{"count":8489,"next":"https://metax.fairdata.fi/v3/datasets?format=json&limit=20&offset=1520","previous":"https://metax.fairdata.fi/v3/datasets?format=json&limit=20&offset=1480","results":[{"id":"cc3b43ff-7cee-41a4-980e-84560c6ab26f","access_rights":{"id":"07ba3e38-9c9b-4f8a-a8d9-580c0a42508c","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"ded254e1-afa9-4870-92bb-930958aec78f","roles":["creator"],"person":{"id":"5d514e5f-63d8-45b6-8dce-809da13c27b5","name":"Laura Uusitalo","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"3c5a13d5-89a3-448d-919f-56fcd8863745","roles":["creator"],"person":{"id":"e747fcf8-10e8-4ff0-87a8-39f80e1cd13b","name":"Maiju Lehtiniemi","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"a8e3ca1e-c186-4f2b-a010-0c8e0314099a","roles":["creator"],"person":{"id":"60272cf4-2b08-44a9-9780-ec2b709590f8","name":"Siru Tasala","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"97657b97-c254-4327-a796-ea336cbf27d7","roles":["creator"],"person":{"id":"3e980bf3-81ac-4e6c-8188-cebd131d89ad","name":"Jose Fernandez"},"organization":{"id":"17a21a65-9ba8-456a-8952-37dea2f9b255","pref_label":{"fi":"AZTI"}}},{"id":"8247d00d-480e-40ea-a0c5-f6b464a992d4","roles":["creator"],"person":{"id":"5642b753-4109-4091-bb7a-5b370a691144","name":"Eneko Bachiller"},"organization":{"id":"a3b25265-fe70-44da-903f-54e6545db0e0","pref_label":{"fi":"IMR Norway"}}},{"id":"765066ef-9bf4-456a-9455-eda6c54de549","roles":["publisher","rights_holder"],"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"A small training set for ZooImage program: scanned zooplankton images, grouped into taxonomic / functional groups. The zooplankton have been collected as part of the COMBINE monitoring programme in the open sea areas of the Gulf of Finland. \n\nAn article based on the data is published and can be found at https://doi.org/10.1016/j.ecolind.2016.05.036\n\nData processing steps: sampling\n\nDescription: The samples were collected in August from the surface layer,\nduring regular monitoring cruises on R/V Aranda from the Gulf\nof Finland, northern Baltic Sea, using a vertically towed\n100 micro-m mesh sized WP-2 closing plankton net (Hydrobios, Kiel,\nGermany). Samples were preserved immediately after collection\nwith 4% formaldehyde solution (Harris et al., 2000) until analysis\nin the laboratory.\n\nData processing steps: processing\n\nDescription: Before scanning, samples were dyed overnight\nusing eosin to enhance contrast (Harris et al., 2000) and applied\nthinly, so that the zooplankton individuals were mostly separate\nfrom each other on a clear, transparent plastic tray (the lid of a\nPCR plate). Sixteen samples were scanned two at the time using an\nEpson PerfectionV750 scanner at 2800 dpi resolution,meaning that\nthe length of 1 mm includes approximately 110 pixels in the image.\nThe pictures (examples in Fig. 2) were scanned as colour pictures\nand analysed using colour picture algorithm. For the training set,\n81 subsamples were scanned, and a total of 1446 scanned images\n(zooplankton individuals and inanimate objects) of were included."},"field_of_science":[],"infrastructure":[],"issued":"2018-02-12","keyword":["Baltic Sea","zooplankton","plankton","images","ZooImage"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"0751fc28-f99a-4591-ab44-7ffc7deb9337","organization":"syke.fi","admin_organization":"syke.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-3e2d32f8-a678-37e8-8e52-52a7f829ef25","pid_generated_by_fairdata":true,"projects":[{"id":"a4376f26-1d20-49fb-b225-65485f6848a8","title":{"en":"MARMONI - Innovative approaches for marine biodiversity monitoring and assessment of conservation status of nature values in the Baltic Sea; DEVOTES - DEVelopment Of innovative Tools for understanding marine biodiversity and assessing Good Environmental Status"},"participating_organizations":[{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}],"funding":[{"funder":{"funder_type":{"id":"6be2b361-67b7-429f-9365-58229de639f2","url":"http://uri.suomi.fi/codelist/fairdata/funder_type/code/eu-framework-programme","in_scheme":"http://uri.suomi.fi/codelist/fairdata/funder_type","pref_label":{"en":"EU Framework Programme","fi":"EU puiteohjelmat"}}},"funding_identifier":"Project Nr. LIFE09 NAT/LV/000238; Grant Agreement No. 308392"}]}],"provenance":[],"relation":[{"entity":{"title":{"en":"Uusitalo, Fernandes, Bachiller, Tasala, Lehtiniemi: Semi-automated classification method addressing marine strategy framework directive (MSFD) zooplankton indicators","fi":"Uusitalo, Fernandes, Bachiller, Tasala, Lehtiniemi: Semi-automated classification method addressing marine strategy framework directive (MSFD) zooplankton indicators"},"entity_identifier":"https://doi.org/10.1016/j.ecolind.2016.05.036","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]}],"remote_resources":[],"spatial":[],"state":"published","temporal":[{"start_date":"2012-08-01","end_date":"2012-08-30"}],"theme":[],"title":{"en":"ZooImage training set, northern Baltic zooplankton"},"created":"2026-03-12T10:27:09Z","modified":"2026-04-23T08:50:22Z","dataset_versions":[{"id":"cc3b43ff-7cee-41a4-980e-84560c6ab26f","title":{"en":"ZooImage training set, northern Baltic zooplankton"},"persistent_identifier":"doi:10.23729/fd-3e2d32f8-a678-37e8-8e52-52a7f829ef25","state":"published","created":"2026-03-12T10:27:09Z","version":1}],"published_revision":4,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-03-12T10:27:09Z","record_modified":"2026-04-23T08:50:22Z"},{"id":"f924209d-8271-4592-951e-9abdec9a4686","access_rights":{"id":"5f1a7c5a-cd67-490c-9374-23efcbd579b2","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"43720e8a-af93-458f-af21-3c6f16ea1d47","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/embargo","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Embargo","fi":"Embargo"}},"restriction_grounds":[{"id":"484e859f-11b5-4163-a387-25c13fcaae29","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/research","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restriced access for research based on contract","fi":"Saatavuutta rajoitettu sopimuksen perusteella vain tutkimuskäyttöön","sv":"Begränsad åtkomst på bas av kontrakt ändast för forskningsändamål"}}],"available":"2026-08-31","show_file_metadata":false},"actors":[{"id":"9daa8d53-93c1-43e2-9958-8eb9271a7236","roles":["publisher","creator"],"person":{"id":"c0cb7270-c649-4199-b033-377397988d30","name":"Eduardo Maeda","email":""},"organization":{"id":"b65efb2c-fd48-4b76-9837-c6f05216d4bd","pref_label":{"en":"University of Helsinki","fi":"Helsingin yliopisto","sv":"Helsingfors universitet","und":"Helsingin yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01901","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"4aae21e3-c028-45b2-a6b9-7631c07463b6","roles":["creator"],"person":{"id":"e8e1df6d-8c5f-4a62-9f60-66be9c6782ba","name":"Eleanor Downie"},"organization":{"id":"b65efb2c-fd48-4b76-9837-c6f05216d4bd","pref_label":{"en":"University of Helsinki","fi":"Helsingin yliopisto","sv":"Helsingfors universitet","und":"Helsingin yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01901","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"This repository contains data and scripts used for the analysis and figure creation in the paper. All R scripts in this directory are designed to run seamlessly if the working directory is set to the same location where the scripts are stored. You can easily set the working directory in R by right-clicking on the script file and selecting “Set As Working Directory.” The data is split into 4 main folders:\n\n1.\tBiomass – Contains the script and data used to produce the biomass figure (Figure 2) including the AnalyzeBiomass.R script and an example FORMIND parametrisation and output results before any fragmentation parameters were applied.\n\n2.\tLiDAR Forest Stand - Holds the script and data for visualizing voxel forests at different growth stages, with an example of the parameterisation files and results for pre- and post-fragmentation simulations.\n\n3.\tNLME - Includes scripts for creating and plotting non-linear mixed models (NLME) of the forest structural metrics from both FORMIND and TLS datasets, as used in Figures 10-12.\n\n4.\tVertical Profiles - Contains scripts and data for generating vertical profiles from various FORMIND parameterizations, corresponding to Figures 5, 7, and 9."},"field_of_science":[{"id":"7334f2e9-1aae-4b87-9088-8226211b06c9","url":"http://www.yso.fi/onto/okm-tieteenala/ta1171","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Geosciences","fi":"Geotieteet","sv":"Geovetenskaper"}},{"id":"99add68c-0c1f-4248-ad68-d0b57d89c984","url":"http://www.yso.fi/onto/okm-tieteenala/ta1172","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Environmental sciences","fi":"Ympäristötiede","sv":"Miljövetenskap"}}],"fileset":{"storage_service":"ida","csc_project":"2001208","total_files_count":52,"total_files_size":3122129167},"infrastructure":[],"issued":"2026-04-22","keyword":["LiDAR","FORMIND","Forest fragmentation","Amazon","Tropical forests"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"368f4722-7d48-47a4-a071-f43877bddf04","organization":"helsinki.fi","admin_organization":"helsinki.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-660cd5cc-e8c0-3b4d-aad2-2840f1a12116","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Data and code for: Fragmented Amazonian forest structure modelling using FORMIND"},"created":"2026-04-22T13:23:20Z","modified":"2026-04-22T13:24:56Z","dataset_versions":[{"id":"f924209d-8271-4592-951e-9abdec9a4686","title":{"en":"Data and code for: Fragmented Amazonian forest structure modelling using FORMIND"},"persistent_identifier":"doi:10.23729/fd-660cd5cc-e8c0-3b4d-aad2-2840f1a12116","state":"published","created":"2026-04-22T13:23:20Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-22T13:23:20Z","record_modified":"2026-04-22T13:24:59Z"},{"id":"27a8bb20-820a-473d-a9f9-deba67579979","access_rights":{"id":"7c35a313-3272-45ee-b3d4-7541b1dac1d3","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"be4e4983-8321-48fd-8492-3905388eabdf","roles":["creator"],"person":{"id":"f2860cf3-97a6-44ba-a71c-0b84ae3e4755","name":"Tiina Markkanen","email":""},"organization":{"id":"524da5e3-4236-4009-985f-4c4c60fbb30a","pref_label":{"fi":"Finnish Meteorological Institute"}}},{"id":"d5e766a9-83da-41f5-bcd2-1698bb197765","roles":["creator"],"person":{"id":"77fe943a-963b-4e56-8ce7-1a19b89d7702","name":"Ismo Lahtinen"},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"64412109-2a52-47e6-b5b4-b85c20da0877","roles":["contributor"],"person":{"id":"6ba2663a-4ee0-44c2-bf12-2afb6c366f5f","name":"Kristin Böttcher","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"5d982476-ac56-4808-ad74-32c15a3cf8b7","roles":["publisher","rights_holder"],"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"fi":"The land ecosystem model JSBACH was used to produce annual values for key climate change indicators for the period 1981 to 2099. The climate change indicators were derived for all of mainland Finland and they include gross primary production (GPP), total ecosystem respiration (TER), net ecosystem exchange (NEE), and start, end and length of vegetation active period. The mean values are given for four time periods, a baseline (1981–2010) and for three scenario periods (2011–2040, 2041–2070, 2071–2099). Additionally changes from the baseline are given for the scenario periods.\nThe dataset contains simulations results for selected response variables of JSBACH model for 2 climate change scenarios (RCP4.5, 8.5) and 5 and 4 climate model inputs, respectively.\n\nProcessing\n\nPlant functional type distribution in JSBACH simulations for Finland is based on Finnish Corine land cover 2012 data and aggregated to a 0.1 x 0.1 degree geographic grid. Yearly values are calculated from daily model output and further averaged for thirty year periods.\n\nThe land surface model resolves plant functional type specific GPP, TER and NEE values for each grid cell within the model domain. Those are subsequently aggregated to grid cell specific values. Start and end of vegetation active period are estimated from GPP using an assumption that GPP of the active period exceeds 15% of the summertime GPP maximum. Agricultural plant functional types have been excluded from calculation of vegetation active period. Values for 30 year periods have further been interpolated to planar grid of resolution of 10km.\n\nhttps://www.climateguide.fi/articles/ecosystem-modelling\n\nJSBACH present day GPP estimates have been compared against PREBAS (PRELES) model for Finland in Peltoniemi et al (2015). The timing of spring events due to vegetation phenology in Finland has been assessed against satellite observations by Böttcher et al (2016). The ability of the model to estimate the drought risk of Finnish forest ecosystems have been assessed by Gao et al (2016).\n\nResources\n\nMaps of the climate change indicators and descriptive statistics for Finland or selected regions can be viewed in climateguide.fi under the section ‘Impacts of climate change’. The following indicators are available from JSBACH simulations: gross primary production (GPP), total ecosystem respiration (TER), net ecosystem exchange (NEE)and start, end and length of vegetation active period. The user can select maps showing the mean values for four time periods, a baseline (1981–2010) and for three scenario periods (2011–2040, 2041–2070, 2071–2100). Additionally changes from the baseline can be viewed for a given scenario period.\n\nhttps://www.climateguide.fi/articles/impact-scenarios-of-climate-change\n\nThe data can be accessed via a Web Feature Service (WFS) supporting versions 1.0.0 and 1.1.0. WFS services can be opened in various GIS applications, for example ArcGIS for Desktop and open source desktop application QGIS.\n\nTypically, the GIS applications loads data from a WFS service in a GML (Geography Markup Language) format. Additionally, the Monimet data can be loaded as zip compressed ESRI Shape files, a CSV file or a JSON file.\n\nThe service includes 6 feature types representing JSBACH simulations.\n\ntereco_grossphotosynthesisjsbach - Gross primary production, JSBACH model (gC/m2/a)\ntereco_netcarbonbalancejsbach - Net ecosystem exchange, JSBACH model (gC/m2/a)\ntereco_totalrespirationjsbach - Total ecosystem respiration rate TER, JSBACH model (gC/m2/a)\ntereco_vapendjsbach - End of vegetation active period, JSBACH model (day of year)\ntereco_vaplengthjsbach - Length of vegetation active period, JSBACH model (days)\ntereco_vapstartjsbach - Start of vegetation active period, JSBACH model (day of year)\n\nThe attributes of each feature type are labelled as [climateModel]_[emissionScenario]_[timePeriod]_0_[valueType].\n\nThere are five climate models.\n\ncanesm2bc - CanESM2\ncnrmcm5bc - CNRM-CM5\ngfdlcm3bc - GFDL-CM3\nhadgem2esbc - HadGEM2-ES\nmiroc5bc - MIROC5\n\nThere are three emission scenarios.\n\nrcp26 - RCP 2.6\nrcp45 - RCP 4.5\nrcp85 - RCP 8.5\n\nThe timePeriod includes the start year and the end year of the period respectively.\n\nThere are three options for valueType.\n\nrc - relative change\nac - absolute change\nav - value\n\nFor example, the attribute labeled as hadgem2es_rcp45_20712100_0_ac describes the climate model HadGEM2-ES, the emission scenario RCP 4.5, a time period from 2011 to 2040 and absolute changes.\n\nhttps://paikkatiedot.ymparisto.fi/geoserver/ilmo-climateguide/wms?request=getcapabilities\n\nMaps of the climate change indicators and descriptive statistics for Finland or selected regions can be viewed in climateguide.fi under the section ‘Impacts of climate change’. The following indicators are available from JSBACH simulations: gross primary production (GPP), total ecosystem respiration (TER), net ecosystem exchange (NEE)and start, end and length of vegetation active period. The user can select maps showing the mean values for four time periods, a baseline (1981–2010) and for three scenario periods (2011–2040, 2041–2070, 2071–2100). Additionally changes from the baseline can be viewed for a given scenario period.\n\nhttps://www.climateguide.fi/articles/impact-scenarios-of-climate-change"},"field_of_science":[],"infrastructure":[],"issued":"2024-05-13","keyword":["carbon","boreal","climate change","simulation","vegetation phenology"],"language":[],"metadata_owner":{"id":"6e85fc7a-2c61-45e3-8f96-3cc73065346b","organization":"syke.fi","admin_organization":"syke.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-18ac382c-d916-3564-8693-d880ff7b0595","pid_generated_by_fairdata":true,"projects":[{"id":"6daa3191-eef1-4f25-90ea-2ae866a29abc","title":{"en":"MONIMET"},"project_identifier":"LIFE07 ENV/FIN/000409","participating_organizations":[{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}],"funding":[]}],"provenance":[],"relation":[{"entity":{"title":{"en":"Böttcher, Markkanen, Thum, Aalto, Aurela, Reick, Kolari, Arslan, Pulliainen: Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations","fi":"Böttcher, Markkanen, Thum, Aalto, Aurela, Reick, Kolari, Arslan, Pulliainen: Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations"},"description":{"en":"The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.","fi":"The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.","und":"The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production."