59:56.246391+00:00" . a , , ; ; "https://quay.io/repository/nordicesmhub/docker-pangeo-notebook"; ; "2022-03-29 11:58:28.213223+00:00"; "2023-02-19 13:49:55.588074+00:00"; """These docker images (different tags) correspond to the docker images built for Galaxy Pangeo JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-pangeo-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b"""; ; "Docker images for Galaxy Pangeo JupyterLab (Quay Container Registry)"; "2022-03-29 11:58:28.213223+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5805953"; ; "2022-03-30 16:52:19.796786+00:00"; "2023-02-19 13:49:55.345103+00:00"; """Dataset used in the Galaxy Pangeo tutorials on Xarray. Data is in netCDF format and is from Copernicus Air Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. This dataset is very small and there is no need to parallelize our data analysis. Parallel data analysis with Pangeo is not covered in this tutorial and will make use of another dataset."""; ; "netCDF input file PM2.5 4 days forecast from December, 22 2020"; "2022-03-30 16:52:19.796786+00:00" . a , , ; "10.5281/zenodo.6394185"; ; "https://doi.org/10.5281/zenodo.6399102"; ; "2022-03-29 17:55:05.034625+00:00"; "2023-02-19 13:49:56.124648+00:00"; """This is a tarball for the Docker Galaxy pangeo-JupyterLab image - Version 1c0f66b. To use it: download the image file docker-pangeo-notebook-1c0f66b.tar load it with docker with the command: docker load --input docker-pangeo-notebook-1c0f66b.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-pangeo-notebook for more details"""; ; "Docker Galaxy pangeo-JupyterLab image Version 1c0f66b"; "2022-03-29 17:55:05.034625+00:00" . a , , ; ; 1729; "https://api.rohub.org/api/resources/56c7c29c-badc-45ad-bb41-75ba492064e2/download/"; ; "2022-03-29 12:08:38.781608+00:00"; "2023-02-19 13:49:59.656812+00:00"; "Default Jupyter Notebook used when starting Galaxy Climate JupyterLab if no other Jupyter Notebook is passed by the user."; ; "Default Jupyter Notebook for Galaxy Climate JupyterLab"; "2022-03-29 12:08:38.781608+00:00" . a , , ; ; 29899819; "https://api.rohub.org/api/resources/9663df26-3adb-40ed-b68e-391c2023ec0b/download/"; ; "2022-03-30 16:44:58.679622+00:00"; "2023-02-19 13:50:02.589260+00:00"; "This is a gif animated image showing how to start the Galaxy Pangeo JupyterLab in Galaxy Europe. 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Jul 27 ,2023. https://doi.org/10.24424/7gt2-h852." . a , ; , , , , , ; "biblio" . a , , ; ; "https://docs.google.com/presentation/d/1Zf94N8sm-oVo5ypOXiuIQp9dMGOV_MvOkLKdbyX89o0/edit#slide=id.gcd7e7a0697_0_0"; ; "2023-07-27 12:09:06.279463+00:00"; "2023-07-27 12:22:17.741960+00:00"; "Presentation given by Toby Hodges on 29 April 2021 to reflect on the First round of Lesson Development Study Groups. Toby explains what the training material on \"Lesson Development Study Group\" is about and how it helps The Carpentries community to co-develop training material."; ; "Lesson Development Study Groups: Reflecting on Round 1 & Planning for the Future"; "2023-07-27 12:09:06.279463+00:00" . a , , ; ; "https://coderefinery.org"; ; "2023-07-27 12:13:39.430228+00:00"; "2023-07-27 12:22:10.948474+00:00"; "CodeRefinery is a community project where you can find Training and e-Infrastructure for Research Software Development."; ; "The CodeRefinery website"; "2023-07-27 12:13:39.430228+00:00" . a , , ; ; "https://galaxyproject.org"; ; "2023-07-27 12:18:17.787123+00:00"; "2023-07-27 12:22:13.425735+00:00"; """Galaxy is an open-source platform for data analysis that enables users to: 1) Use tools from various domains (that can be plugged into workflows) through its graphical web interface. Run code in interactive environments (RStudio, Jupyter...) along with other tools or workflows; 2) Manage data by sharing and publishing results, workflows, and visualizations; 3) Ensure reproducibility by capturing the necessary information to repeat and understand data analyses; 4) The Galaxy Community is actively involved in helping the ecosystem improve and sharing scientific discoveries."""; "Project"; ; "The Galaxy Project website"; "2023-07-27 12:18:17.787123+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.8189268"; ; "2023-07-27 12:15:32.339298+00:00"; "2023-07-27 12:22:12.823369+00:00"; """A short overview of The Carpentries initiative, how they operate and collaboratively develop, maintain and deliver training on foundational coding and data science skills to researchers worldwide for researchers. 