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The site of the MotoR project is Learning and Educational Technology Research Lab (LET), University of Oulu (https://www.oulu.fi/let/). The MotoR multimodal process data set is collected to study secondary school students’ situational motivation and socially shared regulation of learning during a collaborative learning task.\n\nResearch design and data sources\nThe MotoR research design was structured around a multidisciplinary learning period that was part of the students’ biology and chemistry studies. The collaborative science task (described in detail later on) was completed at the University of Oulu in the LeaF research infrastructure (http://www.oulu.fi/leaf-eng), which is a classroom-like learning and research space. MotoR data set consists of video, electrodermal activity (EDA), questionnaire, repeated situational self-report, and interview data. \n\nBefore the data collection, students answered a questionnaire about motivation and motivation regulation in relation to biology and chemistry studies. Viljaranta & Tuominen’s (2018) expectancy-value-cost questionnaire, and Wolters & Benzon’s (2013) motivation regulation strategies questionnaire were revised, resulting in 35 items on expectancies, task values, and costs, and 26 items on motivation regulation strategies. In addition, background information, such as name, age, gender, and class, was asked. \n\nWhile working on a collaborative task, the students filled out repeated situational self-reports five times: once at the beginning (1), three times during (2-4), and once at the end (5) of the task. The repeated situational self-report measured individual situational appraisals of the expectancy for success, task values, and costs in relation to the group assignment. The seven expectancy-value-cost statements were modified from the Finnish translations of the expectancy-value-cost instruments (Viljaranta & Tuominen, 2018; Tuominen, 2013) used in prior studies (Gaspard et al., 2015; 2017; Juntunen et al., 2022). In addition, individuals’ situational appraisal of actualized group-level motivation regulation during the group assignment was measured with one statement in the last four repeated situational self-reports (2-5). The statement of motivation regulation was developed based on the contextualized SAGA instrument (Volet, 2001). At the beginning and the end of the task, students’ appraisals of group assignments were measured with 24 revised items of the contextualized SAGA instrument (Volet, 2001).\n\nThe students’ collaborative working was video recorded to observe their socially shared regulation of learning (SSRL). At the time, three groups were present in the learning and research space, each group in their own separate room. Each group's collaboration was videotaped with one camera, one group microphone located either in the ceiling or at the table, and with personal microphones. Altogether, the observational data included 38 hours of video, with the learning sessions’ mean duration being 90 minutes.\n\nShimmer 3 GSR+ sensors (Realtime Technologies Ltd, Dublin, Ireland) were used to record students’ electrodermal activity with the sampling rate of 128hz. The data of each group member was synchronized with the video recording based on timestamps. First, the data was visually inspected and EDA recordings indicating a missing contact of the electrode were removed from the data set. The EDA data was further processed with the Ledalab toolbox (Benedek & Kaernbach, 2010). First, large artifacts were corrected manually using spline interpolation. Butterworth low pass filter with frequency 0.5 and order 5 was then used to remove small movement artifacts from the signal. Signal was decomposed into phasic and tonic components using Continuous Decomposition Analysis. Non-specific skin conductance responses with minimum amplitude of 0.01μS were detected from the signal (Dawson et al., 2017).\n\nStimulated recall interviews were conducted directly after the completion of the collaborative science task. Each participant was interviewed individually. The interviews were video recorded, and one interview lasted from ten to twenty minutes. The interview included two parts. The first part included questions about the student’s general feelings about the group assignment. The second part considered motivation & regulation during the group assignment. First, students were asked to describe what they think motivation is and how it can be affected. Next, the interview moved on to the stimulus phase, in which the student was presented with visualizations derived from self-reported data filled out during the task. The interviewer asked reasons for students’ initial levels of expectancy for success, values, and costs as well as reasons for the changes in those motivational appraisals during the group assignment.