},"entity_identifier":"https://doi.org/10.3390/rs8070580","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]},{"entity":{"title":{"en":"Gao, Markkanen, Thum, Aurela, Lohila, Mammarella, Hagemann, Aalto: Assessing various drought indicators in representing drought in boreal forests in Finland","fi":"Gao, Markkanen, Thum, Aurela, Lohila, Mammarella, Hagemann, Aalto: Assessing various drought indicators in representing drought in boreal forests in Finland"},"description":{"en":"Abstract. Droughts can impact on forest functioning and production, and even lead to tree mortality. However, drought is an elusive phenomenon that is difficult to quantify and define universally. In this study, we assessed the performance of a set of indicators that have been used to describe drought conditions in the summer months (June, July, August) over a 30 year period (1981–2010) in Finland. Those indicators include the Standardized Precipitation Index (SPI), the Standardized Precipitation–Evapotranspiration Index (SPEI), the Soil Moisture Index (SMI) and the Soil Moisture Anomaly (SMA). Herein, regional soil moisture was produced by the land surface model JSBACH. While SPI, SPEI, and SMA show a degree of anomalies from the statistical means over a period, SMI is directly connected to plant available water and closely dependent on soil properties. Moreover, the buffering effect of soil moisture and the associated soil moisture memory can impact on the onset and duration of drought as indicated by the SMI and SMA, whereas SPI and SPEI are directly controlled by meteorological conditions. In particular, we investigated whether the SMI, SMA and SPEI are able to indicate the Extreme Drought affecting Forest health (EDF) in Finland. EDF thresholds for these indicators are suggested, based on the spatially representative statistics of forest health observations in the exceptional dry year 2006. Our results showed that SMI was the best indicator in capturing the spatial extent of forest damage induced by the extreme drought in 2006. In addition, the derived thresholds were applied to those indicators to capture EDF events over the summer months of the 30 year study period. The SPEI and SMA showed more frequent EDF events over the 30 year period, and typically described a higher fraction of influenced area than SMI. In general, the suggested EDF thresholds for those indicators may be used for the indication of EDF events in Finland or other boreal forests areas in the context of future climate scenarios. However, the results have to be interpreted carefully, with due consideration of their different properties and the complexity of drought. Our results would suggest that in order to take appropriate precautions to mitigate against possible forest losses, an integrated analysis of projected drought with drought indicators is recommended.","fi":"Abstract. Droughts can impact on forest functioning and production, and even lead to tree mortality. However, drought is an elusive phenomenon that is difficult to quantify and define universally. In this study, we assessed the performance of a set of indicators that have been used to describe drought conditions in the summer months (June, July, August) over a 30 year period (1981–2010) in Finland. Those indicators include the Standardized Precipitation Index (SPI), the Standardized Precipitation–Evapotranspiration Index (SPEI), the Soil Moisture Index (SMI) and the Soil Moisture Anomaly (SMA). Herein, regional soil moisture was produced by the land surface model JSBACH. While SPI, SPEI, and SMA show a degree of anomalies from the statistical means over a period, SMI is directly connected to plant available water and closely dependent on soil properties. Moreover, the buffering effect of soil moisture and the associated soil moisture memory can impact on the onset and duration of drought as indicated by the SMI and SMA, whereas SPI and SPEI are directly controlled by meteorological conditions. In particular, we investigated whether the SMI, SMA and SPEI are able to indicate the Extreme Drought affecting Forest health (EDF) in Finland. EDF thresholds for these indicators are suggested, based on the spatially representative statistics of forest health observations in the exceptional dry year 2006. Our results showed that SMI was the best indicator in capturing the spatial extent of forest damage induced by the extreme drought in 2006. In addition, the derived thresholds were applied to those indicators to capture EDF events over the summer months of the 30 year study period. The SPEI and SMA showed more frequent EDF events over the 30 year period, and typically described a higher fraction of influenced area than SMI. In general, the suggested EDF thresholds for those indicators may be used for the indication of EDF events in Finland or other boreal forests areas in the context of future climate scenarios. However, the results have to be interpreted carefully, with due consideration of their different properties and the complexity of drought. Our results would suggest that in order to take appropriate precautions to mitigate against possible forest losses, an integrated analysis of projected drought with drought indicators is recommended.","und":"Abstract. Droughts can impact on forest functioning and production, and even lead to tree mortality. However, drought is an elusive phenomenon that is difficult to quantify and define universally. In this study, we assessed the performance of a set of indicators that have been used to describe drought conditions in the summer months (June, July, August) over a 30 year period (1981–2010) in Finland. Those indicators include the Standardized Precipitation Index (SPI), the Standardized Precipitation–Evapotranspiration Index (SPEI), the Soil Moisture Index (SMI) and the Soil Moisture Anomaly (SMA). Herein, regional soil moisture was produced by the land surface model JSBACH. While SPI, SPEI, and SMA show a degree of anomalies from the statistical means over a period, SMI is directly connected to plant available water and closely dependent on soil properties. Moreover, the buffering effect of soil moisture and the associated soil moisture memory can impact on the onset and duration of drought as indicated by the SMI and SMA, whereas SPI and SPEI are directly controlled by meteorological conditions. In particular, we investigated whether the SMI, SMA and SPEI are able to indicate the Extreme Drought affecting Forest health (EDF) in Finland. EDF thresholds for these indicators are suggested, based on the spatially representative statistics of forest health observations in the exceptional dry year 2006. Our results showed that SMI was the best indicator in capturing the spatial extent of forest damage induced by the extreme drought in 2006. In addition, the derived thresholds were applied to those indicators to capture EDF events over the summer months of the 30 year study period. The SPEI and SMA showed more frequent EDF events over the 30 year period, and typically described a higher fraction of influenced area than SMI. In general, the suggested EDF thresholds for those indicators may be used for the indication of EDF events in Finland or other boreal forests areas in the context of future climate scenarios. However, the results have to be interpreted carefully, with due consideration of their different properties and the complexity of drought. Our results would suggest that in order to take appropriate precautions to mitigate against possible forest losses, an integrated analysis of projected drought with drought indicators is recommended."},"entity_identifier":"https://doi.org/10.5194/hessd-12-8091-2015","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]},{"entity":{"title":{"fi":"Peltoniemi M., Markkanen T., Härkönen S., Muukkonen P., Thum T., Aalto T. & Mäkelä A. , 2015: Consistent estimates of gross primary production of Finnish forests — comparison of estimates of two process models. Boreal Env. Res. 20: 196–212. Available from, www.borenv.net/BER/pdfs/ber20/ber20-196.pdf."},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}}],"remote_resources":[],"spatial":[],"state":"published","temporal":[{"start_date":"1981-01-01","end_date":"2099-12-31"}],"theme":[],"title":{"fi":"JSBACH simulation dataset in Climate Guide"},"created":"2026-03-12T11:17:03Z","modified":"2026-04-22T09:42:33Z","dataset_versions":[{"id":"27a8bb20-820a-473d-a9f9-deba67579979","title":{"fi":"JSBACH simulation dataset in Climate Guide"},"persistent_identifier":"doi:10.23729/fd-18ac382c-d916-3564-8693-d880ff7b0595","state":"published","created":"2026-03-12T11:17:03Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-03-12T11:17:03Z","record_modified":"2026-04-22T09:42:33Z"},{"id":"c19dc933-c2e2-4077-8642-20a532fc78e0","access_rights":{"id":"cdb8da16-a801-480a-918c-efe1116190f1","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"33e1ca5e-5061-4b6f-8896-11775b0f985e","roles":["creator"],"person":{"id":"7bf0deef-dcf7-4400-8e51-30114209f172","name":"Noora Veijalainen","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"719976e0-f8d4-4196-bb8f-7554d21f227b","roles":["creator"],"person":{"id":"800a7329-f0d1-471f-970f-958a8c78e52c","name":"Juho Jakkila"},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"47c4cf71-5a09-4921-a1d5-d2ad4941ad5a","roles":["publisher"],"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"Climate change affect water resources through shorter snow seasons, changed rainfall patterns and increased evaporation. This dataset includes water resources indicators related to the duration of the snow cover, water equivalent of snow, soil moisture deficit, evaporation, runoff and time of occurrence of the greatest runoff. Data are available on a regular 10 km x 10 km over Finland under current and future climate.\n\nData processing\n\n30-year average are shown on a regular 10 km x 10 km over Finland for the baseline period 1981-2010 and three future periods, 2010–2039, 2040–2069 and 2070–2099, under 20 climate scenarios selected from the CMIP5 ensemble: low emissions (RCP2.6), moderate emissions (RCP4.5), moderate-high emissions (RCP6.0) and high emissions (RCP8.5) simulated with 14 Global Climate Models (CCSM4, NorESM1-M, GISS-E2-H, MIROC5, HadGEM2-CC, HadGEM2-ES, GFDL-CM3, MIROC-ESM-CHEM, MIROC-ESM, MPI-ESM-MR, CESM1-BGC, GISS-E2-R, CESM1-CAM5, MRI-CGCM3).\n\nScenarios of variables related water resources have been produced with the Finnish Environment Institute's (Syke) Watershed Simulation and Forecasting System (WSFS) (Vehviläinen & Huttunen 2002). The WSFS is used to draft hydrological predictions and warn of floods in Finland (https://www.vesi.fi/). The most important part of the system is a runoff model that describes the hydrological cycle from precipitation to runoff using normal meteorological material as the starting information (Bergström 1976). The model covers the whole land area of Finland, a total of 390,000 km², including cross-boundary watersheds overrunning the border. The model operates on a watershed sub-division level and the area is divided to approximately 6,400 watershed sub-divisions. The model's input data include precipitation and temperature, while the modelled variables of hydrological cycle include snow accumulation and melting, soil moisture, evaporation, ground water, runoff and discharge and water levels of the main rivers and lakes. The following indicators are included:\nEvaporation sum (unit: mm)\nMaximum runoff (mm)\nSeasonal and annual total runoff (mm)\nSnow cover duration (days)\nMaximum Snow Water Equivalent (kg/m2)\nSoil moisture deficit (mm)\nSeasonal flood timing (percent of years)\n\nAdditional information: https://www.climateguide.fi/articles/finnish-environment-institutes-watershed-simulation-and-forecasting-system\n\nDetails of the analysis to construct this dataset are described in Veijalainen et al. (2019).\n\nData access\n\nhttps://paikkatiedot.ymparisto.fi/geoserver/ilmo-climateguide/wms?request=getcapabilities\n\nThe data can be accessed via a Web Feature Service (WFS) supporting versions 1.0.0 and 1.1.0. WFS services can be opened in various GIS applications, for example ArcGIS for Desktop and open source desktop application QGIS. Typically, the GIS applications loads data from a WFS service in a GML (Geography Markup Language) format. Additionally, the data can be loaded as zip compressed ESRI Shape files, a CSV file or a JSON file. The service includes 14 feature types representing WSFS simulations:\nhydro_landevaporation -- Evaporation sum (mm)\nhydro_runoffmaximumaverage – Maximum runoff (mm)\nhydro_runoffsumaverage_1 – winter (Dec-Feb) total runoff (mm)\nhydro_runoffsumaverage_2 – spring (Mar-May) total runoff (mm)\nhydro_runoffsumaverage_3 – summer (Jun-Aug) total runoff (mm)\nhydro_runoffsumaverage_4 – autumn (Sep-Nov) total runoff (mm)\nhydro_runoffsumaverage – annual total runoff (mm)\nhydro_snowcoverdays – Snow cover duration (days)\nhydro_snowwaterequivalent – Maximum Snow Water Equivalent (kg/m2)\nhydro_soilmoisturedeficit – Soil moisture deficit (mm)\nhydro_timingmaxrunoff_1 – Percentage of years with the maximum flood in winter (Dec-Feb) (percent of years)\nhydro_timingmaxrunoff_2 – Percentage of years with the maximum flood in spring (Mar-May) (percent of years)\nhydro_timingmaxrunoff_3 – Percentage of years with the maximum flood in summer (Jun-Aug) (percent of years)\nhydro_timingmaxrunoff_4 – Percentage of years with the maximum flood in autumn (Sep-Nov) (percent of years)\n\n\nThe attributes of each feature type are labelled as [climateModel]_[emissionScenario]_[timePeriod]_0_[valueType]. There are 14 climate models and four forcing (or emission) scenarios rcp26, rcp45, rcp60 and rcp85. The timePeriod includes the start year and the end year of the period. There are three options for valueType, absolute value “av”, absolute change “ac” and relative change “rc”. For example, the attribute labeled as mpiesmmr_rcp85_20702099_0_rc describes the climate model MPI-ES-MMR, the forcing scenario RCP8.5, the time period from 2070 to 2099 and relative change (expressed as %)."},"field_of_science":[],"infrastructure":[],"issued":"2024-04-10","keyword":["climate change","hydrology","indicator","snow","water"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"3ff46a79-6c0d-4044-af2b-f59e92e5fd54","organization":"syke.fi","admin_organization":"syke.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-23f05976-3b1f-30cd-906e-920ee55d00bd","pid_generated_by_fairdata":true,"projects":[{"id":"c928d5b5-86fb-4c0e-a722-68c0b52bc7e0","title":{"en":"EIFFEL"},"project_identifier":"Grant agreement 101003518","participating_organizations":[{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}],"funding":[{"funder":{"funder_type":{"id":"6be2b361-67b7-429f-9365-58229de639f2","url":"http://uri.suomi.fi/codelist/fairdata/funder_type/code/eu-framework-programme","in_scheme":"http://uri.suomi.fi/codelist/fairdata/funder_type","pref_label":{"en":"EU Framework Programme","fi":"EU puiteohjelmat"}}}}]}],"provenance":[],"relation":[{"entity":{"title":{"fi":"Vehviläinen, B. & Huttunen, M. 2002. The Finnish watershed simulation and forecasting system (WSFS). Publication of the 21st conference of Danube countries on the hydrological forecasting and hydrological bases of water management."},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}},{"entity":{"title":{"fi":"Bergström, S. (1976). Development and application of a conceptual runoff model for Scandinavian catchments.SMHI. Nr RH7. Norrköping."