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Jan 05 ,2024. https://doi.org/10.24424/zcq6-9r81." . a , ; ; "data" . a , ; "raw data" . a , ; ; "biblio" . a , ; "metadata" . a , , ; dct:doi "10.24424/7nkm-2072"; ; 36301; "https://api.rohub.org/api/resources/55d5e2f5-c395-4da5-a7d1-9621c480d0ef/download/"; ; "2024-01-05 14:26:46.457298+00:00"; "2024-01-05 15:11:39.077450+00:00"; "Plot showing the bandwidth as a function of the message size on Fram and Betzy"; "image/png"; ; "OSU-2023Dec.png"; "2024-01-05 14:26:46.457298+00:00" . a , , ; dct:doi "10.24424/pv5n-vq62"; ; 1338; "https://api.rohub.org/api/resources/abbe45f6-a4c4-4ec4-af82-79bb0a95440e/download/"; ; "2024-01-05 14:33:02.319503+00:00"; "2024-01-05 15:11:39.583041+00:00"; "Output of the OSU MPI Get Bandwidth Test with openMPI 4.1.6 on Fram and Betzy"; "text/csv"; "Apptainer", "OpenMPI"; ; "OSU7.2-Fram-Betzy"; "2024-01-05 14:33:02.319503+00:00" . a ; dct:conformsTo ; . a ; "NICEST-2 - the second phase of the Nordic Collaboration on e-Infrastructures for Earth System Modeling focuses on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing initiatives."; "Nordic Collaboration on e-Infrastructures for Earth System Modeling Tools"; "https://w3id.org/ro-id/ed4e6aa2-9db8-452d-9301-ba1606361034" . a , , ; "2024-01-09 09:49:11.365811+00:00"; ; prov:wasDerivedFrom . a ; "bandwidth"; "8.112874779541444"; "4.6" . a ; "Message Passing Inerface"; "13.68421052631579"; "9.1" . a ; "Trondheim"; . a ; "Osu micro-benchmark"; "47.61321909424724"; "38.9" . a ; "Ohio State University"; "14.586466165413531"; "9.7" . a ; "High Performance Computer"; "8.721804511278195"; "5.8" . a ; "network interconnect"; "11.627906976744185"; "9.5" . a ; "benchmark"; "22.045855379188712"; "12.5" . a ; "The Ohio State University (OSU) Micro Benchmarks (OMB) are a widely used suite of benchmarks for measuring and evaluating the performance of MPI operations for point-to-point, multi-pair, and collective communications."; "47.12525667351129"; "45.9" . a ; "bench mark"; "24.867724867724867"; "14.1" . a ; "Education"; "Education" . a ; "micro benchmark"; "21.052631578947366"; "17.2" . a ; "University"; "Education/School/Higher education/University" . a ; "MPI operation"; "12.607099143206854"; "10.3" . a ; "computer network"; "9.876543209876543"; "5.6" . a ; "benchmark"; "23.60902255639098"; "15.7" . a ; "interconnect"; "10.225563909774436"; "6.8" . a ; "earth sciences"; "100.0"; "0.4361959993839264" . a ; "computer programming and software"; "100.0"; "0.6090793609619141" . a ; "mathematical and computer sciences"; "100.0"; "0.6090793609619141" . a ; "information technology"; "22.65625"; "2.9" . a ; "interconnect"; "11.28747795414462"; "6.4" . a ; "different Message Passing Inerface"; "7.099143206854345"; "5.8" . a ; "Steeple chase"; "Sport/Competition discipline/Horse racing/Steeple chase" . a ; "micro"; "21.804511278195488"; "14.5" . a ; "Here we use the OSU micro-benchmark (version 7.2) to assess the performance in terms of bandwidth achieved with an Apptainer container between 2 processors on different nodes with OpenMPI (version 4.1.6) on the Norwegian academic High Performance Computers (HPC) located in Tromsø (Fram) and Trondheim (Betzy)"; "22.689938398357288"; "22.1" . a ; "atmospheric sciences"; "100.0"; "0.4361959993839264" . a ; "computer science"; "77.34375"; "9.9" . a ; "Tromsø"; . a ; "microcomputer"; "23.809523809523807"; "13.5" . a ; "Office of Management and Budget"; . a ; "network"; "7.36842105263158"; "4.9" . a ; "These benchmarks are often used for comparing different Message Passing Inerface (MPI) implementations and the underlying network interconnect."; "30.184804928131417"; "29.4" . a , , ; ; "https://www.osti.gov/servlets/purl/1997634"; ; "2024-01-17 10:54:09.114061+00:00"; "2024-01-17 10:54:10.405249+00:00"; """Abstract—Open MPI is an open-source implementation of the MPI-3 standard that is developed and maintained by collaborators from academia, industry, and national laboratories. Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL) are collaborating on porting and optimizing Open MPI and related components for use on HPE Cray EX systems, with a focus on the DOE Frontier and Aurora exa-scale systems. A key component of this effort involves development of a new LinkX Open Fabrics Interface (OFI) provider. In this paper, we describe enhancements to Open MPI, OpenPMIx runtime components, and the LinkX OFI provider. Performance results are presented for point to point and collective communication operations using both the vendor CXI provider and the LinkX provider, including results obtained using GPU accelerators. Recommended deployment options for EX systems will be discussed, along with future work."""; "Slingshot 11", "libfabric"; ; "Open MPI for HPE Cray EX Systems"; "2024-01-17 10:54:09.114061+00:00" . a ; "forecasting sea ice"; "25.628140703517587"; "35.7" . a ; "Climate change"; "Environment/Climate change" . a ; "Arctic Zone"; "https://www.wikidata.org/wiki/Q25322" . a ; "Einet Galaxy"; "5.8225508317929755"; "6.3" . a ; "motivation involvement"; "5.455850681981334"; "7.6" . a ; "work"; "6.284658040665434"; "6.8" . a ; "motivation"; "5.545286506469501"; "6.0" . a ; "EGU"; "7.024029574861368"; "7.6" . a ; "impact"; "6.800286327845384"; "9.5" . a ; "environment"; "5.511811023622048"; "7.7" . a ; "geophysics"; "63.38268230536455"; "0.8625994324684143" . a ; "job market"; "15.053763440860214"; "1.4" . a ; "Wireless technology"; "Economy, business and finance/Economic sector/Computing and information technology/Wireless technology" . a ; "forecast"; "5.730129390018484"; "6.2" . a ; "work"; "5.368647100930566"; 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Apr 09 ,2024. https://doi.org/10.24424/vpkn-k902." . a , ; ; "tool" . a , ; ; "biblio" . a , ; , , , , ; "output" . a , ; ; "input" . a , , ; ; 772547; "https://api.rohub.org/api/resources/0ad18b1b-594f-4b8a-937e-eff3460be9dd/download/"; ; "2024-04-09 19:02:15.319953+00:00"; "2024-04-19 13:34:19.301131+00:00"; "Poster EGU 2024 (pdf) Implementation of a reproducible pipeline for producing seasonal Arctic sea ice forecasts"; "application/pdf"; "Poster"; ; "Poster EGU 2024 (pdf)"; "2024-04-09 19:02:15.319953+00:00" . a , , ; ; "https://usegalaxy.eu/u/vstoeckl/w/icenet"; ; "2024-04-09 18:52:16.320626+00:00"; "2024-04-19 13:34:22.939052+00:00"; "Galaxy workflow on the Galaxy Europe instance. To execute it, you would need first to get an account on Galaxy Europe (free of charge) and prepare the input dataset."; "galaxy"; ; "Galaxy Workflow IceNet sea-ice forecasting"; "2024-04-09 18:52:16.320626+00:00" . a , , ; ; "https://doi.org/10.1093/nar/gkac247"; ; "2024-04-09 18:59:25.010332+00:00"; "2024-04-19 13:34:23.594734+00:00"; "Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations."; "galaxy-platform"; ; "The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update"; "2024-04-09 18:59:25.010332+00:00" . a , , ; dct:doi "10.24424/tckn-et23"; ; 323417298; "https://api.rohub.org/api/resources/79406cf5-4e66-44dd-97ae-b996a17f2ec6/download/"; ; "2024-04-12 19:22:32.134693+00:00"; "2024-04-19 13:34:23.287670+00:00"; "video/mp4"; ; "Presentation"; "2024-04-12 19:22:32.134693+00:00" . a , , ; ; 1260982; "https://api.rohub.org/api/resources/8105ba74-e8df-435b-ac88-b2fb762365a5/download/"; ; "2024-04-11 11:31:09.064376+00:00"; "2024-04-19 13:34:22.725438+00:00"; "Sketch used in RoHub to illustrate the Research Object created for the poster at EGU 2024."; "image/png"; ; "sketch (based on the poster)"; "2024-04-11 11:31:09.064376+00:00" . a , , ; ; 1473306; "https://api.rohub.org/api/resources/bccd43db-8caf-4734-93d7-c864fb8139c3/download/"; ; "2024-04-12 19:24:37.138056+00:00"; "2024-04-19 13:34:20.251203+00:00"; "application/pdf"; ; "Presentation slides"; "2024-04-12 19:24:37.138056+00:00" . a , , ; ; "https://doi.org/10.5194/egusphere-egu24-8343"; ; "2024-04-09 18:57:09.049029+00:00"; "2024-04-19 13:34:20.491838+00:00"; "EGU abstract submitted."; ; "Abstract EGU24-8343 (poster)"; "2024-04-09 18:57:09.049029+00:00" . a , , ; ; "https://w3id.org/ro-id/ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef"; ; "2024-04-09 18:54:45.057065+00:00"; "2024-04-19 13:34:22.131841+00:00"; "Research Object with the Jupyter Notebook showcasing Sea ice forecasting in the Environmental Data Science book [https://edsbook.org/welcome.html](https://edsbook.org/welcome.html)"; ; "Sea ice forecasting using IceNet (Jupyter Notebook) published in the Environmental Data Science book"; "2024-04-09 18:54:45.057065+00:00" . a ; dct:conformsTo ; . a . a ; "Oil and gas - upstream activities"; "Economy, business and finance/Economic sector/Energy and resource/Oil and gas - upstream