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|a 0309672759
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|a 9780309672757
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|a Casola, Linda Clare
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|a Planning for long-term use of biomedical data
|h Elektronische Ressource
|b proceedings of a workshop
|c Linda Casola, rapporteur ; Board on Mathematical Sciences and Analytics, Committee on Applied and Theoretical Statistics ; Computer Science and Telecommunications Board, Division on Engineering and Physical Sciences ; Board on Life Sciences, Division on Earth and Life Studies ; Board on Research Data and Information, Policy and Global Affairs, The National Academies of Sciences, Engineering, Medicine
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|a Washington, DC
|b The National Academies Press
|c [2020], 2020
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|a 1 PDF file (xiv, 78 pages)
|b illustrations
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|a Includes bibliographical references
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|a National Academies of Sciences, Engineering, and Medicine (U.S.)
|b Committee on Applied and Theoretical Statistics
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|a National Academies of Sciences, Engineering, and Medicine (U.S.)
|b Computer Science and Telecommunications Board
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|a National Academies of Sciences, Engineering, and Medicine (U.S.)
|b Board on Life Sciences
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|a National Academies of Sciences, Engineering, and Medicine (U.S.)
|b Board on Research Data and Information
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|2 ISO 639-2
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|b NCBI
|a National Center for Biotechnology Information
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|u https://www.ncbi.nlm.nih.gov/books/NBK558227
|3 Volltext
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|a Biomedical research data sets are becoming larger and more complex, and computing capabilities are expanding to enable transformative scientific results. The National Institutes of Health's (NIH's) National Library of Medicine (NLM) has the unique role of ensuring that biomedical research data are findable, accessible, interoperable, and reusable in an ethical manner. Tools that forecast the costs of long-term data preservation could be useful as the cost to curate and manage these data in meaningful ways continues to increase, as could stewardship to assess and maintain data that have future value. The National Academies of Sciences, Engineering, and Medicine convened a workshop on July 11-12, 2019 to gather insight and information in order to develop and demonstrate a framework for forecasting long-term costs for preserving, archiving, and accessing biomedical data. Presenters and attendees discussed tools and practices that NLM could use to help researchers and funders better integrate risk management practices and considerations into data preservation, archiving, and accessing decisions; methods to encourage NIH-funded researchers to consider, update, and track lifetime data; and burdens on the academic researchers and industry staff to implement these tools, methods, and practices. This publication summarizes the presentations and discussion of the workshop
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