\n\nThe groups’ task performance was evaluated with an evaluation rubric, developed by the science teachers, throughout the task by the observing researcher. The rubric criteria were scored separately for each task phase. Additionally, in the stimulated recall interviews, the students were asked to grade their groups’ working on a scale from 1-10.\n\nParticipants\n95 8th-grade students from one upper secondary school in Oulu, Finland, participated in this study. The participants were between the ages of 13 and 16, with an average of 14,17 years (SD = .585), from which 40 students were female (42,11 %) and 51 students were male (53,68 %). One participant did not want to define their gender, and three participants did not document their gender. Additionally, five participants did not define their age. The students came from six classrooms, and they were divided into 31 small groups (five groups of two, 19 groups of three, and seven groups of four). \n\nCollaborative science task\nThe students did a collaborative science task which was designed in collaboration with the school’s science teachers. The collaborative science task was a part of a bigger multidisciplinary learning period, including both biology and chemistry. The collaborative science task was also graded, and the grade counted as a part of the whole grade from the bigger multidisciplinary learning period. In the learning task, the students needed to purify water with everyday utensils, such as a plastic bottle, coffee filters, sand, and gravel. Further, the collaborative science task had different phases: air sparging (phase 1), precipitation (phase 2), observation (phase 3), and filtration (phase 4). During air sparging (phase 1), the students shook the water bottle with dirty water for 30 seconds after which they poured the dirty water into a beaker and then from one beaker to another ten times. During precipitation (phase 2), the students added potassium alum to the dirty water and mixed it continuously for five minutes. In the observation phase (phase 3), the students observed the mixture for twenty minutes writing down their observations every five minutes. During filtration (phase 4), the students built a water filter with everyday supplies, cleaned the filter by pouring one to two liters of clean water through the filter, and after that filtered the mixture of dirty water and potassium alum. No detailed instructions on how to perform the phases were given to the students. Instead, the students had learned the principles of purifying water at the school before the collaborative science task occurred, and every group member had studied to become an expert on one of the task phases. In case the students did not know how to proceed with the task, or one expert was missing, the students were provided with an advice card that guided them through that particular task phase. Also, the students continued examining the purified water at school in their biology class as a part of the multidisciplinary learning period after they completed the learning task during the data collection. \n\nReferences:\n\nGaspard, H., Dicke, A., Flunger, B., Schreier, B., Häfner, I., Trautwein, U., et al. (2015). More value through greater differentiation: Gender differences in value beliefs about math. Journal of Educational Psychology, 107, 663–677.\n\nGaspard, H., Häfner, I., Parrisius, C., Trautwein, U., & Nagengast, B. (2017). Assessing task values in five subjects during secondary school: Measurement structure and mean level differences across grade level, gender, and academic subject. Contemporary Educational Psychology, 48, 67-84.\n\nJuntunen, H., Tuominen, H., Viljaranta, J., Hirvonen, R., Toom, A., & Niemivirta, M. (2022). Feeling exhausted and isolated? The connections between university students’ remote teaching and learning experiences, motivation, and psychological well-being during the COVID-19 pandemic. Educational Psychology. doi: 10.1080/01443410.2022.2135686\n\nTuominen, H. (2013). Julkaisematon oppiainekohtaisten arvostusten mittarin käännös. Helsingin yliopisto.