Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub.
Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub.
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DOI：
10.1111/1365-2656.13388
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发表时间：
2021-09
期刊：
影响因子：
--
通讯作者：
Visser ME
中科院分区：
文献类型：
--
作者：
Culina A;Adriaensen F;Bailey LD;Burgess MD;Charmantier A;Cole EF;Eeva T;Matthysen E;Nater CR;Sheldon BC;Saether BE;Vriend SJG;Zajkova Z;Adamík P;Aplin LM;Angulo E;Artemyev A;Barba E;Barišić S;Belda E;Bilgin CC;Bleu J;Both C;Bouwhuis S;Branston CJ;Broggi J;Burke T;Bushuev A;Camacho C;Campobello D;Canal D;Cantarero A;Caro SP;Cauchoix M;Chaine A;Cichoń M;Ćiković D;Cusimano CA;Deimel C;Dhondt AA;Dingemanse NJ;Doligez B;Dominoni DM;Doutrelant C;Drobniak SM;Dubiec A;Eens M;Einar Erikstad K;Espín S;Farine DR;Figuerola J;Kavak Gülbeyaz P;Grégoire A;Hartley IR;Hau M;Hegyi G;Hille S;Hinde CA;Holtmann B;Ilyina T;Isaksson C;Iserbyt A;Ivankina E;Kania W;Kempenaers B;Kerimov A;Komdeur J;Korsten P;Král M;Krist M;Lambrechts M;Lara CE;Leivits A;Liker A;Lodjak J;Mägi M;Mainwaring MC;Mänd R;Massa B;Massemin S;Martínez-Padilla J;Mazgajski TD;Mennerat A;Moreno J;Mouchet A;Nakagawa S;Nilsson JÅ;Nilsson JF;Cláudia Norte A;van Oers K;Orell M;Potti J;Quinn JL;Réale D;Kristin Reiertsen T;Rosivall B;Russell AF;Rytkönen S;Sánchez-Virosta P;Santos ESA;Schroeder J;Senar JC;Seress G;Slagsvold T;Szulkin M;Teplitsky C;Tilgar V;Tolstoguzov A;Török J;Valcu M;Vatka E;Verhulst S;Watson H;Yuta T;Zamora-Marín JM;Visser ME
由于缺乏标准和网络规划，不同科学领域数据的整合和综合工作大大放慢和受阻。对单独标记的动物进行长期研究也不例外。这些研究对于理解野外的进化和生态过程尤为重要。此外，它们的数量和全球分布为评估模式的普遍性和解决大范围的全球问题（如气候变化）提供了独特的机会。为了解决数据整合问题，并在长期鸟类研究的基础上实现新的生态和进化研究规模，我们创建了SPI鸟类网络和数据库（www.spibirds.org），这是一个大规模的倡议，将来自个体可识别（通常是有环的）鸟类的野生种群研究的数据和研究人员联系起来。自成立以来，在一年半的时间里，SPI - Birds已经招募了120多名成员，目前拥有近150万只鸟类的数据，这些鸟类来自80个种群，累积时间超过2000年，并且还在不断增加。SPI‐Birds作为一个数据中心和研究种群的目录。它可以防止数据丢失，确保数据的查找、使用和集成，从而促进协作和综合。我们提供社区衍生的数据和元数据标准，并根据可查找、可访问、可互操作和可重用（FAIR）的原则改进数据完整性，并与现有的元数据语言（例如生态元数据语言）保持一致。鼓舞人心的社区参与源于SPI - Bird的分散方法：研究小组保留对数据使用和数据管理方式的完全控制，而SPI - Birds创建量身定制的管道，将每种独特的数据格式转换为标准格式。我们概述了吸取的经验教训，以便其他社区（例如研究其他分类群的社区）可以采用我们的成功模式。创建特定于社区的中心（如我们的，COMADRE的动物人口统计等）将有助于急需的大规模生态数据整合。SPI - Birds是一项全球规模的倡议，为多年来跟踪的独特标记个体群体收集的数据创建元数据和数据标准。作者收集了2000多年来收集的近150万只鸟类的数据。每个人都可以通过SPI - Birds数据库搜索种群并请求它们的数据。
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 (www.spibirds.org)—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. SPI‐Birds is a global‐scale initiative that creates meta‐data and data standards for data collected in populations of uniquely marked individuals that are followed over years. The authors host data on nearly 1.5 million birds collected over cumulative 2000 years. Everyone can search for populations and request their data via SPI‐Birds database.
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影响因子：
0.4
作者：
de Jong, Maaike;van den Eertwegh, Laura;Visser, Marcel E.
通讯作者：
Visser, Marcel E.
影响因子：
3.8
作者：
Delahaie B;Charmantier A;Chantepie S;Garant D;Porlier M;Teplitsky C
通讯作者：
Teplitsky C
影响因子：
2.7
作者：
Eeva, Tapio;Ruuskanen, Suvi;Laaksonen, Toni
通讯作者：
Laaksonen, Toni
影响因子：
56.9
作者：
Bay, Rachael A.;Harrigan, Ryan J.;Ruegg, Kristen
通讯作者：
Ruegg, Kristen
DOI：
10.1073/pnas.1220228110
发表时间：
2013-06-04
影响因子：
11.1
作者：
Blois, Jessica L.;Williams, John W.;Ferrier, Simon
通讯作者：
Ferrier, Simon