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. 2021 May 9;6(1):e10271.
doi: 10.1002/lrh2.10271. eCollection 2022 Jan.

Categorizing metadata to help mobilize computable biomedical knowledge

Brian S Alper  1 , Allen Flynn  2 , Bruce E Bray  3 , Marisa L Conte  4 , Christina Eldredge  5 , Sigfried Gold  6 , Robert A Greenes  7 , Peter Haug  8 , Kim Jacoby  9 , Gunes Koru  10 , James McClay  11 , Marc L Sainvil  12 , Davide Sottara  12 , Mark Tuttle  13 , Shyam Visweswaran  14 , Robin Ann Yurk  15
Affiliations

Categorizing metadata to help mobilize computable biomedical knowledge

Brian S Alper et al. Learn Health Syst. .

Abstract

Introduction: Computable biomedical knowledge artifacts (CBKs) are digital objects conveying biomedical knowledge in machine-interpretable structures. As more CBKs are produced and their complexity increases, the value obtained from sharing CBKs grows. Mobilizing CBKs and sharing them widely can only be achieved if the CBKs are findable, accessible, interoperable, reusable, and trustable (FAIR+T). To help mobilize CBKs, we describe our efforts to outline metadata categories to make CBKs FAIR+T.

Methods: We examined the literature regarding metadata with the potential to make digital artifacts FAIR+T. We also examined metadata available online today for actual CBKs of 12 different types. With iterative refinement, we came to a consensus on key categories of metadata that, when taken together, can make CBKs FAIR+T. We use subject-predicate-object triples to more clearly differentiate metadata categories.

Results: We defined 13 categories of CBK metadata most relevant to making CBKs FAIR+T. Eleven of these categories (type, domain, purpose, identification, location, CBK-to-CBK relationships, technical, authorization and rights management, provenance, evidential basis, and evidence from use metadata) are evident today where CBKs are stored online. Two additional categories (preservation and integrity metadata) were not evident in our examples. We provide a research agenda to guide further study and development of these and other metadata categories.

Conclusion: A wide variety of metadata elements in various categories is needed to make CBKs FAIR+T. More work is needed to develop a common framework for CBK metadata that can make CBKs FAIR+T for all stakeholders.

Keywords: FAIR principles; computable biomedical knowledge; digital objects; metadata; trust.

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Conflict of interest statement

Brian S. Alper owns Computable Publishing LLC. Mark Tuttle is on the Board of Directors for Apelon and has an equity position. Gunes Koru owns Maryland Health Information Technology LLC and Maryland Data Science and Engineering LLC. No conflicts of interest were reported by Allen Flynn, Bruce E. Bray, Marisa L. Conte, Christina Eldredge, Sigfried Gold, Robert A. Greenes, Peter Haug, Kim Jacoby, James McClay, Marc Sainvil, Davide Sottara, Shyam Visweswaran, and Robin Ann Yurk.

Figures

FIGURE 1
FIGURE 1
Available metadata by category for 12 existing CBKs found online
See this image and copyright information in PMC

References

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