\n\nViljaranta, J., & Tuominen, H. (2018). Oppiaineiden arvostukset: tärkeää, hyödyllistä, kiinnostavaa vai kuormittavaa [Task values: important, useful, interesting, or costly]. In K. Salmela-Aro (Ed.), Motivaatio ja oppiminen, pp. 101–122. Juva: PS-kustannus.\n\nVolet, S.E. (2001). Significance of cultural and motivational variables on students' appraisals of group work. In F. Salili, C.Y. Chiu, & Y.Y. Hong (Eds). Student Motivation: The Culture and Context of Learning (ch15) (pp. 309-334). New York: Plenum.\n\nWolters, C. A., & Benzon, M. B. (2013). Assessing and predicting college students' use of strategies for the self-regulation of motivation. 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The larval areas have been modelled with Gaussian processes, a species distribution modelling approach, and they are based on larval survey data collected in 2007-2014 in the VELMU project. The spatial resolution of the map is 50 m and it is in raster format (GeoTIFF). The map is suitable for marine and coastal spatial planning. The modelled map gives an overview of the extent and spatial distribution as well as the production potential of the larval production areas of Baltic herring in the Finnish coastal areas. It can be used for marine spatial planning of the coastal zone. The map is not suitable for local larval production estimates.","fi":"Kartassa on kuvattu kevätkutuisen silakan poikasten esiintymisalueet (perustuen 4-9 mm pituisten pienpoikasten runsaushavaintoihin) Suomen rannikolla. Poikasten esiintymisalueet on mallinnettu Gaussisella prosessimallilla vuosina 2007–2014 kerättyjen kalaspoikashavaintojen ja paikkatietomuodossa olevien ennustemuuttujien perusteella. Aineiston laskentaresoluutio on 50 m ja se on rasterimuotoinen (GeoTIFF). \n\nMallinnuksessa käytetyt ennustemuuttujat ovat rannikkoalueen maantieteellisiä ominaisuuksia yleistäviä, joten karttamalli ei sovellu yksittäisten lisääntymisalueiden arviointiin. Mallinnuskartta antaa yleiskuvan kevätkutuisen silakan poikasten esiintymisalueiden laajuudesta ja sijainnista Suomen rannikkoalueella. Kartoitushavaintoja ja karttamallia voidaan käyttää tarkempien kenttäkartoitusten suunnittelussa. \n\nSilakkapoikasmallin perusteella pienpoikasten esiintyminen painottuu sisälahtien ja -saariston ulkopuolelle ja siellä on syytä huomioida, että merivirrat saattavat kuljettaa poikasia kauaksi kutualueista. Poikasmallin tulokset eivät siis anna tarkka kuvaa kutualueiden sijainnista rannikolla.","sv":"Kartan visar yngelproduktionsområdena för strömming (4–9 mm långa småyngel) på Finlands kust. Yngelproduktionsområdena har modellerats med gaussiska processer utifrån fiskyngelobservationer som samlats in åren 2007–2014 och prognosvariabler i geodataformat. Materialets spatiella upplösning är 50 m och det är i rasterformat (GeoTIFF). Kartan lämpar sig för allmän beskrivning av fiskarnas förökningsområden samt för planering av användningen och vården av kustområden. Kartan ger en översiktlig bild av omfattningen och läget av strömmingens yngelproduktionsområden och volymen av strömmingens yngelproduktion i Finlands kustområde. Den kan användas som kompletterande uppgift bl.a. vid planering och planläggning av kustzonen eftersom kunskaper om förökningsområdena underlättar planeringen av användningen och skyddet av kustområdet. 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Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. Moreover, the developed methodology enables linking of the total production potential across the whole distribution area to fisheries stock assessment and management.","fi":"Productive fisheries are strongly linked to the ecological state of the essential habitats. In this study, we developed a methodology to assess the most important reproduction habitats of fish by using larval survey data and Bayesian species distribution models that predict the spatial distribution and abundance of fish larvae. Our case study with four commercially and ecologically important fish species in the coastal zone of the northern Baltic Sea demonstrated that the production of fish stocks can be concentrated to an extremely limited area compared with the entire suitable production area. The area suitable for larval production varied from 3.7% to 99.8% among species, but the smallest area responsible for 80% of the cumulative larval production was two to five times more limited, varying from 1.4% to 52.9% among species. Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. Moreover, the developed methodology enables linking of the total production potential across the whole distribution area to fisheries stock assessment and management.","und":"Productive fisheries are strongly linked to the ecological state of the essential habitats. In this study, we developed a methodology to assess the most important reproduction habitats of fish by using larval survey data and Bayesian species distribution models that predict the spatial distribution and abundance of fish larvae. Our case study with four commercially and ecologically important fish species in the coastal zone of the northern Baltic Sea demonstrated that the production of fish stocks can be concentrated to an extremely limited area compared with the entire suitable production area. The area suitable for larval production varied from 3.7% to 99.8% among species, but the smallest area responsible for 80% of the cumulative larval production was two to five times more limited, varying from 1.4% to 52.9% among species. Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. 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The larval areas were modelled with Gaussian processes, a species distribution modelling approach, and are based on larval survey data collected in 2009 – 2011 in the Intersik project. The spatial resolution of the map is 100 m and it is in raster format (GeoTIFF). The map is suitable for marine and coastal spatial planning. The modelled map gives an overview of the extent and spatial distribution of the larval production areas of vendace in the Gulf of Bothnia. It can be used for marine spatial planning of the coastal zone. The map is not suitable for local larval production estimates.","fi":"Kartassa on kuvattu merikutuisen muikun todennäköiset poikastuotantoalueet Selkämerellä, Merenkurkussa ja Perämerellä. Lisääntymisalueet on mallinnettu Gaussisella prosessimallilla vuosina 2009–2011 kerättyjen poikashavaintojen ja paikkatietomuodossa olevien ennustemuuttujien perusteella. Aineiston laskentaresoluutio on 300 m ja se on rasterimuotoinen (GeoTIFF). \n\nKartta soveltuu antamaan yleiskuvan muikun poikastuotantoalueiden laajuudesta ja sijainnista Selkämerellä, Merenkurkussa ja Perämerellä. Sitä voidaan käyttää rannikkovyöhykkeen suunnittelun, kaavoituksen yms. lisätietona, mutta kartta ei sovellu yksittäisten lisääntymisalueiden arviointiin.","sv":"Kartan beskriver de sannolika yngelproduktionsområdena för siklöja sik i Bottenhavet, Kvarken och Bottenviken. Förökningsområdena har modellerats med gaussiska processer utifrån yngelobservationer och prognosvariabler i geodataformat som samlats in åren 2009-2011. Uppgiften om förekomsten av yngel av siklöja användes för att generalisera resultaten för hela havsområdet. Med hjälp av dataprogram för geodata beräknades variabler som beskriver strandområdets geografiska, klimatiska och kemiska egenskaper som förenades med yngelobservationer med en matematisk modell. Med hjälp av modelleringen kunde man ta fram en modell som beskriver sannolikheten för förekomsten av fiskyngel i kustområdena. Materialets spatiella upplösning är 100 m och det är i rasterformat (GeoTIFF). Kartan lämpar sig för allmän beskrivning av fiskarnas förökningsområden samt för planering av användningen och vården av kustområden. Kartan ger en översiktlig bild av omfattningen och läget av siklöjans yngelproduktionsområden i Bottenhavet, Kvarken och Bottenviken. Den kan användas som kompletterande uppgift bl.a. vid planering och planläggning av kustzonen eftersom kunskaper om förökningsområdena underlättar planeringen av användningen och skyddet av kustområdet. Kartan lämpar sig inte för exakta utredningar av förökningsområdena på lokal nivå."},"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"}}],"infrastructure":[],"issued":"2011-10-31","keyword":["kala","kalanpoikaset","merialueet","muikku","lisääntymisalueet"],"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":"e12c5b27-e77c-4742-a994-1feaa2aedf78","organization":"luke.fi","admin_organization":"luke.