activities" . a ; "http"; "10.720887245841034"; "11.6" . a ; "implementation"; "5.082319255547603"; "7.1" . a ; "reproducible pipeline"; "10.050251256281406"; "14.0" . a ; "Hardware"; "Economy, business and finance/Economic sector/Computing and information technology/Hardware" . a ; "computer science"; "21.50537634408602"; "2.0" . a ; "Weather"; "Weather" . a ; "Implementation of a reproducible pipeline for forecasting sea ice."; "19.20485175202156"; "28.5" . a ; "earth sciences"; "100.0"; "1.9435470700263977" . a ; "geosciences"; "36.61731769463545"; "0.4983392357826233" . a ; "Galaxy workflow"; "7.2505384063173"; "10.1" . a ; "Implementation of a reproducible pipeline for forecasting sea ice"; "6.738544474393531"; "10.0" . a ; "workflow"; "2.43378668575519"; "3.4" . a ; """This Research Object corresponds to the work done by Vanessa Stoeckl, and presented as a poster at EGU 2024, ESSI 2.9 \"Seamless transitioning between HPC and cloud in support of Earth Observation, Earth Modeling and community-driven Geoscience approach PANGEO\". - Abstract submitted and accepted at EGU: [https://doi.org/10.5194/egusphere-egu24-8343](https://doi.org/10.5194/egusphere-egu24-8343) - [Rendered Jupyter notebook](https://edsbook.org/notebooks/gallery/ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef/notebook) - [Galaxy workflow showcasing the pipeline for forecasting sea ice](https://usegalaxy.eu/u/vstoeckl/w/icenet)"""; "48.113207547169814"; "71.4" . a ; "poster"; "2.1474588403722263"; "3.0" . a ; "geosciences"; "63.38268230536455"; "0.8625994324684143" . a ; "National Oceanic and Atmospheric Administration"; "https://www.wikidata.org/wiki/Q214700" . a ; "environment"; "5.6377079482439925"; "6.1" . a ; "The Alan Turing Institute"; "acoca@turing.ac.uk"; "Alejandro Coca-Castro" . a ; "bjoern.gruening@gmail.com"; "Björn Grüning" . a ; "vanessa-tamara@web.de"; "Vanessa Stoeckl" . a ; ""; "Oceanography" . a ; ""; "Environmental research" . a ; ""; "Applied sciences" . a , , ; ; "https://destination-earth.eu/use-cases/global-fish-tracking-system-gfts"; ; "2024-03-13 08:41:04.316157+00:00"; "2024-08-12 19:50:27.276584+00:00"; "Link to the official GFTS DESP use case."; "WebSite"; ; "DestinE Use Case official website: Global Fish Tracking System (GFTS) DESP Use Case"; "2024-03-13 08:41:04.316157+00:00" . a , , ; ; "https://destination-earth.github.io/DestinE_ESA_GFTS"; ; "2024-03-13 08:45:35.825465+00:00"; "2024-08-12 19:50:16.380874+00:00"; "These webpages are rendered from GitHub repository and contain all the information about the GFTS project. This includes internal description of the use case, technical documentation, progress, presentations, etc."; "WebSite"; ; "GFTS Use case project website"; "2024-03-13 08:45:35.825465+00:00" . a . a , , ; ; "https://doi.org/10.5281/zenodo.10372387"; ; "2023-12-13 20:50:53.907411+00:00"; "2024-08-12 19:50:17.291963+00:00"; "Slides presented by Mathieu Woillez at the Roadshow Webinar: DestinE in action – meet the first DESP use cases (13 December 2023)"; ; "Global Fish Tracking System - DESP Use Case"; "2023-12-13 20:50:53.907411+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.10809819"; ; "2024-03-12 15:34:59.645366+00:00"; "2024-08-12 19:50:18.034736+00:00"; "Poster presented at the 8th InternationalBio-logging Science Symposium by Tina Odaka, March 2024."; "BSL8"; ; "Leveraging Pangeo to Geolocate Fish Using Biologging Data: The Pangeo-Fish Initiative"; "2024-03-12 15:34:59.645366+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11185948"; ; "2024-05-13 14:46:37.545543+00:00"; "2024-08-12 19:50:27.882827+00:00"; "Project Management Plan for the Global fish Tracking System Use Case on the DestinE Platform."; ; "Deliverable 5.1 - Project Management Plan for GFTS Use Case Application"; "2024-05-13 14:46:37.545543+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186084"; ; "2024-05-13 14:52:05.526290+00:00"; "2024-08-12 19:50:21.743081+00:00"; "Deliverable 5.2 - Use Case Descriptor for the Global fish Tracking System Use Case on the DestinE Platform."; ; "Deliverable 5.2 - Use Case Descriptor for GFTS Use Case Application"; "2024-05-13 14:52:05.526290+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186123"; ; "2024-05-13 14:53:36.574750+00:00"; "2024-08-12 19:50:20.705135+00:00"; "The Gobal Fish track system Use case Application on the DestinE Platform"; ; "Deliverable 5.3 - GFTS Use case