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Guiding principles for technical infrastructure to support computable biomedical knowledge

dc.contributor.authorMcCusker, Jamie
dc.contributor.authorMcIntosh, Leslie D.
dc.contributor.authorShaffer, Chris
dc.contributor.authorBoisvert, Peter
dc.contributor.authorRyan, James
dc.contributor.authorNavale, Vivek
dc.contributor.authorTopaloglu, Umit
dc.contributor.authorRichesson, Rachel L.
dc.date.accessioned2023-07-14T13:54:55Z
dc.date.available2024-08-14 09:54:54en
dc.date.available2023-07-14T13:54:55Z
dc.date.issued2023-07
dc.identifier.citationMcCusker, Jamie; McIntosh, Leslie D.; Shaffer, Chris; Boisvert, Peter; Ryan, James; Navale, Vivek; Topaloglu, Umit; Richesson, Rachel L. (2023). "Guiding principles for technical infrastructure to support computable biomedical knowledge." Learning Health Systems 7(3): n/a-n/a.
dc.identifier.issn2379-6146
dc.identifier.issn2379-6146
dc.identifier.urihttps://hdl.handle.net/2027.42/177225
dc.description.abstractOver the past 4 years, the authors have participated as members of the Mobilizing Computable Biomedical Knowledge Technical Infrastructure working group and focused on conceptualizing the infrastructure required to use computable biomedical knowledge. Here, we summarize our thoughts and lay the foundation for future work in the development of CBK infrastructure, including: explaining the difference between computable knowledge and data, and contextualizing the conversation with the Learning Health Systems and the FAIR principles. Specifically, we provide three guiding principles to advance the development of CBK infrastructure: (a) Promote interoperable systems for data and knowledge to be findable, accessible, interoperable, and reusable. (b) Enable stable, trustworthy knowledge representations that are human and machine readable. (c) Computable knowledge resources should, when possible, be open. Standards supporting computable knowledge infrastructures must be open.
dc.publisherWiley Periodicals, Inc.
dc.publisherUniversity of Michigan
dc.subject.otherFAIR
dc.subject.othercomputable biomedical knowledge
dc.subject.otheropen systems
dc.titleGuiding principles for technical infrastructure to support computable biomedical knowledge
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBiomedical Health Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/177225/1/lrh210352_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/177225/2/lrh210352.pdf
dc.identifier.doi10.1002/lrh2.10352
dc.identifier.sourceLearning Health Systems
dc.identifier.citedreferenceNational Institutes of Health. Biomedical knowledgebase. 2020. https://grants.nih.gov/grants/guide/pa-files/PAR-20-097.html
dc.identifier.citedreferenceLin D, Crabtree J, Dillo I, et al. The TRUST principles for digital repositories. Sci Data. 2020; 7 ( 1 ): 144. doi: 10.1038/s41597-020-0486-7
dc.identifier.citedreferenceHealthcare Information and Management Systems Society. Interoperability in healthcare. 2020. https://www.himss.org/resources/interoperability-healthcare
dc.identifier.citedreferenceGuise J-M, Savitz LA, Friedman CP. Mind the gap: putting evidence into practice in the era of learning health systems. J Gen Intern Med. 2018; 33 ( 12 ): 2237 - 2239.
dc.identifier.citedreferenceWilkinson MD, Dumontier M, Aalbersberg IJ, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016; 3: 160018.
dc.identifier.citedreferenceGreenes R, Lagoze C, Figueroa B, Flynn A. Knowledge Infrastructure Requirements for Computable Biomedical Knowledge (CBK). Michigan: University of Michigan; 2018.
dc.identifier.citedreferenceRichesson RL, Bray BE, Dymek C, et al. Summary of second annual MCBK public meeting: mobilizing computable biomedical knowledge—a movement to accelerate translation of knowledge into action. Learn Health Syst. 2020; 4 ( 2 ): e10222.
dc.identifier.citedreferenceWilliams M, Richesson RL, Bray BE, et al. Summary of third annual MCBK public meeting: mobilizing computable biomedical knowledge—accelerating the second knowledge revolution. Learn Health Syst. 2020; 5: e10255.
dc.identifier.citedreferenceAbout Invest in Open Infrastructure. Invest in Open Infrastructure Initiative. 2021. https://investinopen.org/about/
dc.identifier.citedreferenceIranzo V, Pérez-González S. Epidemiological models and COVID-19: a comparative view. Hist Philos Life Sci. 2021; 43: 104. doi: 10.1007/s40656-021-00457-9
dc.identifier.citedreferencePurkayastha S, Bhattacharyya R, Bhaduri R, et al. A comparison of five epidemiological models for transmission of SARS-CoV-2 in India. BMC Infect Dis. 2021; 21: 533. doi: 10.1186/s12879-021-06077-9
dc.identifier.citedreferenceAlper BS, Flynn A, Bray BE, et al. Categorizing metadata to help mobilize computable biomedical knowledge. Learn Health Syst. 2022; 6 ( 1 ): e10271. doi: 10.1002/lrh2.10271
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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