The analytic potential of scientific data: Understanding re‐use value
Identifieur interne : 000735 ( Main/Curation ); précédent : 000734; suivant : 000736The analytic potential of scientific data: Understanding re‐use value
Auteurs : Carole L. Palmer [États-Unis] ; Nicholas M. Weber [États-Unis] ; Melissa H. Cragin [États-Unis]Source :
- Proceedings of the American Society for Information Science and Technology [ 0044-7870 ] ; 2011.
Abstract
While problems related to the curation and preservation of scientific data are receiving considerable attention from the information science and digital repository communities, relatively little progress has been made on approaches for evaluating the value of data to inform investment in acquisition, curation, and preservation. Adapting Hjørland's concept of the “epistemological potential” of documents, we assert that analytic potential, or the value of data for analysis beyond its original use, should guide development of data collections for repositories aimed at supporting research. Three key aspects of the analytic potential of data are identified and discussed: preservation readiness, potential user communities, and fit for purpose. Based on evidence from research from the Data Conservancy initiative, we demonstrate how the analytic potential of data can be determined and applied to build large‐scale data collections suited for grand challenge science.
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DOI: 10.1002/meet.2011.14504801174
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<front><div type="abstract" xml:lang="en">While problems related to the curation and preservation of scientific data are receiving considerable attention from the information science and digital repository communities, relatively little progress has been made on approaches for evaluating the value of data to inform investment in acquisition, curation, and preservation. Adapting Hjørland's concept of the “epistemological potential” of documents, we assert that analytic potential, or the value of data for analysis beyond its original use, should guide development of data collections for repositories aimed at supporting research. Three key aspects of the analytic potential of data are identified and discussed: preservation readiness, potential user communities, and fit for purpose. Based on evidence from research from the Data Conservancy initiative, we demonstrate how the analytic potential of data can be determined and applied to build large‐scale data collections suited for grand challenge science.</div>
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