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Bray, Bruce E.

https://orcid.org/0000-0003-3963-2964

Mayo Clinic

University of Utah

Citations 2

Categorizing metadata to help mobilize computable biomedical knowledge
Alper, Brian S. , Flynn, Allen , Conte, Marisa , Eldredge, Christina , Gold, Sigfried , Greenes, Robert A. , Haug, Peter J. , Jacoby, Kim, Koru, Güneş , McClay, James C. , Sainvil, Marc L. , Sottara, Davide , Tuttle, Mark S. , Visweswaran, Shyam , Yurk, Robin , Conte, Marisa L , Gold, Sigfried , Koru, Gunes , McClay, James , Sainvil, Marc L , Tuttle, Mark , Visweswaran, Shyam , Yurk, Robin Ann , Alper, Brian S , Bray, Bruce E.

Learning Health Systems | May 10, 2021 | Volume: 6 | Issue: 1 | Pages: No page available

10.1002/lrh2.10271 Get It

AbstractIntroductionComputable 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.MethodsWe 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.ResultsWe 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.ConclusionA 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.
Summary of second annual MCBK public meeting: Mobilizing Computable Biomedical Knowledge—A movement to accelerate translation of knowledge into action
Richesson, Rachel , Bray, Bruce E. , Dymek, Christine , Greenes, Robert A. , McIntosh, Leslie D. , Middleton, Blackford , Perry, Gerald , Platt, Jodyn , Shaffer, C. , Richesson, Rachel L , Shaffer, Christopher

Learning Health Systems | March 2, 2020 | Volume: 4 | Issue: 2 | Pages: No page available

10.1002/lrh2.10222 Get It

AbstractThe volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community formed in 2016 to address these needs. This report summarizes the main outputs of the Second Annual MCBK public meeting, which was held at the National Institutes of Health on July 18‐19, 2019 and brought together over 150 participants from various domains to frame and address important dimensions for mobilizing CBK.