TY - JOUR
T1 - Categorizing metadata to help mobilize computable biomedical knowledge
AU - Alper, Brian S.
AU - Flynn, Allen
AU - Bray, Bruce E.
AU - Conte, Marisa L.
AU - Eldredge, Christina
AU - Gold, Sigfried
AU - Greenes, Robert A.
AU - Haug, Peter
AU - Jacoby, Kim
AU - Koru, Gunes
AU - McClay, James
AU - Sainvil, Marc L.
AU - Sottara, Davide
AU - Tuttle, Mark
AU - Visweswaran, Shyam
AU - Yurk, Robin Ann
N1 - Funding Information:
Finally, we see linkages between this work on CBK metadata and some other major initiatives. For example, the Agency for Healthcare Research and Quality evidence‐based Care Transformation Support (ACTS) initiative and the Center for Reproducible Biomedical Modeling both represent efforts at the federal level in the U.S. to advance CBK sharing in part by specifying and using CBK metadata. Also, the Fast Healthcare Interoperability Resources (FHIR) standard established by Health Level 7 International (HL7) for CBKs in the health domain is being extended to the research domain. These developments connecting CBKs across vast domains offer technical and organizational opportunities to develop common metadata frameworks across wide‐reaching CBK spaces. 72
Publisher Copyright:
© 2021 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
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U2 - 10.1002/lrh2.10271
DO - 10.1002/lrh2.10271
M3 - Article
C2 - 35036552
AN - SCOPUS:85105622676
SN - 2379-6146
VL - 6
JO - Learning Health Systems
JF - Learning Health Systems
IS - 1
M1 - e10271
ER -