Application"; "2024-05-13 14:53:36.574750+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186179"; ; "2024-05-13 14:54:51.494324+00:00"; "2024-08-12 19:50:17.564291+00:00"; "Deliverable 5.5 corresponding to the Global Fish tracking System Use Case Promotion Package"; ; "Deliverable 5.5 - GFTS Use Case Promotion Package"; "2024-05-13 14:54:51.494324+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186191"; ; "2024-05-13 14:56:18.168828+00:00"; "2024-08-12 19:50:26.999845+00:00"; "This report corresponds to the Software Reuse File for the GFTS DestinE Platform Use Case. New version will be uploaded regularly."; ; "Software Reuse File for the GFTS DestinE Platform Use Case"; "2024-05-13 14:56:18.168828+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186227"; ; "2024-05-13 14:57:17.755650+00:00"; "2024-08-12 19:50:15.236431+00:00"; "The Software Release Plan for the Global Fish Tracking System DestinE Use Case."; ; "GFTS Software Release Plan"; "2024-05-13 14:57:17.755650+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186257"; ; "2024-05-13 14:58:42.259068+00:00"; "2024-08-12 19:50:18.592163+00:00"; "The Software Requirement Specifications for the Global fish Tracking System DestinE Use Case."; ; "GFTS Software Requirement Specifications"; "2024-05-13 14:58:42.259068+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186288"; ; "2024-05-13 15:02:41.488702+00:00"; "2024-08-12 19:50:12.780989+00:00"; "The Software Verification and Validation Plan for the Global fish Tracking System DestinE Use Case."; ; "GFTS Software Verification and Validation Plan"; "2024-05-13 15:02:41.488702+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186318"; ; "2024-05-13 15:04:39.257557+00:00"; "2024-08-12 19:50:19.449409+00:00"; "The Software Verification and Validation Report from the Global Fish Tracking System DestinE Use Case."; ; "GFTS Software Verification and Validation Report"; "2024-05-13 15:04:39.257557+00:00" . a , , ; ; "https://gfts.minrk.net/"; ; "2024-04-03 08:56:53.930425+00:00"; "2024-08-12 19:50:18.317893+00:00"; "Link to the Pangeo JupyterHub we are using for developing Pangeo Fish. 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"Climate Stripes"; "datasets/ts_cities.csv_31e7840b5aedca433fb349714141a239.tabular"; "datasets/stripes.png_31e7840b5aedca43c0a4f330c3d24460.png"; "2025-05-23T17:37:48.953745"; "workflows/f1ada1d68e850ab0.gxwf.yml" . a ; "Galaxy workflow engine" . a ; "File"; ""; "stripes.png" . a ; "2025-05-24T11:15:49.407239"; "Run of Galaxy workflow engine"; "2025-05-24T11:15:41.585048"; "#df271e0b-a648-4bff-95d4-739be6c1c6b4" . a ; ; "Galaxy"; . a ; "CWL"; ; "Common Workflow Language"; . a . a , , ; dct:conformsTo , , ; "10.24424/9cee-cz89"; "False"; ; "2025-05-24 13:39:23.468184+00:00"; ; ; 0; "https://api.rohub.org/api/ros/d5430aa5-7a8b-44fe-8d21-6a7c80ac36d4/crate/download/"; ; "2025-05-24 11:31:11+00:00"; "2025-10-16 11:38:20.704323+00:00"; "2025-05-24 11:31:11+00:00"; """# Galaxy Workflow Rerun Information **Workflow:** Climate Stripes **Execution Status:** scheduled **Executed:** 2025-05-24 11:15:41.585048 ## Workflow Inputs ### Formal Input Definitions - **ts_cities.csv** (File) ### Actual Input Files Used - **ts_cities.csv** - Format: `text/plain` - Path: `datasets/ts_cities.csv_31e7840b5aedca433fb349714141a239.tabular` ## Workflow Parameters - **input:** - __class__: `NoReplacement` - **adv:** - colormap: `RdBu_r` - format_date: `` - format_plot: `` - nxsplit: `None` - xname: `` - **ifilename:** - __class__: `ConnectedValue` - **title:** `My ScienceLive Stripes` - **variable:** `tg_anomalies_freiburg` ## Workflow Outputs ### Formal Output Definitions - **stripes.png** (File) ### Actual Output Files Generated - **stripes.png** - Format: `application/octet-stream` - Path: `datasets/stripes.png_31e7840b5aedca43c0a4f330c3d24460.png` ## Rerun Template To rerun this workflow: 1. **Workflow:** Climate Stripes 2. **Required inputs:** - ts_cities.csv (type: `File`) 3. **Parameters to set:** - input: - __class__: `NoReplacement` - adv: - colormap: `RdBu_r` - format_date: `` - format_plot: `` - nxsplit: `None` - xname: `` - ifilename: - __class__: `ConnectedValue` - title: `My ScienceLive Stripes` - variable: `tg_anomalies_freiburg` 4. **Expected outputs:** - stripes.png (type: `File`)"""; 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In contrast to compounds that exhibit aromaticity, aliphatic compounds lack this delocalization. The term \"aromatic\" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. Aromatic hydrocarbons, or arenes, are aromatic organic compounds containing solely carbon and hydrogen atoms. The configuration of six carbon atoms in aromatic compounds is called a \"benzene ring\", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. Not all aromatic compounds are benzene-based; aromaticity can also manifest in heteroarenes, which follow Hückel's rule (for monocyclic rings: when the number of its π electrons equals 4n + 2, where n = 0, 1, 2, 3, ...). 