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:dbe2fa92-0154-4ccb-aa85-cb6bffc59828","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Vanhatalo, Veneranta, Hudd: Species distribution modeling with Gaussian processes: A case study with the youngest stages of sea spawning whitefish (Coregonus lavaretus L. s.l.) larvae","fi":"Vanhatalo, Veneranta, Hudd: Species distribution modeling with Gaussian processes: A case study with the youngest stages of sea spawning whitefish (Coregonus lavaretus L. s.l.) larvae"},"entity_identifier":"https://doi.org/10.1016/j.ecolmodel.2011.12.025","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":"Veneranta, Hudd, Vanhatalo: Reproduction areas of sea-spawning coregonids reflect the environment in shallow coastal waters","fi":"Veneranta, Hudd, Vanhatalo: Reproduction areas of sea-spawning coregonids reflect the environment in shallow coastal waters"},"entity_identifier":"https://doi.org/10.3354/meps10169","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":"Veneranta, L., Hudd, R. & Vanhatalo, J. 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Paikkatieto-ohjelmistojen avulla laskettiin ranta-alueen maantieteellisiä, ilmastollisia ja kemiallisia ominaisuuksia kuvaavia muuttujia, jotka yhdistettiin poikashavaintoihin matemaattisella mallilla. Aineiston laskentaresoluutio on 300 m ja se on rasterimuotoinen (GeoTIFF). \n\nMallinnettu karttataso kertoo yleiskuvan merikutuisen siian poikastuotantoalueiden laajuudesta ja sijainnista Selkämerellä, Merenkurkussa ja Perämerellä. Sitä voidaan käyttää rannikkovyöhykkeen suunnittelun, kaavoituksen yms. lisätietona, mutta kartta ei sovellu yksittäisten lisääntymisalueiden arviointiin.","sv":"Kartan beskriver de sannolika yngelproduktionsområdena för havslekande sik i Bottenhavet, Kvarken och Bottenviken. Förökningsområdena har modellerats med gaussiska processer utifrån yngelobservationer som samlats in åren 2009–2011 och prognosvariabler i geodataformat. Uppgiften om förekomsten av sikyngel användes för att generalisera resultaten för hela havsområdet. 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The larval areas have been modelled with Gaussian processes, a species distribution modelling approach, and they are based on larval survey data collected in 2007-2014 in the VELMU project. The spatial resolution of the map is 50 m and it is in raster format (GeoTIFF). The map is suitable for marine and coastal spatial planning. The modelled map gives an overview of the extent and spatial distribution as well as the production potential of the larval production areas of pikeperch in the Finnish coastal areas. It can be used for marine spatial planning of the coastal zone. The map is not suitable for local larval production estimates.","fi":"Kartassa on kuvattu kuhan pienpoikasten (pituus tavallisesti 5-15 mm, ka 6,6 mm) esiintymisalueet Suomen rannikolla. Alueet on mallinnettu Gaussisin prosessein vuosina 2007–2014 kerättyjen kalanpoikashavaintojen ja paikkatietomuodossa olevien ennustemuuttujien perusteella. 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Den kan användas som kompletterande uppgift bl.a. vid planering och planläggning av kustzonen eftersom kunskaper om förökningsområdena underlättar planeringen av användningen och skyddet av kustområdet. Kartan lämpar sig inte för exakta utredningar av förökningsområdena på lokal nivå."},"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"}}],"infrastructure":[],"issued":"2015-08-31","keyword":["kala","kalanpoikaset","lisääntymisalueet","saaristot","kuha"],"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":"e12c5b27-e77c-4742-a994-1feaa2aedf78","organization":"luke.fi","admin_organization":"luke.fi"},"other_identifiers":[],"persistent_identifier":"urn:nbn:fi:att:fe9bcc31-087a-492e-9d47-bfc62f64c2e6","pid_generated_by_fairdata":true,"projects":[],"provenance":[],"relation":[{"entity":{"title":{"en":"Kallasvuo, Vanhatalo, Veneranta: Modeling the spatial distribution of larval fish abundance provides essential information for management","fi":"Kallasvuo, Vanhatalo, Veneranta: Modeling the spatial distribution of larval fish abundance provides essential information for management. 