},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}},{"entity":{"title":{"en":"Veijalainen, Ahopelto, Marttunen, Jääskeläinen, Britschgi, Orvomaa, Belinskij, Keskinen: Severe Drought in Finland: Modeling Effects on Water Resources and Assessing Climate Change Impacts","fi":"Veijalainen, Ahopelto, Marttunen, Jääskeläinen, Britschgi, Orvomaa, Belinskij, Keskinen: Severe Drought in Finland: Modeling Effects on Water Resources and Assessing Climate Change Impacts"},"description":{"en":"Severe droughts cause substantial damage to different socio-economic sectors, and even Finland, which has abundant water resources, is not immune to their impacts. To assess the implications of a severe drought in Finland, we carried out a national scale drought impact analysis. Firstly, we simulated water levels and discharges during the severe drought of 1939–1942 (the reference drought) in present-day Finland with a hydrological model. Secondly, we estimated how climate change would alter droughts. Thirdly, we assessed the impact of drought on key water use sectors, with a focus on hydropower and water supply. The results indicate that the long-lasting reference drought caused the discharges to decrease at most by 80% compared to the average annual minimum discharges. The water levels generally fell to the lowest levels in the largest lakes in Central and South-Eastern Finland. Climate change scenarios project on average a small decrease in the lowest water levels during droughts. Severe drought would have a significant impact on water-related sectors, reducing water supply and hydropower production. In this way drought is a risk multiplier for the water–energy–food security nexus. We suggest that the resilience to droughts could be improved with region-specific drought management plans and by including droughts in existing regional preparedness exercises.","fi":"Severe droughts cause substantial damage to different socio-economic sectors, and even Finland, which has abundant water resources, is not immune to their impacts. To assess the implications of a severe drought in Finland, we carried out a national scale drought impact analysis. Firstly, we simulated water levels and discharges during the severe drought of 1939–1942 (the reference drought) in present-day Finland with a hydrological model. Secondly, we estimated how climate change would alter droughts. Thirdly, we assessed the impact of drought on key water use sectors, with a focus on hydropower and water supply. The results indicate that the long-lasting reference drought caused the discharges to decrease at most by 80% compared to the average annual minimum discharges. The water levels generally fell to the lowest levels in the largest lakes in Central and South-Eastern Finland. Climate change scenarios project on average a small decrease in the lowest water levels during droughts. Severe drought would have a significant impact on water-related sectors, reducing water supply and hydropower production. In this way drought is a risk multiplier for the water–energy–food security nexus. We suggest that the resilience to droughts could be improved with region-specific drought management plans and by including droughts in existing regional preparedness exercises.","und":"Severe droughts cause substantial damage to different socio-economic sectors, and even Finland, which has abundant water resources, is not immune to their impacts. To assess the implications of a severe drought in Finland, we carried out a national scale drought impact analysis. Firstly, we simulated water levels and discharges during the severe drought of 1939–1942 (the reference drought) in present-day Finland with a hydrological model. Secondly, we estimated how climate change would alter droughts. Thirdly, we assessed the impact of drought on key water use sectors, with a focus on hydropower and water supply. The results indicate that the long-lasting reference drought caused the discharges to decrease at most by 80% compared to the average annual minimum discharges. The water levels generally fell to the lowest levels in the largest lakes in Central and South-Eastern Finland. Climate change scenarios project on average a small decrease in the lowest water levels during droughts. Severe drought would have a significant impact on water-related sectors, reducing water supply and hydropower production. In this way drought is a risk multiplier for the water–energy–food security nexus. We suggest that the resilience to droughts could be improved with region-specific drought management plans and by including droughts in existing regional preparedness exercises."},"entity_identifier":"https://doi.org/10.3390/su11082450","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]}],"remote_resources":[],"spatial":[],"state":"published","temporal":[{"start_date":"1981-01-01","end_date":"2099-12-31"}],"theme":[],"title":{"en":"Water resource indicator dataset in Climate Guide"},"created":"2026-03-12T11:43:02Z","modified":"2026-04-21T15:39:23Z","dataset_versions":[{"id":"c19dc933-c2e2-4077-8642-20a532fc78e0","title":{"en":"Water resource indicator dataset in Climate Guide"},"persistent_identifier":"doi:10.23729/fd-23f05976-3b1f-30cd-906e-920ee55d00bd","state":"published","created":"2026-03-12T11:43:02Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-03-12T11:43:02Z","record_modified":"2026-04-21T15:39:24Z"},{"id":"5a31525e-a4bc-465e-8736-6288830b11b2","access_rights":{"id":"d750faa6-409e-4061-8c8e-220d1ddb5ebf","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"ca3f2e12-53f3-4edd-9064-584cda976035","roles":["creator"],"person":{"id":"1dc7db5f-ffb0-432c-b971-60a2d42800c5","name":"Niko Karvosenoja","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"ae88ffca-0bef-4c56-870a-1eb4df145941","roles":["creator"],"person":{"id":"7f58f08d-2ed5-4969-8ad2-4b6cef2ae16e","name":"Ville-Veikko Paunu","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"76278d6f-1644-4cac-a4e1-fe6f74477531","roles":["creator"],"person":{"id":"e889d344-8db1-4fdb-ac60-f6bad239ac1d","name":"Mikko Savolahti","email":""},"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"b76f4b2f-17b3-4c79-80c1-77aed9f51004","roles":["publisher","rights_holder"],"organization":{"id":"56addf29-2163-45c6-8e44-b3c0a3c604f5","pref_label":{"en":"Finnish Environment Institute","fi":"Suomen ympäristökeskus","sv":"Finlands miljöcentral","und":"Suomen ympäristökeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/7020017","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"Theme: Environment and Conservation\n\nThe dataset contains anthropogenic air pollution and greenhouse gas emissions from Finland for 2019 and 2030. The emissions are calculated with the Finnish Regional Emission Scenario (FRES) model developed at the Finnish Environment Institute. The pollutants included are PM10, PM2.5, PM1, BC, OC, NOx, SO2, CO, VOC, NH3, BaP, CO2, CO2bio, CH4 and N2O. CO2bio refers to biogenic CO2 emissions, e.g. wood combustion. The emissions are given separately for point sources on municipal level and area sources on 250 m x 250 m resolution. The point source emissions indicate the emissions from major energy production and industrial plants. They are calculated based on several year average emissions and are not the officially reported emissions. The area sources are aggregated to 8 sectors: traffic exhaust, traffic dust, machinery and off-road, small scale wood combustion, other small scale combustion, agriculture, peat production, and other area sources.\n\nData processing steps: processing\n\nThe emissions are calculated using the FRES-model. All annual emission estimates are calculated as a product of activity data (fuel use/mileage/land area etc.) and emission factors for a given pollutant or greenhouse gas. Some sources also include technologies for emission reduction. Historical and projected emissions are estimated in five-year intervals. The latest year for historical emissions is currently 2015.\n\nPoint sources:\nPoint sources are combustion/industrial plants with notable annual emissions. FRES model currently includes 400+ point sources. A combination of bottom-up and top-down approaches are used to calculate emissions from point sources. The locations of point sources are known, as well as some other data, such as capacity. Plant-specific emission factors are used for some important point sources and representative averages for others. Activity data like fuel use in each plant is not year-specific but represent the annual average in a given plant. Thus, the modelled and reported emissions from an individual plant are usually not quite congruent. However, total fuel use for a group of similar plants, like coal-fired power plants, is the same as reported that year. For most process industry sites emissions are not modelled, but the reported emissions are used.\n\nArea sources:\nArea sources are smaller sources of emissions, for which annual emissions are not reported by the actors. The most important area sources are traffic and mobile machinery, residential combustion and agriculture. A top-down approach is used to calculate emissions from area sources.\n\nActivity data:\nFuel combustion is the most common activity that produces emissions. Annual consumption of fuels in a given sector is taken from Energy table service by Statistics Finland (https://pxhopea2.stat.fi/sahkoiset_julkaisut/energia2018/start.htm). Other activities, such as mileage, animal numbers and various land use areas are also from Statistics Finland\n\nEmission factors:\nEmission factors of greenhouse gases from combustion sources are fuel-specific. Emission factors of air pollutants are based on various sources like literature, legislative emission levels, measurements and data reported by industrial operators. For traffic and mobile machinery, emission factors are taken from the international GAINS model, in which they are based on COPERT 4 emission calculation tool. For residential wood combustion, emission factors are mostly from measurements made in domestic campaigns. For point sources, emission factors are based on plant-specific technology, representative emission control legislation or reported emissions.\n\nScenarios and emission projections:\nThe FRES model is mostly a tool for integrated assessment of future emission scenarios. Scenarios are based on projections of activity data, foreseeable or agreed changes in legislation and political measures that influence emissions. Current 2030 projection is mostly based on the activities in the WAM scenario of the National Energy and Climate Strategy, published in 2017. It includes legislation that is agreed to enter into force by 2030, such as stricter emission levels for combustion plants and the Ecodesing directive that sets maximum levels for particulate emissions from most residential wood combustion appliances. The emission projection is explained in more detail in the National Air Pollution Control Programme 2030.\n\n\nReferences:\n\nDescription of the FRES model:\nKarvosenoja N. 2008. Emission scenario model for regional air pollution. Monographs of the Boreal Environment Research 32.\n\nEmissions from residential wood combustion:\nSavolahti, M., Karvosenoja, N., Tissari, J., Kupiainen, K., Sippula, O. & Jokiniemi, J. (2016). Black carbon and fine particle emissions in Finnish residential wood combustion: Emission projections, reduction measures and the impact of combustion practices. Atmospheric Environment. https://doi.org/10.1016/j.atmosenv.2016.06.023\n\nNational Air Pollution Control Programme 2030:\nMinistry of the Environment. National Air Pollution Control Programme 2030; Publications of the Ministry of Environment: Suomi, Finland, 2019. https://julkaisut.valtioneuvosto.fi/handle/10024/161467\n\n\nData processing steps: processing\n\nSpatial distribution of the area source emissions are based on several proxies. The main data sources for the proxies are Digiroad for roads and traffic volumes, The National Buildings and Dwellings Register for buildings data, and CORINE2012 for land use data. More information on the proxies can be found in the references below.\n\nPaunu V.-V., Karvosenoja N., Savolahti M., Kupiainen K. 2013. High quality spatial model for residential wood combustion emissions. 16th IUAPPA World Clean Air Congress, Cape Town, South Africa, 29 September - 4 October 2013. 4 pp. 11\n\nKarvosenoja N., et al. 2018. A high-resolution national emission inventory and dispersion modelling – Is population density a sufficient proxy variable? 36th International Technical Meetings (ITM) on Air Pollution Modelling and its Application, Ottawa, Canada, 14.05.2018 - 18.05.2018.\n\nResource content description: Modelling of air pollution emissions\nhttps://www.syke.fi/en/services/modeling/modelling-of-air-pollution-emissions"},"field_of_science":[],"infrastructure":[],"issued":"2020-03-16","keyword":["air pollution","emission","particles","PM","black carbon"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"0751fc28-f99a-4591-ab44-7ffc7deb9337","organization":"syke.fi","admin_organization":"syke.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-123096b0-2625-37ce-a306-7ad0d1879541","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Paunu V.-V., Karvosenoja N., Savolahti M., Kupiainen K. 2013. High quality spatial model for residential wood combustion emissions. 16th IUAPPA World Clean Air Congress, Cape Town, South Africa, 29 September - 4 October 2013. 4 pp. 11"},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}},{"entity":{"title":{"en":"Savolahti, Karvosenoja, Tissari, Kupiainen, Sippula, Jokiniemi: Black carbon and fine particle emissions in Finnish residential wood combustion: Emission projections, reduction measures and the impact of combustion practices","fi":"Savolahti, Karvosenoja, Tissari, Kupiainen, Sippula, Jokiniemi: Black carbon and fine particle emissions in Finnish residential wood combustion: Emission projections, reduction measures and the impact of combustion practices"},"entity_identifier":"https://doi.org/10.1016/j.atmosenv.2016.06.023","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]},{"entity":{"title":{"en":"Ministry of the Environment. National Air Pollution Control Programme 2030; Publications of the Ministry of Environment: Suomi, Finland, 2019"},"entity_identifier":"https://julkaisut.valtioneuvosto.fi/handle/10024/161467","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]},{"entity":{"title":{"en":"Paunu V.-V., Karvosenoja N., Savolahti M., Kupiainen K. 2013. High quality spatial model for residential wood combustion emissions. 16th IUAPPA World Clean Air Congress, Cape Town, South Africa, 29 September - 4 October 2013. 4 pp. 11"},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}},{"entity":{"title":{"en":"Karvosenoja N., et al. 2018. A high-resolution national emission inventory and dispersion modelling – Is population density a sufficient proxy variable? 36th International Technical Meetings (ITM) on Air Pollution Modelling and its Application, Ottawa, Canada, 14.05.2018 - 18.05.2018."},"type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}}},{"entity":{"title":{"en":"Karvosenoja N. 2008. Emission scenario model for regional air pollution. Monographs of the Boreal Environment Research 32"},"entity_identifier":"https://helda.helsinki.fi/handle/10138/39332?locale-attribute=en","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"d48aef1e-b6e1-46da-8f44-f4141b4b8d85","url":"http://purl.org/dc/terms/relation","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Relation","fi":"Liittyy"}},"metax_ids":[]}],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Finnish air pollution emission scenarios"},"created":"2026-03-12T11:04:46Z","modified":"2026-04-21T15:30:36Z","dataset_versions":[{"id":"5a31525e-a4bc-465e-8736-6288830b11b2","title":{"en":"Finnish air pollution emission scenarios"},"persistent_identifier":"doi:10.23729/fd-123096b0-2625-37ce-a306-7ad0d1879541","state":"published","created":"2026-03-12T11:04:46Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-03-12T11:04:46Z","record_modified":"2026-04-21T15:30:39Z"},{"id":"c4dabb35-1c26-4782-ae2f-e2bbd55020c4","access_rights":{"id":"ed915dbc-e032-4c86-908d-037f3772c60b","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"d030a5d3-84e0-4a55-886f-ae078bb46fb1","roles":["creator","publisher"],"person":{"id":"9d62c95c-4e03-44bb-a3b5-9e047251f63f","name":"Tua Nylén","email":"","external_identifier":"https://orcid.org/0000-0002-1261-7214"},"organization":{"id":"bcf1a45c-61c6-43b3-bc8b-b8f3cfa5326d","pref_label":{"en":"Maantiede","fi":"Maantiede","sv":"Maantiede","und":"Maantiede"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10089-2606901","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"6008d1d0-fee8-4efe-9832-74337b62ffa5","pref_label":{"en":"University of Turku","fi":"Turun yliopisto","sv":"Åbo universitet","und":"Turun yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10089","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"The Finland Coastal Change is a multi-temporal dataset of coastal land cover, shoreline position and shoreline displacement along the coast of Finland during 1985–2024.\n\nThe data were created applying the procedure of Nylén et al. (2025), with certain modifications to account for the characteristics of the study area. The procedure utilized the full Landsat collection in Google Earth Engine (namely, Landsat 5, Landsat 7, Landsat 8 and Landsat 9). Version v01 consists of data that haven't been fully validated in the field or against national datasets. The data quality is expected to correspond to that reported for the Arctic coast in Nylén et al. (2025). All data are in ETRS-TM35FIN coordinate reference system (EPSG:3067).\n\n*Data structure*\n\n*Coastal land cover time-series 1985–2024*\n\nThe coastal land cover files classify 30-meter pixels into land and water. Land cover is averaged over five-year time-steps, starting from 1985–1989 and ending in 2020–2024. The name of each of the eight raster image files indicates the start year of the time-step.\n\nEach raster image has one land cover band (\"landcover\"). The pixel values indicate following:\n\n- 1 = land\n- 2 = water\n- NA = less than five valid satellite image observations (no such pixels in the data) or outside the coastal zone\n\n*Shoreline time-series 1985–2024*\n\nVector data describing the historical location of the Finnish shoreline during each of the eight time-steps and calculated from the coastal land cover data. The geojson file name indicates the start year of the time-step. The linestring features have following attributes:\n\n- 'timestep': the start-year of the time-step\n- 'length_m': the length of the linestring feature in meters\n\n*Shoreline displacement rates 1985–2024*\n\nRates of shoreline displacement, calculated at shore-normal transects with a 500-meter spacing and stored at transect mid points (n = 35 696). The attributes of the point feature describe shoreline displacement from different perspectives using following widely used metrics (see USGS Digital Shoreline Analysis System DSAS, Henderson et al. 2026):\n\n- 'NSM': net shoreline movement (m), displacement between oldest and newest shoreline. Positive values indicate seaward displacement\n- 'SCE': shoreline change envelope (m), maximum distance among all historical shorelines\n- 'EPR': end-point-rate (m/year), displacement between first and last observation divided by the number of years. Positive values indicate seaward displacement\n- 'EPR_uncertainty': uncertainty of the end-point-rate (m)\n- 'LRR': linear regression rate (m/year), average displacement rate calculated by fitting a linear regression model to all observations. Positive values indicate seaward displacement. Calculated only for transects that intersect at least three shorelines\n- 'LRR_SE': standard error of the linear regression rate\n\nThe attributes also include:\n\n- 'shorelines': the number of shorelines intersected by the transect (up to 8)\n- 'timespan': the length of the time-series that is created by shorelines intersecting the transect (years, up to 35 years)\n\nThe original transects (with 500-meter spacing and two kilometers each) are also included in the dataset.