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Nov 08 ,2021. https://doi.org/10.24424/1k12-x394." . a , ; "ICHB-PAS" . a ; "Jose Perez" . a , ; "PSNC" . a , ; ; 73394; "https://api.rohub.org/api/resources/1f611f7e-a4b7-45de-be8e-d6f0e39d2fde/download/"; ; "2021-11-08 16:30:06.553639+00:00"; "2021-11-08 17:06:22.592157+00:00"; "image/png"; ; "flow-dcro.png"; "2021-11-08 16:30:06.553639+00:00" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental."""; "EU_CAMS_SURFACE_PM10_G" . a , ; "Flow to compute monthly map" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a ; dct:conformsTo ; . a ; "research object"; "83.11557788944724"; "82.7" . a ; "map"; "17.05639614855571"; "12.4" . a ; "PM10"; "13.541666666666666"; "13.0" . a ; "Copernicus Atmosphere Monitoring Service"; "8.229166666666666"; "7.9" . a ; "object"; 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Nov 09 ,2021. https://doi.org/10.24424/zt8j-c157." . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; ; "https://zenodo.org/record/5554786#.YYlWo9nMI-Q"; ; "2021-11-09 15:52:03.894247+00:00"; "2021-11-10 19:38:07.510465+00:00"; ; "https://zenodo.org/record/5554786#.YYlWo9nMI-Q"; "2021-11-09 15:52:03.894247+00:00" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. 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Dec 08 ,2021. https://doi.org/10.24424/fehe-jb26." . a , ; "metadata" . a , ; "data" . a , ; ; "biblio" . a , ; "raw data" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; ; "2021-12-08 21:44:49.477592+00:00"; "2021-12-08 22:01:19.894769+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; "2021-12-08 21:44:49.477592+00:00" . a , ; "Flow to compute monthly map" . a , ; ; 73394; "https://api.rohub.org/api/resources/25e31ee1-9f77-40d0-a4c3-5bef88b9adc3/download/"; ; "2021-12-08 21:44:36.949407+00:00"; "2021-12-08 22:01:19.428175+00:00"; "image/png"; ; "flow-dcro.png"; "2021-12-08 21:44:36.949407+00:00" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental."""; "EU_CAMS_SURFACE_PM10_G" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; ; "2021-12-08 21:44:42.801819+00:00"; "2021-12-08 22:01:19.788776+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; "2021-12-08 21:44:42.801819+00:00" . a , ; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; ; "2021-12-08 21:44:46.533341+00:00"; "2021-12-08 22:01:20.217111+00:00"; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; "2021-12-08 21:44:46.533341+00:00" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; "Catch data records sample from 2019"; "Catch data from Norway" . a , ; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; ; "2021-12-08 21:44:52.711669+00:00"; "2023-05-16 16:52:12.400121+00:00"; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; "2021-12-08 21:44:52.711669+00:00" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; ; "2021-12-08 21:44:55.989277+00:00"; "2021-12-08 22:01:19.992473+00:00"; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; "2021-12-08 21:44:55.989277+00:00" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a ; dct:conformsTo ; . a , , , ; "Nordic e-Infrastructure Collaboration (NeIC)", "Nordic e-Infrastructure Collaboration (NeIC)", "Nordic e-Infrastructure Collaboration (NeIC)", "Nordic e-Infrastructure Collaboration (NeIC)"; "annefou@geo.uio.no", "annefou@geo.uio.no", "annefou@geo.uio.no", "annefou@geo.uio.no"; "Anne Fouilloux", "Anne Fouilloux", "Anne Fouilloux", "Anne Fouilloux" . a , ; "neworg1@example.org", "neworg1@example.org"; "abcd123", "abcd123"; "Example Org 1", "Example Org 1" . a , ; "published v2", "published v2" . a ; "38.0"; "38.0"; "POINT (38.0 38.0)" . a ; ; "6aa2b88b-ca50-4d9b-81fb-b18cf3b25d74"; "POINT (38.0 38.0)" . a ; "service-account-enrichment" . a , , , , ; "False"; "https://w3id.org/ro-id/9177a694-e747-4d7f-ae7e-87672850e0ec"; "2021-12-08 