Connecting the data landscape of long-term ecological studies : The SPI-Birds data hub

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Culina , A , Adriaensen , F , Bailey , L D , Burgess , M D , Charmantier , A , Cole , E F , Eeva , T , Matthysen , E , Nater , C R , Sheldon , B C , Saether , B-E , Vriend , S J G , Zajkova , Z , Adamik , P , Aplin , L M , Angulo , E , Artemyev , A , Barba , E , Barisic , S , Belda , E , Bilgin , C C , Bleu , J , Both , C , Bouwhuis , S , Branston , C J , Broggi , J , Burke , T , Bushuev , A , Camacho , C , Campobello , D , Canal , D , Cantarero , A , Caro , S P , Cauchoix , M , Chaine , A , Cichon , M , Cikovic , D , Cusimano , C A , Deimel , C , Dhondt , A A , Dingemanse , N J , Doligez , B , Dominoni , D M , Doutrelant , C , Drobniak , S M , Dubiec , A , Eens , M , Erikstad , K E , Espin , S , Farine , D R , Figuerola , J , Gulbeyaz , P K , Gregoire , A , Hartley , I R , Hau , M , Hegyi , G , Hille , S , Hinde , C A , Holtmann , B , Ilyina , T , Isaksson , C , Iserbyt , A , Ivankina , E , Kania , W , Kempenaers , B , Kerimov , A , Komdeur , J , Korsten , P , Kral , M , Krist , M , Lambrechts , M , Lara , C E , Leivits , A , Liker , A , Lodjak , J , Magi , M , Mainwaring , M C , Mand , R , Massa , B , Massemin , S , Martinez-Padilla , J , Mazgajski , T D , Mennerat , A , Moreno , J , Mouchet , A , Nakagawa , S , Nilsson , J-A , Nilsson , J F , Norte , A C , van Oers , K , Orell , M , Potti , J , Quinn , J L , Reale , D , Reiertsen , T K , Rosivall , B , Russell , A F , Rytkonen , S , Sanchez-Virosta , P , Santos , E S A , Schroeder , J , Senar , J C , Seress , G , Slagsvold , T , Szulkin , M , Teplitsky , C , Tilgar , V , Tolstoguzov , A , Torok , J , Valcu , M , Vatka , E , Verhulst , S , Watson , H , Yuta , T , Zamora-Marin , J M & Visser , M E 2021 , ' Connecting the data landscape of long-term ecological studies : The SPI-Birds data hub ' , Journal of Animal Ecology , vol. 90 , no. 9 , pp. 2147-2160 . https://doi.org/10.1111/1365-2656.13388

Title: Connecting the data landscape of long-term ecological studies : The SPI-Birds data hub
Author: Culina, Antica; Adriaensen, Frank; Bailey, Liam D.; Burgess, Malcolm D.; Charmantier, Anne; Cole, Ella F.; Eeva, Tapio; Matthysen, Erik; Nater, Chloe R.; Sheldon, Ben C.; Saether, Bernt-Erik; Vriend, Stefan J. G.; Zajkova, Zuzana; Adamik, Peter; Aplin, Lucy M.; Angulo, Elena; Artemyev, Alexandr; Barba, Emilio; Barisic, Sanja; Belda, Eduardo; Bilgin, Cemal Can; Bleu, Josefa; Both, Christiaan; Bouwhuis, Sandra; Branston, Claire J.; Broggi, Juli; Burke, Terry; Bushuev, Andrey; Camacho, Carlos; Campobello, Daniela; Canal, David; Cantarero, Alejandro; Caro, Samuel P.; Cauchoix, Maxime; Chaine, Alexis; Cichon, Mariusz; Cikovic, Davor; Cusimano, Camillo A.; Deimel, Caroline; Dhondt, Andre A.; Dingemanse, Niels J.; Doligez, Blandine; Dominoni, Davide M.; Doutrelant, Claire; Drobniak, Szymon M.; Dubiec, Anna; Eens, Marcel; Erikstad, Kjell Einar; Espin, Silvia; Farine, Damien R.; Figuerola, Jordi; Gulbeyaz, Pinar Kavak; Gregoire, Arnaud; Hartley, Ian R.; Hau, Michaela; Hegyi, Gergely; Hille, Sabine; Hinde, Camilla A.; Holtmann, Benedikt; Ilyina, Tatyana; Isaksson, Caroline; Iserbyt, Arne; Ivankina, Elena; Kania, Wojciech; Kempenaers, Bart; Kerimov, Anvar; Komdeur, Jan; Korsten, Peter; Kral, Miroslav; Krist, Milos; Lambrechts, Marcel; Lara, Carlos E.; Leivits, Agu; Liker, Andras; Lodjak, Jaanis; Magi, Marko; Mainwaring, Mark C.; Mand, Raivo; Massa, Bruno; Massemin, Sylvie; Martinez-Padilla, Jesus; Mazgajski, Tomasz D.; Mennerat, Adele; Moreno, Juan; Mouchet, Alexia; Nakagawa, Shinichi; Nilsson, Jan-Ake; Nilsson, Johan F.; Norte, Ana Claudia; van Oers, Kees; Orell, Markku; Potti, Jaime; Quinn, John L.; Reale, Denis; Reiertsen, Tone Kristin; Rosivall, Balazs; Russell, Andrew F.; Rytkonen, Seppo; Sanchez-Virosta, Pablo; Santos, Eduardo S. A.; Schroeder, Julia; Senar, Juan Carlos; Seress, Gabor; Slagsvold, Tore; Szulkin, Marta; Teplitsky, Celine; Tilgar, Vallo; Tolstoguzov, Andrey; Torok, Janos; Valcu, Mihai; Vatka, Emma; Verhulst, Simon; Watson, Hannah; Yuta, Teru; Zamora-Marin, Jose M.; Visser, Marcel E.
Other contributor: University of Helsinki, Organismal and Evolutionary Biology Research Programme
Date: 2021-09
Language: eng
Number of pages: 14
Belongs to series: Journal of Animal Ecology
ISSN: 0021-8790
DOI: https://doi.org/10.1111/1365-2656.13388
URI: http://hdl.handle.net/10138/335439
Abstract: The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database ()-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.
Subject: birds
data standards
database
FAIR data
long&#8208
term studies
meta&#8208
research network
CLIMATE-CHANGE
CLUTCH-SIZE
GREAT TITS
SELECTION
POPULATIONS
PERSONALITY
EVOLUTION
RESPONSES
ALTER
1181 Ecology, evolutionary biology
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