\n\n*References*\n\nNylén, T., Calle, M., Gonzales-Inca, C. (2025). Unveiling coastal change across the Arctic with full Landsat collections and data fusion. Remote Sensing of Environment 322, 114696. https://doi.org/10.1016/j.rse.2025.114696.\n\nHenderson, R.E., Farris, A.S., Kratzmann, M.G., Bartlett, M.K., Ergul, A., McAndrews, J., Cibaj, R., Zichichi, J.L., Himmelstoss, E.A., Thieler, E.R. (2026). Digital Shoreline Analysis System version 6.1: U.S. Geological Survey software release. https://doi.org/10.5066/P1NHMJNC.","fi":"\"Finland Coastal Change\" on Suomen rannikon maanpeitteen ja rantaviivan sijainnin aikasarja ja rannansiirtymistä vuosina 1985–2024 kuvaava aineisto.\n\nAineisto tuotettiin soveltamalla Nylénin ym. (2025) kuvaamaa menetelmää tietyin muokkauksin, jotka huomioivat tutkimusalueen erityispiirteet. Menetelmä hyödynsi Google Earth Enginen koko Landsat-aineistoa (Landsat 5, Landsat 7, Landsat 8 ja Landsat 9). Version v01 aineistolle ei ole tehty validointia maastossa tai vertaamalla kansalliseen aineistoon. Tarkkuuden oletetaan vastaavan vähintään arktisen rannikon aineistolle raportoitua tarkkuutta (Nylén ym. 2025). Koko aineisto on ETRS-TM35FIN koordinaattijärjestelmässä (EPSG:3067).\n\n*Aineiston rakenne*\n\n*\"Coastal land cover time-series 1985–2024\" (rannikon maanpeiteaikasarja)*\n\nRannikon maanpeiteaineisto jakaa 30 metrin pikselit maaksi ja vedeksi. Aineisto edustaa keskimääräistä maanpeitettä viiden vuoden aika-askeleella (time-step), joista ensimmäinen on 1985–1989 ja viimeinen 2020–2024. Kunkin rasterikuvan tiedostonimi osoittaa aika-askeleen alkuvuoden.\n\nKukin rasterikuva koostuu yhdestä maanpeitettä kuvaavasta kanavasta (\"landcover\"). Pikselien arvot ovat:\n\n- 1 = maa\n- 2 = vesi\n- NA = alle viisi hyväksyttävää satelliittikuvahavaintoa (tässä aineistossa ei ole tällaisia pikseleitä) tai rantavyöhykkeen ulkopuolella\n\n*\"Shoreline time-series 1985–2024\" (rantaviiva-aikasarja)*\n\nVektoriaineisto, joka kuvaa Suomen rantaviivan historiallista sijaintia kullakin aika-askeleella, laskettuna rannikon maanpeiteaineistosta. Kunkin geojson-tiedoston nimi osoittaa aika-askeleen alkuvuoden. Viivakohteilla on seuraavat ominaisuustiedot:\n\n- 'timestep': aika-askeleen alkuvuosi\n- 'length_m': viivakohteen pituus metreinä\n\n*\"Shoreline displacement rates 1985–2024\" (rannansiirtymisnopeudet)*\n\nRannansiirtymisnopeudet on laskettu rantaviivan kohtisuoraan leikkaavilla linjoilla 500 metrin välein, ja nopeudet on tallennettu linjojen keskipisteisiin (n = 35 696). Pistekohteiden ominaisuustiedot kuvaavat rannansiirtymistä eri näkökulmista seuraavien yleisesti käytettyjen tunnuslukujen avulla (kts. USGS Digital Shoreline Analysis System DSAS, Henderson ym. 2026):\n\n- 'NSM': net shoreline movement (m), vanhimman ja uusimman rantaviivan välinen etäisyys. Positiiviset arvot kuvaavat siirtymistä merelle päin\n- 'SCE': shoreline change envelope (m), suurin kahden rantaviivan välinen etäisyys koko rantaviiva-aikasarjassa\n- 'EPR': end-point-rate (m/vuosi), vanhimman ja uusimman rantaviivan välinen etäisyys jaettuna kuluneella ajalla vuosina. Positiiviset arvot kuvaavat siirtymistä merelle päin\n- 'EPR_uncertainty': EPR epävarmuus (m)\n- 'LRR': linear regression rate (m/vuosi), keskimääräinen rannansiirtymisnopeus, joka on laskettu sovittamalla lineaarinen regressiomalli kaikkiin rantaviivahavaintoihin. Positiiviset arvot kuvaavat siirtymistä merelle päin. LRR on laskettu ainoastaan linjoille, jotka leikkaavat vähintään kolmea rantaviivaa\n- 'LRR_SE': LRR keskivirhe\n\nOminaisuustiedot sisältävät myös seuraavat tiedot:\n\n- 'shorelines': linjan leikkaamien rantaviivojen lukumäärä (enintään 8)\n- 'timespan': sen aikasarjan pituus, joka muodostuu linjan leikkaamista rantaviivoista (vuosina, enintään 35 vuotta)\n\nAlkuperäiset linjat (500 metrin välein, kukin kaksi kilometriä pitkä) sisältyvät myös aineistoon.\n\n*Lähteet*\n\nNylén, T., Calle, M., Gonzales-Inca, C. (2025). Unveiling coastal change across the Arctic with full Landsat collections and data fusion. Remote Sensing of Environment 322, 114696. https://doi.org/10.1016/j.rse.2025.114696.\n\nHenderson, R.E., Farris, A.S., Kratzmann, M.G., Bartlett, M.K., Ergul, A., McAndrews, J., Cibaj, R., Zichichi, J.L., Himmelstoss, E.A., Thieler, E.R. (2026). Digital Shoreline Analysis System version 6.1: U.S. Geological Survey software release. https://doi.org/10.5066/P1NHMJNC."},"field_of_science":[],"fileset":{"storage_service":"ida","csc_project":"2018959","total_files_count":28,"total_files_size":390324630},"infrastructure":[],"issued":"2026-04-20","keyword":["Coastal change","Land uplift","Erosion","Finland","Landsat","Rannikon muutos","Maankohoaminen","Eroosio","Suomi"],"language":[],"metadata_owner":{"id":"f63a7a54-e0c8-453c-aa00-79f44aad4b63","organization":"utu.fi","admin_organization":"utu.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-ade4f14f-20d3-3c37-8372-eef09ab91965","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Nylén, Calle, Gonzales-Inca: Unveiling coastal change across the Arctic with full Landsat collections and data fusion","fi":"Nylén, Calle, Gonzales-Inca: Unveiling coastal change across the Arctic with full Landsat collections and data fusion"},"entity_identifier":"https://doi.org/10.1016/j.rse.2025.114696","type":{"id":"fb3d4a47-7445-423e-a4be-0693bcb8047b","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Publication","fi":"Julkaisu"}}},"relation_type":{"id":"618665fa-c468-4bf5-b361-992c82861fe7","url":"http://purl.org/vocab/frbr/core#successorOf","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Continues","fi":"Täydentää aineistoa"}},"metax_ids":[]}],"remote_resources":[],"spatial":[{"geographic_name":"Coast of Finland (Suomen rannikko, 59°–66° N)","custom_wkt":["POLYGON ((19.45736 59.56423, 17.75111 65.56864, 27.97203 65.847, 27.79041 59.77923, 19.45736 59.56423))"],"geolocations":{"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[19.45736,59.56423],[17.75111,65.56864],[27.97203,65.847],[27.79041,59.77923],[19.45736,59.56423]]]},"bbox":[17.75111,59.56423,27.97203,65.847]}]}}],"state":"published","temporal":[{"start_date":"1985-01-01","end_date":"2024-12-31"}],"theme":[],"title":{"en":"Finland Coastal Change","fi":"Finland Coastal Change"},"created":"2026-04-20T14:06:05Z","modified":"2026-04-21T12:37:16Z","dataset_versions":[{"id":"c4dabb35-1c26-4782-ae2f-e2bbd55020c4","title":{"en":"Finland Coastal Change","fi":"Finland Coastal Change"},"persistent_identifier":"doi:10.23729/fd-ade4f14f-20d3-3c37-8372-eef09ab91965","state":"published","created":"2026-04-20T14:06:05Z","version":1}],"published_revision":3,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-20T14:06:05Z","record_modified":"2026-04-21T12:37:16Z"},{"id":"4f676a16-9184-4d7d-85a1-cd0761ed8ab9","access_rights":{"id":"36d5d511-aeb9-48e7-888a-900e6655f2fb","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"334a22b4-127e-4b02-9950-a322c632cf10","roles":["creator"],"person":{"id":"4a74e280-d87b-49c2-8d00-7a6026ea27fe","name":"Dani Flinkman"},"organization":{"id":"a4dc30ef-4be2-412a-a399-ebac8a37213e","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi","sv":"Åbo Akademi","und":"Åbo Akademi"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"cd0ac2ea-875a-47ce-923b-c0b38cdc4a55","roles":["creator"],"person":{"id":"d93bb999-f6aa-4906-8a12-8083a9cb6d99","name":"Eleanor Coffey","external_identifier":"https://orcid.org/0000-0002-9717-5610"},"organization":{"id":"a4dc30ef-4be2-412a-a399-ebac8a37213e","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi","sv":"Åbo Akademi","und":"Åbo Akademi"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"b2209e29-6969-4640-bbed-59df91a60e79","roles":["publisher"],"organization":{"id":"7777c26a-199d-4744-8862-2ceee193d530","pref_label":{"en":"Zenodo","fi":"Zenodo","sv":"Zenodo"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-abo","description":{"en":"This is a set of phosphoproteomic data from 5 sets of patient data from sporadic Parkinson's brain. Regions include substantia nigra, striatum and temporal gyrus. Data was analysed from MS spectra located in PRIDE repository PXD034120, PXD037684, and PXD047134 that had not previously been analysed for post translational modifications."},"field_of_science":[{"id":"aaeda937-2324-41b5-af09-17f5f34b7b8e","url":"http://www.yso.fi/onto/okm-tieteenala/ta318","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Medical biotechnology","fi":"Lääketieteen bioteknologia","sv":"Medicinsk bioteknologi"}}],"infrastructure":[],"issued":"2026-04-09","keyword":[],"language":[],"metadata_owner":{"id":"dde6b62a-99e9-49c2-92bc-4a08ae3d9a09","organization":"service_abo"},"other_identifiers":[],"persistent_identifier":"doi:10.5281/zenodo.19486407","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Phosphoproteomic reanalysis of PRotein IDEntification database (PRIDE) datasets: PXD034120, PXD047134 and PXD037684"},"created":"2026-04-21T06:35:54Z","modified":"2026-04-21T06:35:54Z","dataset_versions":[{"id":"4f676a16-9184-4d7d-85a1-cd0761ed8ab9","title":{"en":"Phosphoproteomic reanalysis of PRotein IDEntification database (PRIDE) datasets: PXD034120, PXD047134 and PXD037684"},"persistent_identifier":"doi:10.5281/zenodo.19486407","state":"published","created":"2026-04-21T06:35:54Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-21T06:35:55Z","record_modified":"2026-04-21T06:35:55Z"},{"id":"45bc57fa-4664-4a26-bc2b-89a89582bb28","access_rights":{"id":"897e96aa-708c-4ab6-95d5-e4105ed256b2","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"1dc63581-2c9e-41a3-bbbf-132eb1271dce","roles":["creator"],"person":{"id":"2b20d714-be3e-4dcc-998c-91df63cf3592","name":"Ahmad Alkhaldi"},"organization":{"id":"3d0ee2ad-0248-4bd4-8344-ab57fbd521e9","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi University","sv":"Åbo Akademi University"},"external_identifier":"https://ror.org/029pk6x14"}},{"id":"c3e11322-ca2b-4194-b041-3081b6ec8289","roles":["creator"],"person":{"id":"b57abc93-2b11-43c9-b69f-dadb5edeec4f","name":"Igli Balla"},"organization":{"id":"3d0ee2ad-0248-4bd4-8344-ab57fbd521e9","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi University","sv":"Åbo Akademi University"},"external_identifier":"https://ror.org/029pk6x14"}},{"id":"46aa68ef-83ec-4252-ae92-496edf5224a3","roles":["creator"],"person":{"id":"1e017f3f-883d-4876-9a72-856ee2074d81","name":"Rahma El Bouazzaoui"},"organization":{"id":"3d0ee2ad-0248-4bd4-8344-ab57fbd521e9","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi University","sv":"Åbo Akademi University"},"external_identifier":"https://ror.org/029pk6x14"}},{"id":"7400c9b8-ad23-4edb-8a6c-c615d0feb040","roles":["creator"],"person":{"id":"4a3f5f6f-5634-454a-a343-a9eb309571eb","name":"Tirthendu Chakravorty"},"organization":{"id":"3d0ee2ad-0248-4bd4-8344-ab57fbd521e9","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi University","sv":"Åbo Akademi University"},"external_identifier":"https://ror.org/029pk6x14"}},{"id":"a92b1edc-e1a1-4ff6-a033-d8ba4ddca962","roles":["creator"],"person":{"id":"db904618-6167-4eec-b62a-88c048e78a4c","name":"Hergys Rexha"},"organization":{"id":"a4dc30ef-4be2-412a-a399-ebac8a37213e","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi","sv":"Åbo Akademi","und":"Åbo Akademi"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"d5fd4135-ad30-422c-b6a3-946525e84e86","roles":["creator"],"person":{"id":"4e430e4b-1224-4ffe-8000-efa3ca6163a8","name":"Sebastien Lafond","external_identifier":"https://orcid.org/0000-0002-5286-5343"},"organization":{"id":"a4dc30ef-4be2-412a-a399-ebac8a37213e","pref_label":{"en":"Åbo Akademi University","fi":"Åbo Akademi","sv":"Åbo Akademi","und":"Åbo Akademi"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01903","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"65a98cb2-db34-4932-9ea3-a81fe9fbf725","roles":["creator"],"person":{"id":"a53c4577-1606-4ff5-915d-2e514a726abd","name":"Tristan Klempka"},"organization":{"id":"f1c300e0-f6ef-449b-b070-728261461291","pref_label":{"en":"AILiveSim"}}},{"id":"62510172-623f-4fc0-88d4-a95ddd08584d","roles":["publisher"],"organization":{"id":"b9e8d1b0-49ea-4c35-b43a-567db26d2060","pref_label":{"en":"Zenodo","fi":"Zenodo","sv":"Zenodo"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-abo","description":{"en":"To use the dataset, the zip parts should be merged back together.\r\n\r\nThis dataset was created for theme name, which was accepted at the IEEE Conference on Artificial Intelligence 2026. paper of the saThe paper will be presented on 9/5/26: https://www.ieeesmc.org/cai-2026/detailed-schedule/ \r\n\r\nWhen using this dataset, please cite this Zenodo record and the associated publication: \r\n\r\nAlkhaldi, Ahmad; Balla, Igli; El Bouazzaoui, Rahma; Chakravorty, Tirthendu Prosad; Rexha, Hergys; Lafond, Sebastien; Klempka, Tristan, Hybrid 3D Asset Retrieval Via Contrastive Vision-Language Matching and Structured Prompt Parsing, IEEE Conference on Artificial Intelligence 2026."},"field_of_science":[{"id":"33d291b9-9b23-4192-b878-cffc210af1d3","url":"http://www.yso.fi/onto/okm-tieteenala/ta113","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Computer and information sciences","fi":"Tietojenkäsittely ja informaatiotieteet","sv":"Data- och informationsvetenskap"}}],"infrastructure":[],"issued":"2025-11-19","keyword":[],"language":[],"metadata_owner":{"id":"dde6b62a-99e9-49c2-92bc-4a08ae3d9a09","organization":"service_abo"},"other_identifiers":[],"persistent_identifier":"doi:10.5281/zenodo.17584713","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Hybrid 3D Asset Retrieval via Contrastive Vision-Language Matching and Structured Prompt Parsing"},"created":"2026-04-21T06:35:51Z","modified":"2026-04-21T06:35:51Z","dataset_versions":[{"id":"45bc57fa-4664-4a26-bc2b-89a89582bb28","title":{"en":"Hybrid 3D Asset Retrieval via Contrastive Vision-Language Matching and Structured Prompt Parsing"},"persistent_identifier":"doi:10.5281/zenodo.17584713","state":"published","created":"2026-04-21T06:35:51Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-21T06:35:52Z","record_modified":"2026-04-21T06:35:52Z"},{"id":"fcb78e11-0c56-425b-9547-16b9451dda95","access_rights":{"id":"3d83e6a9-d690-4918-ba3e-16cf69c46d1d","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"0ff1fed5-6a67-47b3-8478-9dce0f4920df","roles":["creator","publisher"],"person":{"id":"13ac2847-41d1-4a31-99f1-9b3ba401baa8","name":"Ekaterina Paasonen","email":"","external_identifier":"https://orcid.org/0000-0003-2365-865X"},"organization":{"id":"59637e7e-9d36-41b1-bfc0-4c6acb3b90b4","pref_label":{"en":"A.I. Virtanen -instituutti","fi":"A.I. Virtanen -instituutti","sv":"A.I. Virtanen -instituutti","und":"A.I. Virtanen -instituutti"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10088-29401","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"e9d4978f-97d0-4d50-93dd-ee3987b63001","pref_label":{"en":"University of Eastern Finland","fi":"Itä-Suomen yliopisto","sv":"Östra Finlands universitet","und":"Itä-Suomen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10088","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"In this folder, scripts and data related to the manuscript \"Mapping Cardiac and Respiratory Pulsations Simultaneously with Functional Connectivity in the Rat Brain Using Zero Echo Time fMRI\" are stored.\n\n\"scripts\" folder contains scripts in Matlab and Python used to perform all data preprocessing and analysis steps. \n\n\"derivatives\" folder contains:\n-denoised ECG files in .mat format along with detected R-R and breathing peaks,\n-reconstructed in three ways functional ZTE files in NIfTi format(cardiac-gated, respiratory-gated and traditional resting-state),\n-MB-SWIFT anatomical images. \nAll MRI images are coregistered to the common template. Folder is organized in BIDS format.\n\n\"extras\" folder contains coregistration template and ROIs used for the data analysis.\n\nFor further inquiries please contact: Ekaterina Paasonen, ekaterina.paasonen@uef.fi"},"field_of_science":[{"id":"86f7e152-5062-476a-bf43-c09bf5e2c0b5","url":"http://www.yso.fi/onto/okm-tieteenala/ta3112","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Neurosciences","fi":"Neurotieteet","sv":"Neurovetenskaper"}}],"fileset":{"storage_service":"ida","csc_project":"2001107","total_files_count":1,"total_files_size":185112030643},"infrastructure":[],"issued":"2026-04-14","keyword":["fMRI","ZTE","pulsations","neurofluids"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"16e37651-3910-41e5-8dab-98b7dc219a69","organization":"uef.fi","admin_organization":"uef.