22:04:49.342182+00:00"; "mailto:rpalma@man.poznan.pl"; ; , ; ; 86622; "https://api.rohub.org/api/ros/c737f695-6715-4916-8bef-8fc0ce879760/crate/download/"; ; ; ; "2021-12-08 21:40:02.447472+00:00"; "2024-03-05 12:17:25.629746+00:00"; "2021-12-08 21:40:02.447472+00:00"; "This Research Object demonstrate how to compute monthly map of PM10 over your country - modified"; "application/ld+json"; , , , , , , , , ; "https://w3id.org/ro-id/c737f695-6715-4916-8bef-8fc0ce879760"; ; "8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot", "Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v2"; ; "MANUAL"; "https://w3id.org/ro-id/c737f695-6715-4916-8bef-8fc0ce879760/df4db37c-7304-430d-b08e-ba41cdc33e9e"; "Anne Foilloux, Nieves Pepito, and Pepito Bato. \"Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v2.\" ROHub. Dec 08 ,2021. http://doi.org/10.23728/b2share.3c82435c669b49fcaa5541b465e055fa." . a , ; ; "biblio" . a , ; "data" . a , ; "raw data" . a , ; "metadata" . a , ; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; ; "2021-12-08 21:44:55.989277+00:00"; "2021-12-08 22:04:44.732746+00:00"; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; "2021-12-08 21:44:55.989277+00:00" . a , ; "Flow to compute monthly map" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; ; "2021-12-08 21:44:42.801819+00:00"; "2021-12-08 22:04:44.543287+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; "2021-12-08 21:44:42.801819+00:00" . a , ; ; 73394; "https://api.rohub.org/api/resources/287efd15-0bd1-474d-88c2-4542e1393d8d/download/"; ; "2021-12-08 21:44:36.949407+00:00"; "2021-12-08 22:04:44.160524+00:00"; "image/png"; ; "flow-dcro.png"; "2021-12-08 21:44:36.949407+00:00" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental."""; "EU_CAMS_SURFACE_PM10_G" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; ; "2021-12-08 21:44:52.711669+00:00"; "2023-05-16 16:53:21.645987+00:00"; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; "2021-12-08 21:44:52.711669+00:00" . a , ; "Catch data records sample from 2019"; "Catch data from Norway" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; ; "2021-12-08 21:44:46.533341+00:00"; "2021-12-08 22:04:44.869071+00:00"; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; "2021-12-08 21:44:46.533341+00:00" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; ; "2021-12-08 21:44:49.477592+00:00"; "2021-12-08 22:04:44.654574+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; "2021-12-08 21:44:49.477592+00:00" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a ; dct:conformsTo ; . a , ; "10.13039/501100000781", "10.13039/501100000781"; "European Commission", "European Commission" . a , ; , ; "101017502", "101017502"; "RELIANCE", "RELIANCE"; "Research Lifecycle Management for Earth Science Communities and Copernicus Users", "Research Lifecycle Management for Earth Science Communities and Copernicus Users" . a , , , ; "POINT (38.0 38.0)", "POINT (38.0 38.0)" . a , . a ; ; "0a113f7e-5c4d-411e-985e-2d71e8dcbd28"; "POINT (38.0 38.0)" . a ; "38.0"; "38.0"; "POINT (38.0 38.0)" . a ; "service-account-enrichment" . a , , , , ; "False"; "https://w3id.org/ro-id/93ece8d0-3be4-4658-a840-156bda47f612"; "2021-12-09 15:19:11.307501+00:00"; "mailto:rpalma@man.poznan.pl"; ; , ; ; 87394; "https://api.rohub.org/api/ros/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c/crate/download/"; ; ; ; "2021-12-09 15:05:57.255344+00:00"; "2024-03-05 12:17:25.978567+00:00"; "2021-12-09 15:05:57.255344+00:00"; "This Research Object demonstrate how to compute monthly map of PM10 over your country - modified"; "application/ld+json"; ; ; , , , , , , , , ; "https://w3id.org/ro-id/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c"; ; "8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot", "Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v1"; ; "MANUAL"; "https://w3id.org/ro-id/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c/ea782618-0dff-4cfa-8604-e121ce29d3cf"; "Anne Foilloux, Nieves Pepito, and Pepito Bato. \"Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v1.