Moving Toward Findable, Accessible, Interoperable, Reusable Practices in Epidemiologic Research.
Data sharing is essential for reproducibility of epidemiologic research, replication of findings, pooled analyses in consortia efforts, and maximizing study value to address multiple research questions. However, barriers related to confidentiality, costs, and incentives often limit the extent and sp...
| Publicado en: | American Journal of Epidemiology Vol. 192; no. 6; pp. 995 - 1006 |
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| Autores principales: | , , , , , , , , , , , , , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Jun2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=164082899&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164082899 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00029262 1X1 jtl: American Journal of Epidemiology issn: 00029262 maglogo: N pubinfo: dt: Jun2023 vid: 192 iid: 6 pid: 622 pub: Oxford University Press / USA artinfo: ui: 164082899 164082899 164082899 10.1093/aje/kwad040 164082899 ppf: 995 ppct: 11 formats: tig: atl: Moving Toward Findable, Accessible, Interoperable, Reusable Practices in Epidemiologic Research. aug: au: García-Closas, Montserrat Ahearn, Thomas U Gaudet, Mia M Hurson, Amber N Balasubramanian, Jeya Balaji Choudhury, Parichoy Pal Gerlanc, Nicole M Patel, Bhaumik Russ, Daniel Abubakar, Mustapha Freedman, Neal D Wong, Wendy S W Chanock, Stephen J Gonzalez, Amy Berrington de Almeida, Jonas S sug: subj: Web Search Engines Evaluation Access to Information Evaluation Reproducibility of Results Data Management Methods Electronic Health Records Epidemiological Research Consortia Privacy and Confidentiality Metadata Application Service Provider Collaboration Cost Benefit Analysis ab: Data sharing is essential for reproducibility of epidemiologic research, replication of findings, pooled analyses in consortia efforts, and maximizing study value to address multiple research questions. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of data sharing. Epidemiological practices that follow Findable, Accessible, Interoperable, Reusable (FAIR) principles can address these barriers by making data resources findable with the necessary metadata, accessible to authorized users, and interoperable with other data, to optimize the reuse of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to remote, accessible ("Cloud") data servers, using machine-readable and nonproprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing research resources, both data and code. However, these costs are outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the reuse of precious research resources by the scientific community. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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