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.23729/fd-82383458-691c-36c3-9561-698e946269d0","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Original data for \"Mapping Cardiac and Respiratory Pulsations Simultaneously with Functional Connectivity in the Rat Brain Using Zero Echo Time fMRI\""},"created":"2026-04-14T07:29:49Z","modified":"2026-04-20T12:26:46Z","dataset_versions":[{"id":"fcb78e11-0c56-425b-9547-16b9451dda95","title":{"en":"Original data for \"Mapping Cardiac and Respiratory Pulsations Simultaneously with Functional Connectivity in the Rat Brain Using Zero Echo Time fMRI\""},"persistent_identifier":"doi:10.23729/fd-82383458-691c-36c3-9561-698e946269d0","state":"published","created":"2026-04-14T07:29:49Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-14T07:29:50Z","record_modified":"2026-04-20T12:26:49Z"},{"id":"0db51145-4b24-423a-9f2b-384bb91aac69","access_rights":{"id":"07643aea-7651-4cb7-a3d8-6e8c24b9d516","description":{"en":"Limited access until data is used in a publication"},"license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"43720e8a-af93-458f-af21-3c6f16ea1d47","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/embargo","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Embargo","fi":"Embargo"}},"restriction_grounds":[{"id":"0ed3a2e1-6c11-4278-af67-c6713f838ecd","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restricted access due to other reasons","fi":"Saatavuutta rajoitettu muulla perusteella","sv":"Begränsad åtkomst av övriga skäl"}}],"show_file_metadata":false},"actors":[{"id":"b14813a8-3af1-4d02-814f-0ea203ef6d57","roles":["creator","publisher","rights_holder"],"person":{"id":"3aa9b200-cf51-483c-a40f-3fbb7a1c3bbd","name":"Jenni Prokkola","email":""},"organization":{"id":"b941a6eb-d7ba-4261-aa8b-eb5cf98f709c","pref_label":{"en":"Natural Resources Institute Finland","fi":"Luonnonvarakeskus","sv":"Naturresursinstitutet","und":"Luonnonvarakeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"01139faf-6af4-44cb-9a41-4a11f0b47856","roles":["creator"],"person":{"id":"594a1969-bb10-4f83-a16f-6087d2f12884","name":"Lucy Cotgrove","email":""},"organization":{"id":"b941a6eb-d7ba-4261-aa8b-eb5cf98f709c","pref_label":{"en":"Natural Resources Institute Finland","fi":"Luonnonvarakeskus","sv":"Naturresursinstitutet","und":"Luonnonvarakeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":1,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"AVITI high throughput PE raw sequence data. Two libraries, each with 96 samples. Each sample is prepared with 3' RNAseq library preparation protocol from RNA extracted from gill tissue of juvenile Atlantic salmon."},"field_of_science":[{"id":"ea57f07d-16d8-4c7a-8a52-39ef1112278a","url":"http://www.yso.fi/onto/okm-tieteenala/ta1181","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Ecology, evolutionary biology","fi":"Ekologia, evoluutiobiologia","sv":"Ekologi, evolutionsbiologi"}},{"id":"be28a2ad-4020-40c5-82f4-cc90fbb15b97","url":"http://www.yso.fi/onto/okm-tieteenala/ta1184","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Genetics, developmental biology, physiology","fi":"Genetiikka, kehitysbiologia, fysiologia","sv":"Genetik, utvecklingsbiologi, fysiologi"}}],"infrastructure":[],"issued":"2026-04-20","keyword":["lohi","salmon","gill","transcriptomics","geeniekspressio","lämpötila","temperature"],"language":[],"metadata_owner":{"id":"1dfb1b42-a382-4059-b24c-a17afb3b1f93","organization":"luke.fi","admin_organization":"luke.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:fd-935b0092-5e7f-30ad-a334-22d6c22f2461","pid_generated_by_fairdata":true,"projects":[{"id":"6616d995-c82b-48cc-b3dd-996331fa6e8a","title":{"en":"Evolutionary physiology of thermal performance in Atlantic salmon"},"project_identifier":"THERMOEVO","participating_organizations":[{"id":"298f263c-1492-4a70-9adc-6012c2c14e3a","pref_label":{"en":"Vaelluskalat ja rakennetut joet","fi":"Vaelluskalat ja rakennetut joet","sv":"Vaelluskalat ja rakennetut joet","und":"Vaelluskalat ja rakennetut joet"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010-4100111210","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"b941a6eb-d7ba-4261-aa8b-eb5cf98f709c","pref_label":{"en":"Natural Resources Institute Finland","fi":"Luonnonvarakeskus","sv":"Naturresursinstitutet","und":"Luonnonvarakeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"funding":[{"funder":{"organization":{"id":"298f263c-1492-4a70-9adc-6012c2c14e3a","pref_label":{"en":"Vaelluskalat ja rakennetut joet","fi":"Vaelluskalat ja rakennetut joet","sv":"Vaelluskalat ja rakennetut joet","und":"Vaelluskalat ja rakennetut joet"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010-4100111210","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"b941a6eb-d7ba-4261-aa8b-eb5cf98f709c","pref_label":{"en":"Natural Resources Institute Finland","fi":"Luonnonvarakeskus","sv":"Naturresursinstitutet","und":"Luonnonvarakeskus"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4100010","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},"funder_type":{"id":"d38a8484-f3d7-43cf-ad79-829ebb3ba9eb","url":"http://uri.suomi.fi/codelist/fairdata/funder_type/code/academy-of-finland","in_scheme":"http://uri.suomi.fi/codelist/fairdata/funder_type","pref_label":{"en":"Academy of Finland","fi":"Suomen Akatemia"}}},"funding_identifier":"348965"}]}],"provenance":[],"relation":[],"remote_resources":[],"spatial":[{"geographic_name":"Itämeri","reference":{"id":"de91e413-705e-43ff-bcfc-d7fa2138645b","url":"http://www.yso.fi/onto/yso/p105655","in_scheme":"http://www.yso.fi/onto/yso/places","pref_label":{"en":"Iijoki Basin","fi":"Iijoen vesistö","sv":"Ijo älvs vattendrag"},"as_wkt":"POINT (25.274 65.34)"},"custom_wkt":["POINT (25.274 65.34)"],"geolocations":{"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Point","coordinates":[25.274,65.34]},"bbox":[25.274,65.34,25.274,65.34]}]}}],"state":"published","temporal":[],"theme":[],"title":{"en":"RNAseq data from salmon gills"},"created":"2026-04-20T11:07:06Z","cumulation_started":"2026-04-20T11:08:26Z","modified":"2026-04-20T11:08:24Z","dataset_versions":[{"id":"0db51145-4b24-423a-9f2b-384bb91aac69","title":{"en":"RNAseq data from salmon gills"},"persistent_identifier":"urn:nbn:fi:fd-935b0092-5e7f-30ad-a334-22d6c22f2461","state":"published","created":"2026-04-20T11:07:06Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-20T11:07:06Z","record_modified":"2026-04-20T11:08:26Z"},{"id":"10d3f7b9-31cf-499e-831c-2bb4a407757c","access_rights":{"id":"60ac19df-1f03-47df-904c-7b8bd771f7ee","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"a49882ac-15a3-4de0-ab83-8ea1bf6b25e6","roles":["creator"],"person":{"id":"dff6587b-b71e-4b3a-b3c7-c86786232336","name":"Joakim Jestilä","external_identifier":"https://orcid.org/0000-0002-7233-2093"},"organization":{"id":"5bda7535-0300-4299-b15d-b4950d914702","pref_label":{"en":"Department of Chemistry and Materials Science","fi":"Department of Chemistry and Materials Science","sv":"Department of Chemistry and Materials Science","und":"Department of Chemistry and Materials Science"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076-T105","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"7d61af1c-0cc6-46fe-9940-21da2b080cb3","pref_label":{"en":"Aalto University","fi":"Aalto-yliopisto","sv":"Aalto-universitetet","und":"Aalto-yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"843baaea-7f06-45a9-be32-438974d407c2","roles":["creator"],"person":{"id":"ab039799-4aeb-4734-985d-441394961dce","name":"Antti Karttunen","external_identifier":"https://orcid.org/0000-0003-4187-5447"},"organization":{"id":"5bda7535-0300-4299-b15d-b4950d914702","pref_label":{"en":"Department of Chemistry and Materials Science","fi":"Department of Chemistry and Materials Science","sv":"Department of Chemistry and Materials Science","und":"Department of Chemistry and Materials Science"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076-T105","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"7d61af1c-0cc6-46fe-9940-21da2b080cb3","pref_label":{"en":"Aalto University","fi":"Aalto-yliopisto","sv":"Aalto-universitetet","und":"Aalto-yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"9c001b07-061b-4364-8323-2a37015289f7","roles":["publisher"],"organization":{"id":"1541ed4c-c382-450f-8798-45990a51d0a4","pref_label":{"en":"Zenodo","fi":"Zenodo","sv":"Zenodo"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-acris","description":{"en":"This repository contains the results of a computational investigation of the oligomerization tendencies of three different lithium compounds commonly used as precursors for atomic layer deposition (ALD), lithium tert-butoxide (LiOtBu), lithium bis(trimethylsilyl)amide (Li-HMDS) and lithium 2,2,6,6-tetramethyl-3,5-heptanedionate (Li-THD). \r\n\r\nBriefly described, the contents of the repository are as follows: \r\n\r\n1) Conformer search using the conformer-rotamer ensemble sampling tool (CREST).\r\n\r\n2) DFT (B3LYP-D4/Def2-TZVPP) relaxation of the lowest energy conformers, followed by frequency calculations and thermal corrections at a range of temperatures (270 K to 698 K), including relaxation trajectories, optimized geometries and Hessians. \r\n\r\n3) DLPNO-CCSD(T)/CBS single point energy calculations on the final DFT structures, using the 3/4-extrapolation scheme (Def2-TZVPP/Def2-QZVPP).\r\n\r\n4) A file containing the cartesian coordinates of the optimized geometries of all precursors (Li_precursor_oligomers.xyz), as well as all oligomers of a given precursor compound (LiOtBu_oligomers.xyz, LiHMD_oligomers.xyz and LiTHD_oligomers.xyz)."},"field_of_science":[{"id":"4fca0be9-45d1-4544-9eeb-24dec6bcb0df","url":"http://www.yso.fi/onto/okm-tieteenala/ta116","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Chemical sciences","fi":"Kemia","sv":"Kemi"}}],"infrastructure":[],"issued":"2026-04-10","keyword":[],"language":[],"metadata_owner":{"id":"fce90ccd-e305-45f9-90b3-1e462f048c9a","organization":"aalto.fi","admin_organization":"aalto.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.5281/zenodo.19492284","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Computational gas-phase oligomerization equilibria of lithium precursors for atomic layer deposition"},"created":"2026-04-16T04:43:59Z","modified":"2026-04-18T12:45:23Z","dataset_versions":[{"id":"10d3f7b9-31cf-499e-831c-2bb4a407757c","title":{"en":"Computational gas-phase oligomerization equilibria of lithium precursors for atomic layer deposition"},"persistent_identifier":"doi:10.5281/zenodo.19492284","state":"published","created":"2026-04-16T04:43:59Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-16T04:43:59Z","record_modified":"2026-04-18T12:45:24Z"},{"id":"d97fc8ae-5c93-4fd6-8af7-389ece117e26","access_rights":{"id":"edbc4dc3-d856-45c8-a242-7afd9c469e0e","license":[{"id":"35b18e72-3819-4ec6-a1be-14624f29d968","url":"http://uri.suomi.fi/codelist/fairdata/license/code/CC-BY-4.0","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Creative Commons Attribution 4.0 International (CC BY 4.0)","fi":"Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"1f86287d-53c9-4268-b44a-7faf19c5126e","roles":["creator"],"person":{"id":"1155ced7-826d-4e55-878b-99aee7b01e69","name":"Jaana Vapaavuori","external_identifier":"https://orcid.org/0000-0002-5923-0789"},"organization":{"id":"5bda7535-0300-4299-b15d-b4950d914702","pref_label":{"en":"Department of Chemistry and Materials Science","fi":"Department of Chemistry and Materials Science","sv":"Department of Chemistry and Materials Science","und":"Department of Chemistry and Materials Science"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076-T105","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"7d61af1c-0cc6-46fe-9940-21da2b080cb3","pref_label":{"en":"Aalto University","fi":"Aalto-yliopisto","sv":"Aalto-universitetet","und":"Aalto-yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"0747e3c3-0be3-4a31-af43-350ba755821d","roles":["creator"],"person":{"id":"66d057fa-5b2f-48f0-9456-f898586c52aa","name":"Pedro Emanuel Santos Sillva","external_identifier":"https://orcid.org/0000-0002-8783-8740"},"organization":{"id":"5bda7535-0300-4299-b15d-b4950d914702","pref_label":{"en":"Department of Chemistry and Materials Science","fi":"Department of Chemistry and Materials Science","sv":"Department of Chemistry and Materials Science","und":"Department of Chemistry and Materials Science"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076-T105","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"7d61af1c-0cc6-46fe-9940-21da2b080cb3","pref_label":{"en":"Aalto University","fi":"Aalto-yliopisto","sv":"Aalto-universitetet","und":"Aalto-yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"c9aeca02-c4e1-4428-91e2-4aa9d1121ea0","roles":["creator"],"person":{"id":"e1f064e4-a4af-481d-a2e7-e145adc1d247","name":"Maija Vaara","external_identifier":"https://orcid.org/0000-0003-0090-0351"},"organization":{"id":"5bda7535-0300-4299-b15d-b4950d914702","pref_label":{"en":"Department of Chemistry and Materials Science","fi":"Department of Chemistry and Materials Science","sv":"Department of Chemistry and Materials Science","und":"Department of Chemistry and Materials Science"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076-T105","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"7d61af1c-0cc6-46fe-9940-21da2b080cb3","pref_label":{"en":"Aalto University","fi":"Aalto-yliopisto","sv":"Aalto-universitetet","und":"Aalto-yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10076","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"df26ea02-9906-4068-93fd-2999d10d00fe","roles":["publisher"],"organization":{"id":"bc08e025-0a5d-44f3-968a-4b0f82060407","pref_label":{"en":"Zenodo","fi":"Zenodo","sv":"Zenodo"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-acris","description":{"en":"Dataset Overview\r\n\r\nThis dataset contains molecular dynamics simulation inputs/outputs and physical experiment recordings for bobbin lace patterns studied for their pore contraction behaviour under selective yarn fixing.\r\n\r\n\r\n\r\nDirectory Structure\r\n\r\nThe repository is organized into three main directories:\r\n\r\n\r\n\r\n\r\n\r\nlammps_data/: Contains LAMMPS input files, specifically the particle mesh, with one file provided per pattern.\r\n\r\n\r\n\r\n\r\nsimulations/: Contains the molecular dynamics simulation results, organized with one subfolder per pattern (Pattern_{ID}/). Each subfolder includes:\r\n\r\n\r\n\r\n\r\n\r\nTrajectories (*.lammpstrj) for stabilisation and each individual contraction step.\r\n\r\n\r\n\r\n\r\nLAMMPS run logs (*.log).\r\n\r\n\r\n\r\n\r\nRestart files generated after stabilisation (sim1.restart).\r\n\r\n\r\n\r\n\r\nA plots/ directory containing time-series data for pore geometry (*_holes.json) and yarn contraction (*_yarn_lengths.json), combined analysis outputs, relative pore area changes, area distributions, histograms, and yarn length evolution plots.\r\n\r\n\r\n\r\n\r\n\r\n\r\ntextile samples/: Contains data from the physical experiments.\r\n\r\n\r\n\r\n\r\n\r\nFolders named {ID}-{n} {date}/ contain data for one lace sample each, where ID is the pattern and n is the replicate number. These folders hold contraction videos (*.MOV), before-and-after photographs (DSC_*.JPG), and a plots/ subfolder with identical analysis outputs to those found in the simulations.\r\n\r\n\r\n\r\n\r\nFolders knit_{date}/ and weave_{date}/ contain reference knitted (article label: K) and woven (article label: W) samples.\r\n\r\n\r\n\r\n\r\nThe images_tools/ directory contains photographs of the experimental equipment used.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nPattern Naming Conventions\r\n\r\nTwo naming systems are utilized across the dataset files. The article labels organize the patterns by their structural family: Knit (K), Woven (W), Square (S1-S2), Diamond (D1-D7), Hexa (H1), Rose (R1-R13), and Spruce (Sp1). The pattern IDs found in the file and folder names correspond directly to the numbering used in the reference bobbin lace pattern book: Uta Ulrich, Gründe mit System (2011).\r\n\r\nKey Variants and Exceptions:\r\n\r\n\r\n\r\n\r\n\r\nR12 (Rose-12) variants: The variant 3051_1t employs a 4-step contraction sequence ([[1],[3],[1,2],[1,2,3,4,5,6,7,8]]). The variant 3051v2 utilizes a 2-step sequence ([[1,2],[1,2,3,4,5,6,7,8]]). Three physical replicates for these variants are available under textile samples/3051/.\r\n\r\n\r\n\r\n\r\nPhysical samples located in textile samples/2003-01/ and textile samples/3110-10/ are included in the repository but were not used in the article simulations.\r\n\r\n\r\n\r\n\r\n\r\nSimulation File Naming\r\n\r\nLAMMPS data and trajectory files follow this specific naming convention: pattern{ID}_{dist}_{mass}_{threshold}_{ks}_{kb}[_contract_fix_{yarns}]\r\n\r\n\r\n\r\n\r\n\r\ndist: Particle spacing in simulation units (Value: 0.25).\r\n\r\n\r\n\r\n\r\nmass: Particle mass (Value: 1.0).\r\n\r\n\r\n\r\n\r\nthreshold: Contact force threshold (Value: 0.0).\r\n\r\n\r\n\r\n\r\nks: Stretching spring constant (Value: 30.0).\r\n\r\n\r\n\r\n\r\nkb: Bending stiffness (Value: 0.1).\r\n\r\n\r\n\r\n\r\nyarns: Underscore-separated IDs of the yarns held fixed during contraction (e.g., 1_2_3_4).\r\n\r\n\r\n\r\n\r\n\r\nNote: Files lacking the _contract_fix_* suffix represent the initial stabilisation runs. Each file with the _contract_fix_{yarns} suffix represents a subsequent contraction step.\r\n\r\n\r\n\r\n\r\nSoftware and Visualization\r\n\r\nSimulations were conducted using LAMMPS. To visualize the simulation trajectories using the free version of OVITO Basic, follow these steps:\r\n\r\n\r\n\r\n\r\n\r\nOpen the input file: Navigate to File → Open, and select the .data file for your desired pattern from the lammps_data/ directory.