Sudhanvan Iyer, Kathryn Maxson Jones, Jill O Robinson, Nicole R Provenza, Dominique Duncan, Gabriel Lázaro-Muñoz, Amy L McGuire, Sameer A Sheth, Mary A Majumder
{"title":"BRAIN 计划数据共享生态系统:特点、挑战、益处和机遇。","authors":"Sudhanvan Iyer, Kathryn Maxson Jones, Jill O Robinson, Nicole R Provenza, Dominique Duncan, Gabriel Lázaro-Muñoz, Amy L McGuire, Sameer A Sheth, Mary A Majumder","doi":"10.7554/eLife.94000","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, we provide an overview and analysis of the BRAIN Initiative data-sharing ecosystem. First, we compare and contrast the characteristics of the seven BRAIN Initiative data archives germane to data sharing and reuse, namely data submission and access procedures and aspects of interoperability. Second, we discuss challenges, benefits, and future opportunities, focusing on issues largely specific to sharing human data and drawing on <i>N</i> = 34 interviews with diverse stakeholders. The BRAIN Initiative-funded archive ecosystem faces interoperability and data stewardship challenges, such as achieving and maintaining interoperability of data and archives and harmonizing research participants' informed consents for tiers of access for human data across multiple archives. Yet, a benefit of this distributed archive ecosystem is the ability of more specialized archives to adapt to the needs of particular research communities. Finally, the multiple archives offer ample raw material for network evolution in response to the needs of neuroscientists over time. Our first objective in this paper is to provide a guide to the BRAIN Initiative data-sharing ecosystem for readers interested in sharing and reusing neuroscience data. Second, our analysis supports the development of empirically informed policy and practice aimed at making neuroscience data more findable, accessible, interoperable, and reusable.</p>","PeriodicalId":11640,"journal":{"name":"eLife","volume":"13 ","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities.\",\"authors\":\"Sudhanvan Iyer, Kathryn Maxson Jones, Jill O Robinson, Nicole R Provenza, Dominique Duncan, Gabriel Lázaro-Muñoz, Amy L McGuire, Sameer A Sheth, Mary A Majumder\",\"doi\":\"10.7554/eLife.94000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper, we provide an overview and analysis of the BRAIN Initiative data-sharing ecosystem. First, we compare and contrast the characteristics of the seven BRAIN Initiative data archives germane to data sharing and reuse, namely data submission and access procedures and aspects of interoperability. Second, we discuss challenges, benefits, and future opportunities, focusing on issues largely specific to sharing human data and drawing on <i>N</i> = 34 interviews with diverse stakeholders. The BRAIN Initiative-funded archive ecosystem faces interoperability and data stewardship challenges, such as achieving and maintaining interoperability of data and archives and harmonizing research participants' informed consents for tiers of access for human data across multiple archives. Yet, a benefit of this distributed archive ecosystem is the ability of more specialized archives to adapt to the needs of particular research communities. Finally, the multiple archives offer ample raw material for network evolution in response to the needs of neuroscientists over time. Our first objective in this paper is to provide a guide to the BRAIN Initiative data-sharing ecosystem for readers interested in sharing and reusing neuroscience data. Second, our analysis supports the development of empirically informed policy and practice aimed at making neuroscience data more findable, accessible, interoperable, and reusable.</p>\",\"PeriodicalId\":11640,\"journal\":{\"name\":\"eLife\",\"volume\":\"13 \",\"pages\":\"\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2024-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"eLife\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.7554/eLife.94000\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"eLife","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.7554/eLife.94000","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities.
In this paper, we provide an overview and analysis of the BRAIN Initiative data-sharing ecosystem. First, we compare and contrast the characteristics of the seven BRAIN Initiative data archives germane to data sharing and reuse, namely data submission and access procedures and aspects of interoperability. Second, we discuss challenges, benefits, and future opportunities, focusing on issues largely specific to sharing human data and drawing on N = 34 interviews with diverse stakeholders. The BRAIN Initiative-funded archive ecosystem faces interoperability and data stewardship challenges, such as achieving and maintaining interoperability of data and archives and harmonizing research participants' informed consents for tiers of access for human data across multiple archives. Yet, a benefit of this distributed archive ecosystem is the ability of more specialized archives to adapt to the needs of particular research communities. Finally, the multiple archives offer ample raw material for network evolution in response to the needs of neuroscientists over time. Our first objective in this paper is to provide a guide to the BRAIN Initiative data-sharing ecosystem for readers interested in sharing and reusing neuroscience data. Second, our analysis supports the development of empirically informed policy and practice aimed at making neuroscience data more findable, accessible, interoperable, and reusable.
期刊介绍:
eLife is a distinguished, not-for-profit, peer-reviewed open access scientific journal that specializes in the fields of biomedical and life sciences. eLife is known for its selective publication process, which includes a variety of article types such as:
Research Articles: Detailed reports of original research findings.
Short Reports: Concise presentations of significant findings that do not warrant a full-length research article.
Tools and Resources: Descriptions of new tools, technologies, or resources that facilitate scientific research.
Research Advances: Brief reports on significant scientific advancements that have immediate implications for the field.
Scientific Correspondence: Short communications that comment on or provide additional information related to published articles.
Review Articles: Comprehensive overviews of a specific topic or field within the life sciences.