Data rescue: An assessment framework for legacy research collections

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dc.contributor.authorHoffman, Kelly M.
dc.contributor.authorClarke, Cooper T.
dc.contributor.authorShiue, Hilary Szu Yin
dc.contributor.authorNicholas, Phillip
dc.contributor.authorShaw, Miranda
dc.contributor.authorFenlon, Katrina
dc.date.accessioned2020-10-01T19:28:48Z
dc.date.available2020-10-01T19:28:48Z
dc.date.issued2020-09-30
dc.description.abstractWidespread investments in the reproducibility and reuse of scientific data have spurred an increasing recognition of the potential value of data biding in unpublished records and collections of legacy research materials, such as scientists’ papers, historical publications, and working files. Recovering usable scientific data from legacy collections constitutes one kind of data rescue: the application of selected data curation processes to data at imminent risk of loss. Given the growing interest in data-intensive science and growing movement toward computationally amenable collections in memory institutions, the National Agricultural Library and other curation institutions need systematic approaches to processing legacy collections with the specific goal of retrieving reusable or historically valuable scientific data. This white paper reports on research conducted under the auspices of the Digital Curation Fellows Program, a collaborative research initiative of the United States Department of Agriculture’s National Agricultural Library and the University of Maryland College of Information Studies. We offer a framework for assessing collections of scientific records for the purpose of data rescue, developed through research on three case studies of agricultural research collections. This framework aims to guide data rescue initiatives at the National Agricultural Library and other agricultural research centers, and to provide conceptual and practical framing for emerging conversations around data rescue in the agricultural research community and across disciplines.en_US
dc.description.sponsorshipThis white paper is the product of research conducted under a Non-Assistance Cooperative Agreement #58-8260-6-003 between the University of Maryland and the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), National Agricultural Library with funding provided by the USDA, ARS, Office of National Programs.en_US
dc.identifierhttps://doi.org/10.13016/1zmx-ghhq
dc.identifier.urihttp://hdl.handle.net/1903/26475
dc.language.isoen_USen_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md)
dc.relation.isAvailableAtDigital Repository at the University of Maryland
dc.relation.ispartofseriesDigital Curation Fellows Program;
dc.subjectdigital curationen_US
dc.subjectdata curationen_US
dc.subjectagricultureen_US
dc.subjectdata rescueen_US
dc.subjectdata reuseen_US
dc.subjectscientific research dataen_US
dc.subjectdigital preservationen_US
dc.titleData rescue: An assessment framework for legacy research collectionsen_US
dc.typeTechnical Reporten_US

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