\r\n\r\n\r\n\r\n\r\nSet the import format: When the LAMMPS Data File Import dialog appears, set the Atom style to bond and map the columns to atom-ID, molecule-ID, atom-type, x, y, z.\r\n\r\n\r\n\r\n\r\nAdjust display sizes: In the Visual Elements panel, adjust the Particle Radius to 0.5 and the Bond Width to 1.0.\r\n\r\n\r\n\r\n\r\nLoad the trajectory: In the Pipeline panel, select Add modification... → Load Trajectory, and choose the corresponding .lammpstrj file from simulations/Pattern_{ID}/.\r\n\r\n\r\n\r\nTo observe the entire contraction protocol, load the stabilisation trajectory first (the file with no suffix), followed by the contraction step trajectories (_contract_fix_{yarns}.lammpstrj) in sequential order."},"field_of_science":[{"id":"58c407dd-b614-4d38-a92a-e6d9cdff7814","url":"http://www.yso.fi/onto/okm-tieteenala/ta216","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Materials engineering","fi":"Materiaalitekniikka","sv":"Materialteknik"}}],"infrastructure":[],"issued":"2026-03-26","keyword":[],"language":[],"metadata_owner":{"id":"fce90ccd-e305-45f9-90b3-1e462f048c9a","organization":"aalto.fi","admin_organization":"aalto.fi"},"other_identifiers":[],"persistent_identifier":"doi:10.5281/zenodo.19232528","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Active textiles move in confined areas dataset"},"created":"2026-04-16T04:43:55Z","modified":"2026-04-18T12:45:19Z","dataset_versions":[{"id":"d97fc8ae-5c93-4fd6-8af7-389ece117e26","title":{"en":"Active textiles move in confined areas dataset"},"persistent_identifier":"doi:10.5281/zenodo.19232528","state":"published","created":"2026-04-16T04:43:55Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-16T04:43:56Z","record_modified":"2026-04-18T12:45:21Z"},{"id":"67f9039e-9e60-4ccc-bef7-104b39cff60c","access_rights":{"id":"0b0dc256-030e-4865-8ab2-0e7d21a6e3b8","license":[{"id":"03258502-6709-437e-9a06-5661857ea4bf","description":{"en":"The dataset is (B) available for research, teaching and study.","fi":"Aineisto on käytettävissä (B) tutkimukseen, opetukseen ja opiskeluun."},"url":"http://uri.suomi.fi/codelist/fairdata/license/code/other-closed","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other (Not Open)","fi":"Muu (Ei avoin)"}}],"access_type":{"id":"729ffd9f-6d7a-40e9-aa97-a363a16fd113","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/restricted","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Restricted use","fi":"Saatavuutta rajoitettu"}},"restriction_grounds":[{"id":"484e859f-11b5-4163-a387-25c13fcaae29","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/research","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restriced access for research based on contract","fi":"Saatavuutta rajoitettu sopimuksen perusteella vain tutkimuskäyttöön","sv":"Begränsad åtkomst på bas av kontrakt ändast för forskningsändamål"}},{"id":"8c6eebb2-d1f7-47e9-a041-b32a172745b4","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/education","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restricted access for teaching or studying based on contract","fi":"Saatavuutta rajoitettu sopimuksen perusteella opetukseen ja opiskeluun","sv":"Begränsad åtkomst på bas av kontrakt ändast för undervisning och studier"}}]},"actors":[{"id":"14e55c2b-2091-4bdf-92a5-e1daf81d6e01","roles":["creator"],"organization":{"id":"6d788d2f-3acd-43f4-a407-5afc2bad34e5","pref_label":{"fi":"Nuorisotutkimusseura"}}},{"id":"4a9d9c80-2c92-4f3b-b972-687cb729c21e","roles":["creator"],"organization":{"id":"2e69c476-a019-4d2c-92d5-f7eb43ca366f","pref_label":{"fi":"Opetus- ja kulttuuriministeriö. Valtion nuorisoneuvosto"}}},{"id":"3de15d41-9cbb-4bae-9d5e-aeb294ef3d12","roles":["creator"],"organization":{"id":"56b3f60c-ebd9-4b5c-9063-50690a44f031","pref_label":{"en":"Finnish Youth Research Society"}}},{"id":"28c2134e-19f5-4c75-95ba-779cb45b1708","roles":["creator"],"organization":{"id":"3589f6c4-458e-4653-bc54-40347086edd5","pref_label":{"en":"Ministry of Education and Culture. State Youth Council"}}},{"id":"a424bdd4-6b24-4f10-8a32-32175dd206fb","roles":["publisher"],"organization":{"id":"24e34cd1-11fc-4777-985c-dbdd68b78c24","pref_label":{"en":"Tietoarkisto","fi":"Tietoarkisto","sv":"Tietoarkisto","und":"Tietoarkisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122-6130","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-harvest-fsd","description":{"en":"In the interview survey Children and Youth Leisure Survey 2020, the leisure time and hobbies of people aged 7-29 were examined. In this year's survey, the main themes were children's and young people's media use and participation in culture and the arts. The interview questions differed slightly according to the age of the respondent, and a few questions were also asked of the parents of those under 15. At the beginning, a few background questions were asked of respondents aged 15-29. For those under 15, the questions were asked of their parent. The questions concerned gender, municipality of residence, and mother tongue. After this, children's and young people's leisure time and hobbies were examined. The respondents themselves, or the parents of children under 10, were asked about the prevalence of hobbies, the frequency of participation, and the adequacy of leisure time. Those aged over 10 were additionally asked about participation in culture and about possible experiences of inappropriate treatment in hobbies. Next, the questions dealt with children's and young people's social contacts, their forms, and regularity. The respondents were asked, for example, about the frequency and ways of keeping in contact and about the use of social media as a communication channel. Internet and media use was examined, for example, by asking what activities the respondent engages in online, whether they follow social media influencers, whether they have encountered inappropriate behaviour online, and whether they listen to music or attend music events. In addition, respondents aged over 15 were asked about their views on body modification, such as tattoos and piercings. Questions related to media use were also asked of the parents of children under 15. Parents were asked, for example, about conflicts in the family caused by gaming and internet use, and about ways of restricting children's phone use. After this, respondents aged 10-29 were asked about membership of organisations and participation in organisational activities. In addition, the respondents were asked to assess their satisfaction with different areas of life. Finally, respondents aged 10-29 were asked for further background information, such as their level of education and whether they felt they belonged to a minority. The background variables in the data include age, gender, language, major regions NUTS2, type of neighbourhood, education, and economic activity.","fi":"Lasten ja nuorten vapaa-aika 2020-haastattelututkimuksessa kartoitettiin 7-29-vuotiaiden vapaa-ajan viettoa sekä harrastamista. Tämän vuoden kyselyssä pääteemoja olivat lasten ja nuorten median käyttö sekä kulttuurin ja taiteen harrastaminen. Haastattelukysymykset poikkesivat toisistaan hieman haastateltavan iän mukaan, ja alle 15-vuotiaiden vanhemmille esitettiin myös muutamia kysymyksiä. Aluksi esitettiin muutama taustoittava kysymys 15-29-vuotiaille haastateltaville. Alle 15-vuotiaiden kohdalla kysymykset esitettiin hänen vanhemmalleen. Kysymykset koskivat sukupuolta, asuinpaikkakuntaa sekä äidinkieltä. Tämän jälkeen kartoitettiin lasten ja nuorten vapaa-aikaa ja harrastamista. Haastateltavalta itseltään tai alle 10-vuotiaiden lasten vanhemmilta kysyttiin harrastusten yleisyydestä, harrastamisen tiheydestä sekä vapaa-ajan riittävyydestä. Yli 10-vuotiailta tiedusteltiin lisäksi kulttuurin harrastamisesta sekä mahdollisista epäasiallisen kohtelun kokemuksista harrastusten yhteydessä. Seuraavaksi kysymykset käsittelivät lasten ja nuorten sosiaalisia kontakteja, niiden muotoja ja säännöllisyyttä. Haastateltavilta kysyttiin muun muassa yhteydenpidon yleisyydestä ja tavoista sekä sosiaalisen median käytöstä viestinnän väylänä. Netin ja median käytöstä tiedusteltiin muun muassa, mitä asioita haastateltava tekee netissä, seuraako hän sosiaalisen median vaikuttajia, onko hän kohdannut epäasiallista käytöstä verkossa sekä kuunteleeko hän musiikkia tai käy musiikkitapahtumissa. Lisäksi yli 15-vuotiailta tiedusteltiin heidän näkemyksiään kehon muokkaamisesta, kuten tatuoinneista ja lävistyksistä. Median käyttöön liittyviä kysymyksiä esitettiin myös alle 15-vuotiaiden lasten vanhemmille. Vanhemmilta kysyttiin muun muassa pelaamisen ja internetin käytön aiheuttamista riidoista perheessä sekä tavoista rajoittaa lasten puhelimen käyttöä. Tämän jälkeen 10-29-vuotiailta tiedusteltiin järjestöihin kuulumisesta ja järjestötoimintaan osallistumisesta. Lisäksi haastateltavia pyydettiin arvioimaan tyytyväisyyttään elämän eri osa-alueisiin. Lopuksi 10-29-vuotiailta kysyttiin lisää taustatietoja, kuten haastateltavan koulutustasoa sekä sitä, kokeeko hän kuuluvansa johonkin vähemmistöön. Taustamuuttujina aineistossa ovat ikä, sukupuoli, kieli, suuralue, paikkakuntatyyppi, koulutus ja pääasiallinen toiminta."},"field_of_science":[{"id":"eb6d49d6-6bfc-4d8c-86b8-d9497924b295","url":"http://www.yso.fi/onto/okm-tieteenala/ta5","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Social sciences","fi":"YHTEISKUNTATIETEET","sv":"Samhällsvetenskaper"}}],"infrastructure":[],"issued":"2026-04-07","keyword":["ajankäyttö","epäasiallinen kohtelu","harrastukset","hyvinvointi","Internet","järjestötoiminta","kulttuuriharrastukset","lapset (ikäryhmät)","mediankäyttö","nuoret","ruutuaika","sosiaaliset suhteet","vapaa-aika","vapaa-ajantoiminnat","adolescents","children","community action","cultural activitie","harassment","hobbies","internet","leisure time","leisure time activities","mass media use","social life","time budgets","well-being (health)","Lapset","Nuoret","Ajankäyttö","Kulttuuritoiminta ja -osallistuminen, mielipiteet kulttuurista","Children","Youth","Time use","Cultural activities and participation"],"language":[{"id":"c757dc29-552d-48b2-9efc-4d53b939a7ef","url":"http://lexvo.org/id/iso639-3/fin","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"Finnish","fi":"suomi","sv":"finska"}}],"metadata_owner":{"id":"0eabdf3f-948e-43bf-84ab-fe7b6163faaf","organization":"service_fsd"},"other_identifiers":[{"notation":"https://doi.org/10.60686/t-fsd3990","identifier_type":{"id":"753e313e-2eb1-4f81-988c-d50e7a7cd7fb","url":"http://uri.suomi.fi/codelist/fairdata/identifier_type/code/doi","in_scheme":"http://uri.suomi.fi/codelist/fairdata/identifier_type","pref_label":{"en":"Digital Object Identifier (DOI)"}},"metax_ids":[]}],"persistent_identifier":"urn:nbn:fi:fsd:T-FSD3990","pid_generated_by_fairdata":false,"projects":[],"provenance":[{"id":"8534bec3-5f15-4f00-a959-568787defd14","title":{"en":"Collection"},"description":{"en":"Contains the date(s) when the data were collected."},"spatial":{"geographic_name":"Suomi"},"temporal":{"start_date":"2020-01-23","end_date":"2020-02-29"},"is_associated_with":[],"used_entity":[],"variables":[{"id":"b2102289-54d8-4e4b-9ba6-651e300b5189","pref_label":{"en":"Children and young people aged 7-29 living in mainland Finland","fi":"7-29-vuotiaat Manner-Suomessa asuvat lapset ja nuoret"}}]},{"id":"805c5273-cd80-43d0-be3c-81ac674eada7","title":{"en":"Production"},"description":{"en":"Date when the data collection were produced (not distributed or archived)"},"temporal":{"start_date":"2026-04-07","end_date":"2026-04-07"},"is_associated_with":[],"used_entity":[],"variables":[]},{"id":"07907753-85f1-4941-8239-972afda06c46","title":{"en":"Production"},"description":{"en":"Date when the data collection were produced (not distributed or archived)"},"temporal":{"start_date":"2026-04-14","end_date":"2026-04-14"},"is_associated_with":[],"used_entity":[],"variables":[]},{"id":"184edd9c-4a84-4a02-964f-2320ca6fc39e","title":{"en":"Collection"},"description":{"en":"Contains the date(s) when the data were collected."},"spatial":{"geographic_name":"Finland"},"is_associated_with":[],"used_entity":[],"variables":[]}],"relation":[],"remote_resources":[],"spatial":[{"geographic_name":"Suomi"},{"geographic_name":"Finland"}],"state":"published","temporal":[{"start_date":"2020-01-23","end_date":"2020-02-29"}],"theme":[],"title":{"en":"Children and Youth Leisure Survey 2020","fi":"Lasten ja nuorten vapaa-aika 2020"},"created":"2026-04-08T01:10:22Z","modified":"2026-04-18T01:09:54Z","dataset_versions":[{"id":"67f9039e-9e60-4ccc-bef7-104b39cff60c","title":{"en":"Children and Youth Leisure Survey 2020","fi":"Lasten ja nuorten vapaa-aika 2020"},"persistent_identifier":"urn:nbn:fi:fsd:T-FSD3990","state":"published","created":"2026-04-08T01:10:22Z","version":1}],"published_revision":3,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-08T01:10:22Z","record_modified":"2026-04-18T01:09:55Z"},{"id":"c5acb070-13f1-44f5-b570-3ebed7acb20f","access_rights":{"id":"ffcc8601-cd65-4852-b214-e59df767103b","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"https://creativecommons.org/licenses/by/4.0/","url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"2fc4125c-4254-44e7-92f7-1fdd8dab254c","roles":["creator"],"person":{"id":"10bc2929-5410-4ac4-bf54-76dfa0e40970","name":"DIGITS project team"},"organization":{"id":"3f7aa419-42e4-445a-999e-9b58a0165119","pref_label":{"en":"DIGITS project team"}}},{"id":"33692908-c5a2-41ed-85dc-7d10a0b49589","roles":["publisher","creator"],"person":{"id":"65445751-34ca-4172-8e94-c166aaa79437","name":"Philipp Müller","email":""},"organization":{"id":"1025824c-5798-4d94-9b93-ea3cbfc89580","pref_label":{"en":"Tampere University of Technology","fi":"Tampereen teknillinen yliopisto","sv":"Tammerfors tekniska universitet","und":"Tampereen teknillinen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01915","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":2,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"Zip-file that contains the datasets measured with the eNose as well as all scripts needed for redoing the tests discussed in Müller et al. - Online Scent Classification by Ion-Mobility Spectrometry Sequences."},"field_of_science":[{"id":"d8354311-7dfe-45ff-86cc-67869faf332f","url":"http://www.yso.fi/onto/okm-tieteenala/ta119","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Other natural sciences","fi":"Muut luonnontieteet","sv":"Övrig naturvetenskap"}}],"fileset":{"storage_service":"ida","csc_project":"2000547","total_files_count":1,"total_files_size":4315153},"infrastructure":[],"issued":"2021-02-05","keyword":["ion-mobility spectrometry"],"language":[],"metadata_owner":{"id":"152c4a53-7d33-4549-bc69-218c8bb411ce","organization":"tuni.fi","admin_organization":"tuni.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:a434b7ae-679a-44ba-b417-1cc1d82bdbbd","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[{"id":"954d32ae-f9e5-42f8-b166-f3dcce9f1760","url":"http://www.yso.fi/onto/koko/p69508","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"ion-mobility spectrometry","fi":"ioniliikkuvuusspektrometria","sv":"jonrörlighetsspektrometri"}}],"title":{"en":"Data for Muller et al. -- Online Scent Classification by Ion-mobility Spectrometry Sequences"},"created":"2021-02-05T07:29:21Z","cumulation_started":"2021-02-05T07:29:21Z","cumulation_ended":"2021-02-05T07:51:04Z","modified":"2026-04-16T15:11:03Z","dataset_versions":[{"id":"c5acb070-13f1-44f5-b570-3ebed7acb20f","title":{"en":"Data for Muller et al. -- Online Scent Classification by Ion-mobility Spectrometry Sequences"},"persistent_identifier":"urn:nbn:fi:att:a434b7ae-679a-44ba-b417-1cc1d82bdbbd","state":"published","created":"2021-02-05T07:29:21Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2025-02-10T17:21:39Z","record_modified":"2026-04-16T15:11:03Z"},{"id":"5e5eecec-fd69-40ab-ad44-216ceac474df","access_rights":{"id":"0c885fb6-c237-4636-8bb1-84fd3bad6ba4","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"https://creativecommons.org/licenses/by/4.0/","url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"9bc55104-d408-4620-9bca-41d386479f16","roles":["creator"],"person":{"id":"2c20777c-9ec8-4f30-8890-c9dbf22318e2","name":"Müller et al."},"organization":{"id":"47b1d651-35be-4b12-a6f5-ca0ed76fe070","pref_label":{"und":"Tampere University of Technology / University of Tampere"}}},{"id":"3f44dd21-08e6-4ef3-8f5b-c5f81b4df6b2","roles":["publisher"],"organization":{"id":"859201b3-53d1-4564-99e5-626a26ca00d8","pref_label":{"fi":"BioMediTech","und":"BioMediTech"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01905-2501","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"29627d45-a94e-46aa-b216-1cb5027f7538","pref_label":{"en":"University of Tampere (-2018)","fi":"Tampereen yliopisto (-2018)","sv":"Tammerfors universitet (-2018)","und":"Tampereen yliopisto (-2018)"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01905","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}},{"id":"15d39edf-97d7-4c85-a1e8-de866b6ed980","roles":["curator","creator"],"person":{"id":"0a0a523c-f687-4804-ba27-304d752b80b3","name":"Philipp Müller","email":"","external_identifier":"ORCID 0000-0003-4314-7339"},"organization":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"Zip file contains log-files with measurements from ChemPro100i that were used for the tests in Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'.