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Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. Moreover, the developed methodology enables linking of the total production potential across the whole distribution area to fisheries stock assessment and management.","fi":"Productive fisheries are strongly linked to the ecological state of the essential habitats. In this study, we developed a methodology to assess the most important reproduction habitats of fish by using larval survey data and Bayesian species distribution models that predict the spatial distribution and abundance of fish larvae. Our case study with four commercially and ecologically important fish species in the coastal zone of the northern Baltic Sea demonstrated that the production of fish stocks can be concentrated to an extremely limited area compared with the entire suitable production area. The area suitable for larval production varied from 3.7% to 99.8% among species, but the smallest area responsible for 80% of the cumulative larval production was two to five times more limited, varying from 1.4% to 52.9% among species. Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. Moreover, the developed methodology enables linking of the total production potential across the whole distribution area to fisheries stock assessment and management.","und":"Productive fisheries are strongly linked to the ecological state of the essential habitats. In this study, we developed a methodology to assess the most important reproduction habitats of fish by using larval survey data and Bayesian species distribution models that predict the spatial distribution and abundance of fish larvae. Our case study with four commercially and ecologically important fish species in the coastal zone of the northern Baltic Sea demonstrated that the production of fish stocks can be concentrated to an extremely limited area compared with the entire suitable production area. The area suitable for larval production varied from 3.7% to 99.8% among species, but the smallest area responsible for 80% of the cumulative larval production was two to five times more limited, varying from 1.4% to 52.9% among species. Hence, instead of the traditional approach of modeling only habitat suitability for fish production, marine spatial planning and management should take into account the areal production potential. Moreover, the developed methodology enables linking of the total production potential across the whole distribution area to fisheries stock assessment and management."},"entity_identifier":"https://doi.org/10.1139/cjfas-2016-0008","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":[{"title":{"en":"Kuhan mallinnetut poikastuotantoalueet Suomen rannikolla / VELMU"},"use_category":{"id":"4e5917ef-0c64-4940-8e2f-75b9632a9cc2","url":"http://uri.suomi.fi/codelist/fairdata/use_category/code/publication","in_scheme":"http://uri.suomi.fi/codelist/fairdata/use_category","pref_label":{"en":"Publication","fi":"Julkaisu"}},"download_url":"https://kartta.luke.fi/geoserver/velmu/wms?service=WMS&version=1.3.0&request=GetCapabilities"}],"spatial":[{"geographic_name":"Suomen rannikko"}],"state":"published","temporal":[{"start_date":"2007-01-01","end_date":"2014-12-31"}],"theme":[{"id":"efa245a5-bf8b-4bbd-b02b-812d88f6b42a","url":"http://www.yso.fi/onto/koko/p71087","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"spawning beds","fi":"kutupaikat (lisääntymisalueet)"}},{"id":"cfc55788-ace2-40e8-ac57-b257e9f8974f","url":"http://www.yso.fi/onto/koko/p36038","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"pike-perch","fi":"kuha","sv":"gös"}},{"id":"7e62dd2b-f1c6-4c83-a8e8-b230edba1b74","url":"http://www.yso.fi/onto/koko/p30549","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"archipelagoes","fi":"saaristot","sv":"skärgårdar"}},{"id":"e91aa72a-c209-469f-bbf8-fbf30dac1256","url":"http://www.yso.fi/onto/koko/p35463","in_scheme":"http://www.yso.fi/onto/koko/","pref_label":{"en":"fishes","fi":"kalat (selkärankaiset)","sv":"fiskar (djur)"}}],"title":{"en":"The modelled larval production areas of pikeperch in the Finnish coastal area / VELMU","fi":"Kuhan mallinnetut poikastuotantoalueet Suomen rannikolla / VELMU","sv":"Modellerade yngelproduktionsområden för gös längs Finlands kust / VELMU"},"created":"2022-12-21T05:34:24Z","modified":"2024-04-15T09:57:06Z","dataset_versions":[{"id":"a1f3fb34-1cfa-42ff-9845-d1192622aacb","title":{"en":"The modelled larval production areas of pikeperch in the Finnish coastal area / VELMU","fi":"Kuhan mallinnetut poikastuotantoalueet Suomen rannikolla / VELMU","sv":"Modellerade yngelproduktionsområden för gös längs Finlands kust / VELMU"},"persistent_identifier":"urn:nbn:fi:att:fe9bcc31-087a-492e-9d47-bfc62f64c2e6","state":"published","created":"2022-12-21T05:34:24Z","version":1}],"published_revision":1,"version":1,"api_version":2,"metadata_repository":"Fairdata","record_created":"2025-02-10T18:35:45Z","record_modified":"2025-02-10T18:35:46Z"}]}