\" ROHub. Dec 09 ,2021. https://doi.org/10.24424/w44h-8089." . a , ; "metadata" . a , ; "data" . a , ; ; "biblio" . a , ; "raw data" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; ; "2021-12-09 15:07:51.036076+00:00"; "2021-12-09 15:19:08.564064+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; "2021-12-09 15:07:51.036076+00:00" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; ; "2021-12-09 15:07:43.448712+00:00"; "2021-12-09 15:19:08.515865+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; "2021-12-09 15:07:43.448712+00:00" . a , ; "Flow to compute monthly map" . a , ; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; ; "2021-12-09 15:07:55.588569+00:00"; "2023-05-16 16:54:04.603729+00:00"; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; "2021-12-09 15:07:55.588569+00:00" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; ; 73394; "https://api.rohub.org/api/resources/7733e68b-7b14-45b8-96ef-b0ff1e3b6a45/download/"; ; "2021-12-09 15:07:22.892363+00:00"; "2021-12-09 15:19:08.338406+00:00"; "image/png"; ; "flow-dcro.png"; "2021-12-09 15:07:22.892363+00:00" . a , ; "Catch data records sample from 2019"; "Catch data from Norway" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental."""; "EU_CAMS_SURFACE_PM10_G" . a , ; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; ; "2021-12-09 15:07:47.272247+00:00"; "2021-12-09 15:19:08.713366+00:00"; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; "2021-12-09 15:07:47.272247+00:00" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a , ; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; ; "2021-12-09 15:07:59.055468+00:00"; "2021-12-09 15:19:08.607528+00:00"; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; "2021-12-09 15:07:59.055468+00:00" . a ; dct:conformsTo ; . a , ; "neworg2@example.org", "neworg2@example.org"; "abcd123", "abcd123"; "Example Org 2", "Example Org 2" . a ; "38.0"; "38.0"; "POINT (38.0 38.0)" . a ; ; "86a33d62-4541-495f-a640-2b60e0394266"; "POINT (38.0 38.0)" . a ; "service-account-enrichment" . a , , , , ; "False"; "https://w3id.org/ro-id/93ece8d0-3be4-4658-a840-156bda47f612"; "2021-12-09 15:20:23.441762+00:00"; "mailto:rpalma@man.poznan.pl"; ; , ; ; 87383; "https://api.rohub.org/api/ros/57cf76e1-2179-4650-b48b-b5990dca86c1/crate/download/"; ; ; ; "2021-12-09 15:05:57.255344+00:00"; "2024-03-05 12:17:26.248043+00:00"; "2021-12-09 15:05:57.255344+00:00"; "This Research Object demonstrate how to compute monthly map of PM10 over your country - modified"; "application/ld+json"; ; ; , , , , , , , , ; "https://w3id.org/ro-id/57cf76e1-2179-4650-b48b-b5990dca86c1"; ; "8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot", "Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2"; ; "MANUAL"; "https://w3id.org/ro-id/57cf76e1-2179-4650-b48b-b5990dca86c1/ea782618-0dff-4cfa-8604-e121ce29d3cf"; "Anne Foilloux, Nieves Pepito, and Pepito Bato. \"Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2.\" ROHub. Dec 09 ,2021. https://doi.org/10.24424/yptf-km76." . a , ; ; "biblio" . a , ; "metadata" . a , ; "raw data" . a , ; "data" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; ; "2021-12-09 15:07:51.036076+00:00"; "2021-12-09 15:20:20.634446+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01"; "2021-12-09 15:07:51.036076+00:00" . a , ; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; ; "2021-12-09 15:07:47.272247+00:00"; "2021-12-09 15:20:20.738000+00:00"; ; "https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff"; "2021-12-09 15:07:47.272247+00:00" . a , ; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; ; "2021-12-09 15:07:43.448712+00:00"; "2021-12-09 15:20:20.597858+00:00"; ; "https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G"; "2021-12-09 15:07:43.448712+00:00" . a , ; "Flow to compute monthly map" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; ; "2021-12-09 15:07:59.055468+00:00"; "2021-12-09 15:20:20.669306+00:00"; ; "https://box.psnc.pl/f/d90a0e1e0d/?raw=1"; "2021-12-09 15:07:59.055468+00:00" . a , ; ; 73394; "https://api.rohub.org/api/resources/7bfd4974-4bf8-4922-ae40-36a2ca9ef7fe/download/"; ; "2021-12-09 15:07:22.892363+00:00"; "2021-12-09 15:20:20.444066+00:00"; "image/png"; ; "flow-dcro.png"; "2021-12-09 15:07:22.892363+00:00" . a , ; "Catch data records sample from 2019"; "Catch data from Norway" . a , ; """This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental."""; "EU_CAMS_SURFACE_PM10_G" . a , ; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; ; "2021-12-09 15:07:55.588569+00:00"; "2023-05-16 16:54:33.185954+00:00"; ; "https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb"; "2021-12-09 15:07:55.588569+00:00" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a ; dct:conformsTo ; .