\nBenzyl acetate (BEA data), cis-Jasmone (CIS data) and indole (IND data) were presented to IMS-based eNose ChemPro100i from syringes with two different pump rates (108 and 189 ul/hour). For each component and pump rate measurements for 10 times 10 minutes were recorded (see 'Started pumps' and 'Pumps stopped' in corresponding txt-files).\nFood scents were presented to eNose in sealed jar and on plate. For each food scent and presentation method 5 times 5 minutes were recorded (see corresponding xlsx-files).","fi":"ei","sv":"nej"},"field_of_science":[],"fileset":{"storage_service":"ida","csc_project":"2000547","total_files_count":0,"total_files_size":0},"infrastructure":[],"issued":"2018-04-18","keyword":["data"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"152c4a53-7d33-4549-bc69-218c8bb411ce","organization":"tuni.fi","admin_organization":"tuni.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:csc-kata20180418151056882791","pid_generated_by_fairdata":true,"projects":[{"id":"faef05e2-c7f1-4c61-8929-f2354d4b11b7","title":{"en":"DIGITS","fi":"DIGITS","und":"DIGITS"},"participating_organizations":[{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}],"funding":[]}],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[{"id":"954d32ae-f9e5-42f8-b166-f3dcce9f1760","url":"http://www.yso.fi/onto/koko/p69508","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"ion-mobility spectrometry","fi":"ioniliikkuvuusspektrometria","sv":"jonrörlighetsspektrometri"}},{"id":"e85413d0-02f3-4b96-bbd2-0e2881ce6acd","url":"http://www.yso.fi/onto/koko/p34109","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"measurement","fi":"mittaus","sv":"mätning"}}],"title":{"en":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'","fi":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'","sv":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'"},"created":"2019-06-27T07:10:08Z","deprecated":"2021-02-05T07:05:15Z","modified":"2026-04-16T15:05:36Z","dataset_versions":[{"id":"5e5eecec-fd69-40ab-ad44-216ceac474df","title":{"en":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'","fi":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'","sv":"Dataset for Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'"},"persistent_identifier":"urn:nbn:fi:csc-kata20180418151056882791","state":"published","created":"2019-06-27T07:10:08Z","deprecated":"2021-02-05T07:05:15Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2025-02-10T16:52:50Z","record_modified":"2026-04-16T15:05:37Z"},{"id":"9d30e6ba-d31e-4e55-860f-de9768a7af01","access_rights":{"id":"9a1b55fb-f4ab-476c-beb0-89e8c4dfe7cb","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"https://creativecommons.org/licenses/by/4.0/","url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"0a6427bb-02d8-49dc-a7e8-c1285a7f5df4","roles":["creator"],"organization":{"id":"cf7e6e4d-7b32-4e93-becf-a6561c384ac4","pref_label":{"en":"DIGITS project team"}}},{"id":"a0d83888-88a5-440d-b7ac-48be93f646ee","roles":["publisher","contributor"],"person":{"id":"de003cda-ca59-4935-9ee8-8378316c3cd9","name":"Philipp Müller","email":""},"organization":{"id":"1025824c-5798-4d94-9b93-ea3cbfc89580","pref_label":{"en":"Tampere University of Technology","fi":"Tampereen teknillinen yliopisto","sv":"Tammerfors tekniska universitet","und":"Tampereen teknillinen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/01915","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"Zip file contains log-files with measurements from ChemPro100i that were used for the tests in Muller et al. - 'Scent classification by K nearest neighbors using ion-mobility spectrometry'. Benzyl acetate (BEA data), cis-Jasmone (CIS data) and indole (IND data) were presented to IMS-based eNose ChemPro100i from syringes with two different pump rates (108 and 189 ul/hour). For each component and pump rate measurements for 10 times 10 minutes were recorded (see 'Started pumps' and 'Pumps stopped' in corresponding txt-files). Food scents were presented to eNose in sealed jar and on plate. For each food scent and presentation method 5 times 5 minutes were recorded (see corresponding xlsx-files)."},"field_of_science":[{"id":"d8354311-7dfe-45ff-86cc-67869faf332f","url":"http://www.yso.fi/onto/okm-tieteenala/ta119","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Other natural sciences","fi":"Muut luonnontieteet","sv":"Övrig naturvetenskap"}}],"fileset":{"storage_service":"ida","csc_project":"2000547","total_files_count":1,"total_files_size":7220120},"infrastructure":[],"issued":"2021-02-05","keyword":["K Nearest Neighbor","Ion-mobility spectrometry"],"language":[],"metadata_owner":{"id":"152c4a53-7d33-4549-bc69-218c8bb411ce","organization":"tuni.fi","admin_organization":"tuni.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:3f20b7b4-00ca-42d4-92d3-3f23a5e00a75","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[{"id":"954d32ae-f9e5-42f8-b166-f3dcce9f1760","url":"http://www.yso.fi/onto/koko/p69508","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"ion-mobility spectrometry","fi":"ioniliikkuvuusspektrometria","sv":"jonrörlighetsspektrometri"}}],"title":{"en":"Dataset for Muller et al. -- Scent classification by K nearest neighbors using ion-mobility spectrometry"},"created":"2021-02-05T13:30:17Z","modified":"2026-04-16T15:04:09Z","dataset_versions":[{"id":"9d30e6ba-d31e-4e55-860f-de9768a7af01","title":{"en":"Dataset for Muller et al. -- Scent classification by K nearest neighbors using ion-mobility spectrometry"},"persistent_identifier":"urn:nbn:fi:att:3f20b7b4-00ca-42d4-92d3-3f23a5e00a75","state":"published","created":"2021-02-05T13:30:17Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2025-02-10T17:21:41Z","record_modified":"2026-04-16T15:04:10Z"},{"id":"046f3be6-132c-46fe-9049-1e0d34ad7414","access_rights":{"id":"646fdc61-8d8b-4a00-8db6-49def865d439","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"https://creativecommons.org/licenses/by/4.0/","url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[],"show_file_metadata":true},"actors":[{"id":"9f56d5ff-37fb-4306-83e6-66c54f3c7b1a","roles":["creator"],"person":{"id":"61063f7c-39f6-468c-90a9-205a814d258b","name":"Dharmendra Sharma"},"organization":{"id":"69f52684-f80b-41d3-be0b-922487ac47a0","pref_label":{"en":"VTT Technical Research Centre of Finland Ltd","fi":"Teknologian tutkimuskeskus VTT Oy","sv":"Teknologiska forskningscentralen VTT Ab","und":"Teknologian tutkimuskeskus VTT Oy"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/26473754","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"af5279c8-1b7e-45ef-8376-51b684cc728e","roles":["creator"],"person":{"id":"b7f1d2cd-2a69-449a-a9cf-36e744c38c5c","name":"Pavel Davidson"},"organization":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"3d16ca94-faa8-4e80-8383-0d53c702a13a","roles":["publisher","contributor"],"person":{"id":"a148f21f-81a5-4c59-bdcc-161904a66a08","name":"Philipp Müller","external_identifier":"ORCID 0000-0003-4314-7339"},"organization":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}},{"id":"8bcc1e4e-a5a5-4723-9b9c-c01cbecca546","roles":["contributor"],"person":{"id":"43c5abf8-ffe9-41aa-83f1-68ef829b9e32","name":"Robert Piché"},"organization":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-ida","description":{"en":"All data used in Sharma et al. - \"Indirect Estimation of Vertical Ground Reaction Force from a~Body-Mounted INS/GPS Using Machine Learning\" (2021). Three CSV files that contain training dataset, test dataset 1 and test dataset 2, and one TXT file that contains column names for the CSV files."},"field_of_science":[{"id":"90fd0c26-03ee-44e0-9e1e-00633b4c768b","url":"http://www.yso.fi/onto/okm-tieteenala/ta111","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Mathematics","fi":"Matematiikka","sv":"Matematik"}},{"id":"5d9b49d9-f2d2-4841-8f5c-ef72f2017c9e","url":"http://www.yso.fi/onto/okm-tieteenala/ta222","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Other engineering and technologies","fi":"Muu tekniikka","sv":"Övrig teknik och teknologi"}},{"id":"6a5c35e3-d81b-4259-a8b3-8bad11beb0de","url":"http://www.yso.fi/onto/okm-tieteenala/ta315","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Sport and fitness sciences","fi":"Liikuntatiede","sv":"Gymnastik- och idrottsvetenskap"}}],"fileset":{"storage_service":"ida","csc_project":"2000547","total_files_count":1,"total_files_size":95758401},"infrastructure":[],"issued":"2021-02-20","keyword":["INS/GPS","insoles"],"language":[],"metadata_owner":{"id":"152c4a53-7d33-4549-bc69-218c8bb411ce","organization":"tuni.fi","admin_organization":"tuni.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:4e6d3f54-1e87-4522-a6cf-cea979e6c236","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[],"remote_resources":[],"spatial":[],"state":"published","temporal":[],"theme":[],"title":{"en":"Dataset for Sharma et al. - \"Indirect Estimation of Vertical Ground Reaction Force from a~Body-Mounted INS/GPS Using Machine Learning\""},"created":"2021-02-20T14:46:00Z","modified":"2026-04-16T14:52:14Z","dataset_versions":[{"id":"046f3be6-132c-46fe-9049-1e0d34ad7414","title":{"en":"Dataset for Sharma et al. - \"Indirect Estimation of Vertical Ground Reaction Force from a~Body-Mounted INS/GPS Using Machine Learning\""},"persistent_identifier":"urn:nbn:fi:att:4e6d3f54-1e87-4522-a6cf-cea979e6c236","state":"published","created":"2021-02-20T14:46:00Z","version":1}],"published_revision":3,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2025-02-10T17:22:53Z","record_modified":"2026-04-16T14:52:14Z"},{"id":"dc9e2348-0e64-46e7-8afd-7b054b64d59f","access_rights":{"id":"255fae0a-1521-454c-984d-ab2a91574acd","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","title":{"en":"Creative Commons Attribution (CC-BY)"},"url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"67823dbb-a204-49bb-90cc-8faf1ef6f362","roles":["creator"],"person":{"id":"ada2a285-b900-4cac-8efd-20aa6b6d22a3","name":"Karhu, Juha A. and Lindfors Anders"},"organization":{"id":"859c5fc8-4007-4f19-b04a-26aa2cd3c8c2","pref_label":{"en":"Finnish Meteorological Institute"}}},{"id":"7c8244f6-a36f-4857-8d25-7f42b2d65105","roles":["publisher"],"organization":{"id":"dc707cd4-7583-4aa0-ba10-8ff2c5672b16","pref_label":{"en":"Finnish Meteorological Institute","fi":"Ilmatieteen laitos","sv":"Meteorologiska Institutet","und":"Ilmatieteen laitos"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4940015","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-fmi","description":{"en":"The data is described in Karhu et al. (2025) (submitted to Geoscience Data Journal)\n\nPV power, ancillary and meteorological data for each PV system are organised in their respective, semicolon separated, csv-files with unique headers explaining the variables:\n\n* FMI\\_Helsinki\\_PV.csv\n* FMI\\_Kuopio\\_PV.csv\n* FMI\\_Sodankyla\\_20deg\\_PV.csv\n* FMI\\_Sodankyla\\_90deg\\_PV.csv\n\nBelow is an example how to read the datafiles to a pandas dataframe with python. Please note, that the lengths of the metadata header vary:\n\n* Helsinki and Kuopio: 67\n* Sodankylä: 93\n\n### \n\nimport pandas as pd\ndtype\\_dict = {'Remarks': str}\ndf = pd.read\\_csv('FMI\\_Sodankyla\\_20deg\\_PV.csv', sep=';', parse\\_dates=['utctime'], index\\_col=['utctime'], dtype=dtype\\_dict, header=93)\n\n### \n\nDaily plots of PV, meteorological and ancillary data are in system-specific tarballs:\n\n* Helsinki\\_daily\\_plots.tar.gz\n* Kuopio\\_daily\\_plots.tar.gz (pending)\n* Sodankyla\\_20deg\\_daily\\_plots.tar.gz (pending)\n* Sodankyla\\_90deg\\_daily\\_plots.tar.gz (pending)\n\nHourly photographs of the Sodankylä modules are in a tarball:\n\n* Sodankyla\\_module\\_images\\_2018-2021.tar.gz\n\nMetadata, additional photographs of the PV sites and their surroundings as well as data sheets and technical information of the modules and inverters can be found in a separate tarball:\n\n* siteinfo\\_and\\_metadata.tar.gz"},"field_of_science":[{"id":"7334f2e9-1aae-4b87-9088-8226211b06c9","url":"http://www.yso.fi/onto/okm-tieteenala/ta1171","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Geosciences","fi":"Geotieteet","sv":"Geovetenskaper"}}],"infrastructure":[],"issued":"2025-01-27","keyword":["photocoltaics, PV output, ancillary data, snow, quality control"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"08d36e35-a86f-4c31-bb2b-c4d97398caa1","organization":"service_fmi"},"other_identifiers":[{"notation":"http://hdl.handle.net/11304/d63abd17-c3d8-4fda-a85d-25ce80ef7b30","metax_ids":[]},{"notation":"25f5b679926d434f96fe5c0addf9cc01","metax_ids":[]}],"persistent_identifier":"doi:10.57707/fmi-b2share.25f5b679926d434f96fe5c0addf9cc01","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Dataset","fi":"Tutkimusaineisto","und":"Tutkimusaineisto"},"entity_identifier":"doi:10.57707/fmi-b2share.c7b3ec9f19324a6497639d6d8c0cde84","type":{"id":"e327ac43-4e47-43e8-9a18-cad528eeac08","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/dataset","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Dataset","fi":"Tutkimusaineisto"}}},"relation_type":{"id":"c6f0457f-cf9e-47bb-8762-6d3cc0bce29c","url":"http://www.w3.org/ns/adms#next","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Has next version","fi":"Seuraava versio"}},"metax_ids":["a13d72ca-a335-460a-9f08-131d706be440"]},{"entity":{"title":{"en":"Dataset","fi":"Tutkimusaineisto","und":"Tutkimusaineisto"},"entity_identifier":"doi:10.57707/fmi-b2share.fbe73c1d7c144ce787db3785302dd1e1","type":{"id":"e327ac43-4e47-43e8-9a18-cad528eeac08","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/dataset","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Dataset","fi":"Tutkimusaineisto"}}},"relation_type":{"id":"4ba059bd-215b-4505-bcec-5f304d66f5a8","url":"http://www.w3.org/ns/adms#previous","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Has previous version","fi":"Edellinen versio"}},"metax_ids":["d1ef320a-0cb5-4a14-9d53-21bbe9c1a96d"]}],"remote_resources":[{"title":{"en":"FMI_Helsinki_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"FMI_Kuopio_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"FMI_Sodankyla_20deg_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"FMI_Sodankyla_90deg_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"Helsinki_daily_plots.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"siteinfo_and_metadata.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"},{"title":{"en":"Sodankyla_module_images_2018-2021.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/eq3rk-6t180"}],"spatial":[],"state":"published","temporal":[{"start_date":"2015-08-25"}],"theme":[],"title":{"en":"PV production data with ancillary PV and meteorological data including solar radiation measurements from FMI's outdoor solar laboratories in Helsinki, Kuopio and Sodankylä (Finland) starting from August 2015 and ending Dec 2021"},"created":"2026-04-15T08:19:31Z","modified":"2026-04-15T08:22:30Z","dataset_versions":[{"id":"dc9e2348-0e64-46e7-8afd-7b054b64d59f","title":{"en":"PV production data with ancillary PV and meteorological data including solar radiation measurements from FMI's outdoor solar laboratories in Helsinki, Kuopio and Sodankylä (Finland) starting from August 2015 and ending Dec 2021"},"persistent_identifier":"doi:10.57707/fmi-b2share.25f5b679926d434f96fe5c0addf9cc01","state":"published","created":"2026-04-15T08:19:31Z","version":1}],"published_revision":3,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-15T08:19:31Z","record_modified":"2026-04-15T08:22:30Z"},{"id":"a13d72ca-a335-460a-9f08-131d706be440","access_rights":{"id":"7a6c3424-f0a4-4290-8ed4-85d26bc8f00b","license":[{"id":"6142d0c6-945d-4085-b9f7-81e52afa253b","custom_url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","title":{"en":"Creative Commons Attribution (CC-BY)"},"url":"http://uri.suomi.fi/codelist/fairdata/license/code/other","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other","fi":"Muu"}}],"access_type":{"id":"d01ac02c-fc70-4c68-9434-8383cb693ff0","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/open","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Open","fi":"Avoin"}},"restriction_grounds":[]},"actors":[{"id":"c6b9459e-4fe4-49e8-869d-6fda244865ec","roles":["creator"],"person":{"id":"359f2138-78e0-40f4-8d63-b74b3ba49f27","name":"Karhu, Juha A. and Lindfors Anders"},"organization":{"id":"a6df9670-4942-44af-b46d-7068e7b11069","pref_label":{"en":"Finnish Meteorological Institute"}}},{"id":"3467242c-5e0c-497d-b43c-5043feca94f8","roles":["publisher"],"organization":{"id":"dc707cd4-7583-4aa0-ba10-8ff2c5672b16","pref_label":{"en":"Finnish Meteorological Institute","fi":"Ilmatieteen laitos","sv":"Meteorologiska Institutet","und":"Ilmatieteen laitos"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/4940015","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-fmi","description":{"en":"The data is described in Karhu, J. A., A. V. Lindfors, W. Wandji Nyamsi, et al. 2026. “ Photovoltaic Power and Meteorological Datasets With Snow Detection From the Outdoor Solar Power Laboratories of the Finnish Meteorological Institute.” Geoscience Data Journal 13, no. 1: e70039. https://doi.org/10.1002/gdj3.70039.\n\nPV power, ancillary and meteorological data for each PV system are organised in their respective, semicolon separated, csv-files with unique headers explaining the variables:\n\n* FMI\\_Helsinki\\_PV.csv\n* FMI\\_Kuopio\\_PV.csv\n* FMI\\_Sodankyla\\_20deg\\_PV.csv\n* FMI\\_Sodankyla\\_90deg\\_PV.csv\n\nBelow is an example how to read the datafiles to a pandas dataframe with python. Please note, that the lengths of the metadata header vary:\n\n* Helsinki and Kuopio: 67\n* Sodankylä: 93\n\n### \n\nimport pandas as pd\ndtype\\_dict = {'Remarks': str}\ndf = pd.read\\_csv('FMI\\_Sodankyla\\_20deg\\_PV.csv', sep=';', parse\\_dates=['utctime'], index\\_col=['utctime'], dtype=dtype\\_dict, header=93)\n\n### \n\nDaily plots of PV, meteorological and ancillary data are in system-specific tarballs:\n\n* Helsinki\\_daily\\_plots.tar.gz\n* Kuopio\\_daily\\_plots.tar.gz\n* Sodankyla\\_20deg\\_daily\\_plots.tar.gz\n* Sodankyla\\_90deg\\_daily\\_plots.tar.gz\n\nHourly photographs of the Sodankylä modules are in a tarball:\n\n* Sodankyla\\_module\\_images\\_2018-2021.tar.gz\n\nMetadata, additional photographs of the PV sites and their surroundings as well as data sheets and technical information of the modules and inverters can be found in a separate tarball:\n\n* siteinfo\\_and\\_metadata.tar.gz"},"field_of_science":[{"id":"7334f2e9-1aae-4b87-9088-8226211b06c9","url":"http://www.yso.fi/onto/okm-tieteenala/ta1171","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Geosciences","fi":"Geotieteet","sv":"Geovetenskaper"}}],"infrastructure":[],"issued":"2025-06-09","keyword":["photocoltaics, PV output, ancillary data, snow, quality control"],"language":[{"id":"ec748146-3403-4a7f-adfe-bdbb1b889372","url":"http://lexvo.org/id/iso639-3/eng","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"English","fi":"englanti","sv":"engelska"}}],"metadata_owner":{"id":"08d36e35-a86f-4c31-bb2b-c4d97398caa1","organization":"service_fmi"},"other_identifiers":[{"notation":"http://hdl.handle.net/11304/9643a26b-b763-437d-9485-2b3f897a1c41","metax_ids":[]},{"notation":"c7b3ec9f19324a6497639d6d8c0cde84","metax_ids":[]}],"persistent_identifier":"doi:10.57707/fmi-b2share.c7b3ec9f19324a6497639d6d8c0cde84","pid_generated_by_fairdata":false,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Dataset","fi":"Tutkimusaineisto","und":"Tutkimusaineisto"},"entity_identifier":"doi:10.57707/fmi-b2share.25f5b679926d434f96fe5c0addf9cc01","type":{"id":"e327ac43-4e47-43e8-9a18-cad528eeac08","url":"http://uri.suomi.fi/codelist/fairdata/resource_type/code/dataset","in_scheme":"http://uri.suomi.fi/codelist/fairdata/resource_type","pref_label":{"en":"Dataset","fi":"Tutkimusaineisto"}}},"relation_type":{"id":"4ba059bd-215b-4505-bcec-5f304d66f5a8","url":"http://www.w3.org/ns/adms#previous","in_scheme":"http://uri.suomi.fi/codelist/fairdata/relation_type","pref_label":{"en":"Has previous version","fi":"Edellinen versio"}},"metax_ids":["dc9e2348-0e64-46e7-8afd-7b054b64d59f"]}],"remote_resources":[{"title":{"en":"FMI_Helsinki_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"FMI_Kuopio_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"FMI_Sodankyla_20deg_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"FMI_Sodankyla_90deg_PV.csv"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"Helsinki_daily_plots.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"Kuopio_daily_plots.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"siteinfo_and_metadata.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"Sodankyla_20deg_daily_plots.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"Sodankyla_90deg_daily_plots.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"},{"title":{"en":"Sodankyla_module_images_2018-2021.tar.gz"},"use_category":{"id":"ed5844fc-6309-4a8f-98bb-e18c1aec9fdc","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/outcome","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Outcome material","fi":"Tulosaineisto"}},"access_url":"https://fmi.b2share.csc.fi/records/238fk-zyw57"}],"spatial":[],"state":"published","temporal":[{"start_date":"2015-08-25"}],"theme":[],"title":{"en":"PV production data with ancillary PV and meteorological data including solar radiation measurements from FMI's outdoor solar laboratories in Helsinki, Kuopio and Sodankylä (Finland) starting from August 2015 and ending Dec 2021"},"created":"2026-04-15T08:22:26Z","modified":"2026-04-15T08:22:26Z","dataset_versions":[{"id":"a13d72ca-a335-460a-9f08-131d706be440","title":{"en":"PV production data with ancillary PV and meteorological data including solar radiation measurements from FMI's outdoor solar laboratories in Helsinki, Kuopio and Sodankylä (Finland) starting from August 2015 and ending Dec 2021"},"persistent_identifier":"doi:10.57707/fmi-b2share.c7b3ec9f19324a6497639d6d8c0cde84","state":"published","created":"2026-04-15T08:22:26Z","version":1}],"published_revision":1,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-15T08:22:26Z","record_modified":"2026-04-15T08:22:27Z"},{"id":"e8921c05-d34e-4715-9736-8a592f9e8e3f","access_rights":{"id":"f3b2ac03-c681-4b1d-af5f-1c67fae60055","license":[{"id":"03258502-6709-437e-9a06-5661857ea4bf","description":{"en":"The dataset is (B) available for research, teaching and study.","fi":"Aineisto on käytettävissä (B) tutkimukseen, opetukseen ja opiskeluun."},"url":"http://uri.suomi.fi/codelist/fairdata/license/code/other-closed","in_scheme":"http://uri.suomi.fi/codelist/fairdata/license","pref_label":{"en":"Other (Not Open)","fi":"Muu (Ei avoin)"}}],"access_type":{"id":"729ffd9f-6d7a-40e9-aa97-a363a16fd113","url":"http://uri.suomi.fi/codelist/fairdata/access_type/code/restricted","in_scheme":"http://uri.suomi.fi/codelist/fairdata/access_type","pref_label":{"en":"Restricted use","fi":"Saatavuutta rajoitettu"}},"restriction_grounds":[{"id":"484e859f-11b5-4163-a387-25c13fcaae29","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/research","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restriced access for research based on contract","fi":"Saatavuutta rajoitettu sopimuksen perusteella vain tutkimuskäyttöön","sv":"Begränsad åtkomst på bas av kontrakt ändast för forskningsändamål"}},{"id":"8c6eebb2-d1f7-47e9-a041-b32a172745b4","url":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds/code/education","in_scheme":"http://uri.suomi.fi/codelist/fairdata/restriction_grounds","pref_label":{"en":"Restricted access for teaching or studying based on contract","fi":"Saatavuutta rajoitettu sopimuksen perusteella opetukseen ja opiskeluun","sv":"Begränsad åtkomst på bas av kontrakt ändast för undervisning och studier"}}]},"actors":[{"id":"e8f6a616-4c5a-4040-9d2d-ab85f897aa14","roles":["creator"],"organization":{"id":"b1bd730d-68b2-46b6-9b12-57f0e46cb6fc","pref_label":{"fi":"Opetus- ja kulttuuriministeriö. Valtion nuorisoneuvosto"}}},{"id":"236b2557-dc4d-4281-8557-85baf6c24dd7","roles":["creator"],"organization":{"id":"0f778f19-437d-4780-baa7-c15c102bf382","pref_label":{"fi":"Valtion liikuntaneuvosto"}}},{"id":"86d03185-8db7-40ac-8c40-929e6efe3cf7","roles":["creator"],"organization":{"id":"9da1ec71-7d8f-4d7a-836c-649b56b1dd0d","pref_label":{"fi":"Nuorisotutkimusseura. Nuorisotutkimusverkosto"}}},{"id":"2191a767-1886-41cb-9190-824dff88deba","roles":["creator"],"organization":{"id":"b43ef51c-24f7-436d-a589-cf2eec3be3aa","pref_label":{"en":"Ministry of Education and Culture. State Youth Council"}}},{"id":"3dfd6fec-9e8d-4737-a471-a5ddfea1375d","roles":["creator"],"organization":{"id":"1e1fef6b-9fd0-4e16-93b2-5e35ef46cade","pref_label":{"en":"National Sports Council"}}},{"id":"d0edec15-7e5e-4d3d-8842-202ab3d95119","roles":["creator"],"organization":{"id":"ca603555-226f-481a-b721-c29d0d83a1a0","pref_label":{"en":"Finnish Youth Research Society. Finnish Youth Research Network"}}},{"id":"4170e005-4cfb-4e1a-b62d-d8293fe8bd92","roles":["publisher"],"organization":{"id":"24e34cd1-11fc-4777-985c-dbdd68b78c24","pref_label":{"en":"Tietoarkisto","fi":"Tietoarkisto","sv":"Tietoarkisto","und":"Tietoarkisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122-6130","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization","parent":{"id":"ea83ea7b-4d44-4d0b-b4ac-a8df3f00ae20","pref_label":{"en":"Tampere University","fi":"Tampereen yliopisto","sv":"Tammerfors universitet","und":"Tampereen yliopisto"},"url":"http://uri.suomi.fi/codelist/fairdata/organization/code/10122","in_scheme":"http://uri.suomi.fi/codelist/fairdata/organization"}}}],"cumulative_state":0,"data_catalog":"urn:nbn:fi:att:data-catalog-harvest-fsd","description":{"en":"In the interview survey Children and Youth Leisure Survey 2022, the leisure time and hobbies of people aged 7-29 were examined. In this year's survey, the main theme was the pleasantness of participation in hobbies. The interview questions differed slightly according to the age of the respondent, and a few questions were also asked of the parents of those under 15. At first, a few background questions were asked of respondents aged 15-29. For those under 15, the questions were asked of their parent. The questions concerned gender, municipality of residence, and mother tongue. After this, the amount of children's and young people's leisure time and the prevalence of participation in hobbies were examined. The prevalence of participation in hobbies was examined, for example, by asking whether the respondent had any hobbies or would like to have a hobby. If the respondent did not have any hobbies, reasons for not participating in hobbies were asked. Questions related to participation in hobbies were also asked of the parents of children under 10. Next, the respondents were asked about the hobby that took up most of their time and their most pleasant hobby. The respondents were asked to assess how different descriptions applied first to the hobby that took up most of their time and then to their most pleasant hobby, as well as how they travelled to these hobbies. After this, the respondents' views on being in nature were examined. In addition, reasons for discontinuing a pleasant guided hobby were examined. The respondents were also asked about experiences of inappropriate treatment or behaviour in hobbies. The interview also examined the respondents' views on the accessibility of hobbies. In addition, the effects of the COVID-19 period on participation in hobbies were examined using various statements. After this, respondents aged 10-29 were asked about membership of organisations and participation in organisational activities. In addition, the respondents were asked to assess their satisfaction with different areas of life. Finally, respondents aged 15-29 were asked for further background information, such as their level of education, whether they had any functional limitations, and whether they felt they belonged to a minority. The background variables in the data include age, gender, mother tongue, major regions NUTS2, type of neighbourhood, education, and economic activity.","fi":"Lasten ja nuorten vapaa-aika 2022-haastattelututkimuksessa kartoitettiin 7-29-vuotiaiden vapaa-ajan viettoa sekä harrastamista. Tämän vuoden kyselyssä pääteemana oli harrastamisen mieluisuus. Haastattelukysymykset poikkesivat toisistaan hieman haastateltavan iän mukaan, ja alle 15-vuotiaiden vanhemmille esitettiin myös muutamia kysymyksiä. Aluksi esitettiin muutama taustoittava kysymys 15-29-vuotiaille haastateltaville. Alle 15-vuotiaiden kohdalla kysymykset esitettiin hänen vanhemmalleen. Kysymykset koskivat sukupuolta, asuinpaikkakuntaa sekä äidinkieltä. Tämän jälkeen kartoitettiin lasten ja nuorten vapaa-ajan määrää ja harrastamisen yleisyyttä. Harrastamisen yleisyyttä kartoitettiin muun muassa kysymällä, onko haastateltavalla mitään harrastusta tai haluaisiko hän harrastaa jotakin. Jos haastateltava ei harrastanut mitään, kysyttiin syitä harrastamattomuudelle. Harrastamiseen liittyvät kysymykset esitettiin myös alle 10-vuotiaiden lasten vanhemmille. Seuraavaksi haastateltavilta kysyttiin heidän eniten aikaa vievästä harrastuksestaan sekä mieluisimmasta harrastuksestaan. Haastateltavia pyydettiin arvioimaan, miten eri kuvaukset sopivat ensin hänelle eniten aikaa vievään harrastukseen ja sitten mieluisimpaan harrastukseen, sekä miten he kulkevat näihin harrastuksiin. Tämän jälkeen selvitettiin haastateltavien mielipiteitä luonnossa olemisesta. Lisäksi selvitettiin syitä mieluisan ohjatun harrastuksen lopettamiselle. Haastateltavilta kysyttiin myös kokemuksia epäasiallisesta kohtelusta tai käytöksestä harrastuksissa. Haastattelussa selvitettiin myös vastaajien näkemyksiä harrastusten tavoitettavuudesta. Lisäksi selvitettiin korona-ajan vaikutuksia harrastamiseen erilaisten väittämien avulla. Tämän jälkeen 10-29-vuotiailta tiedusteltiin järjestöihin kuulumisesta ja järjestötoimintaan osallistumisesta. Lisäksi haastateltavia pyydettiin arvioimaan tyytyväisyyttään elämän eri osa-alueisiin. Lopuksi 15-29-vuotiailta kysyttiin lisää taustatietoja, kuten haastateltavan koulutustasoa, onko haastateltavalla joitakin toimintarajoitteita, sekä sitä, kokeeko hän kuuluvansa johonkin vähemmistöön. Taustamuuttujina aineistossa ovat ikä, sukupuoli, äidinkieli, suuralue, paikkakuntatyyppi, koulutus ja pääasiallinen toiminta."},"field_of_science":[{"id":"eb6d49d6-6bfc-4d8c-86b8-d9497924b295","url":"http://www.yso.fi/onto/okm-tieteenala/ta5","in_scheme":"http://www.yso.fi/onto/okm-tieteenala/conceptscheme","pref_label":{"en":"Social sciences","fi":"YHTEISKUNTATIETEET","sv":"Samhällsvetenskaper"}}],"infrastructure":[],"issued":"2026-04-07","keyword":["ajankäyttö","COVID-19","epäasiallinen kohtelu","harrastukset","hyvinvointi","fyysinen aktiivisuus","järjestötoiminta","lapset (ikäryhmät)","liikunta","luonto","nuoret","vapaa-aika","vapaa-ajantoiminnat","adolescents","children","community action","COVID-19","environment","exercise (physical activity)","harassment","hobbies","leisure time","leisure time activities","physical activities","time budgets","well-being (health)","Lapset","Nuoret","Ajankäyttö","Vapaa-aika, matkailu ja urheilu","Children","Youth","Time use","Leisure, tourism and sport"],"language":[{"id":"c757dc29-552d-48b2-9efc-4d53b939a7ef","url":"http://lexvo.org/id/iso639-3/fin","in_scheme":"http://lexvo.org/id/","pref_label":{"en":"Finnish","fi":"suomi","sv":"finska"}}],"metadata_owner":{"id":"0eabdf3f-948e-43bf-84ab-fe7b6163faaf","organization":"service_fsd"},"other_identifiers":[{"notation":"https://doi.org/10.60686/t-fsd3992","identifier_type":{"id":"753e313e-2eb1-4f81-988c-d50e7a7cd7fb","url":"http://uri.suomi.fi/codelist/fairdata/identifier_type/code/doi","in_scheme":"http://uri.suomi.fi/codelist/fairdata/identifier_type","pref_label":{"en":"Digital Object Identifier (DOI)"}},"metax_ids":[]}],"persistent_identifier":"urn:nbn:fi:fsd:T-FSD3992","pid_generated_by_fairdata":false,"projects":[],"provenance":[{"id":"09bd0be6-3d6f-472a-8331-e1aaa6643a23","title":{"en":"Collection"},"description":{"en":"Contains the date(s) when the data were collected."},"spatial":{"geographic_name":"Finland"},"temporal":{"start_date":"2022-02-09","end_date":"2022-03-24"},"is_associated_with":[],"used_entity":[],"variables":[{"id":"6b42f8c4-6f9d-44d9-99fb-8db698fbca05","pref_label":{"en":"Children and young people aged 7-29 living in mainland Finland","fi":"7-29-vuotiaat Manner-Suomessa asuvat lapset ja nuoret"}}]},{"id":"283c961f-f6ce-48fc-a05a-f4808ab6317b","title":{"en":"Production"},"description":{"en":"Date when the data collection were produced (not distributed or archived)"},"temporal":{"start_date":"2026-04-07","end_date":"2026-04-07"},"is_associated_with":[],"used_entity":[],"variables":[]},{"id":"8b0d911a-ac88-4e10-9bfa-462b0ac3ba6f","title":{"en":"Production"},"description":{"en":"Date when the data collection were produced (not distributed or archived)"},"temporal":{"start_date":"2026-04-14","end_date":"2026-04-14"},"is_associated_with":[],"used_entity":[],"variables":[]},{"id":"5813262c-e3ec-4fea-a169-dffacf9a7303","title":{"en":"Collection"},"description":{"en":"Contains the date(s) when the data were collected."},"spatial":{"geographic_name":"Suomi","reference":{"id":"684b98e8-d5c1-4a59-9247-4793cbbd38e4","url":"http://www.yso.fi/onto/yso/p94426","in_scheme":"http://www.yso.fi/onto/yso/places","pref_label":{"en":"Finland","fi":"Suomi","sv":"Finland"},"as_wkt":"POINT (27 65)"},"custom_wkt":["POINT (27 65)"],"geolocations":{"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Point","coordinates":[27.0,65.0]},"bbox":[27.0,65.0,27.0,65.0]}]}},"is_associated_with":[],"used_entity":[],"variables":[]}],"relation":[],"remote_resources":[],"spatial":[{"geographic_name":"Finland"},{"geographic_name":"Suomi","reference":{"id":"684b98e8-d5c1-4a59-9247-4793cbbd38e4","url":"http://www.yso.fi/onto/yso/p94426","in_scheme":"http://www.yso.fi/onto/yso/places","pref_label":{"en":"Finland","fi":"Suomi","sv":"Finland"},"as_wkt":"POINT (27 65)"},"custom_wkt":["POINT (27 65)"],"geolocations":{"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Point","coordinates":[27.0,65.0]},"bbox":[27.0,65.0,27.0,65.0]}]}}],"state":"published","temporal":[{"start_date":"2022-02-09","end_date":"2022-03-24"}],"theme":[],"title":{"en":"Children and Youth Leisure Survey 2022","fi":"Lasten ja nuorten vapaa-aika 2022"},"created":"2026-04-08T01:10:30Z","modified":"2026-04-15T01:11:21Z","dataset_versions":[{"id":"e8921c05-d34e-4715-9736-8a592f9e8e3f","title":{"en":"Children and Youth Leisure Survey 2022","fi":"Lasten ja nuorten vapaa-aika 2022"},"persistent_identifier":"urn:nbn:fi:fsd:T-FSD3992","state":"published","created":"2026-04-08T01:10:30Z","version":1}],"published_revision":2,"version":1,"api_version":3,"metadata_repository":"Fairdata","record_created":"2026-04-08T01:10:30Z","record_modified":"2026-04-15T01:11:21Z"}]}