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Title:Relating data practices, types, and curation functions: An empirically derived framework.
Author(s):Cragin, Melissa H.; Palmer, Carole L.; Chao, Tiffany C.
Subject(s):Data curation, scientific data, scientific work practice
Abstract:We present a general conceptual framework that maps relationships and dependencies among scientific data practices, types of data produced and used, and associated curation activities. As part of the Data Conservancy initiative, the framework is being elaborated through empirical studies of data practices in the earth sciences and life science and validated against use cases as curatorial services are developed around data being prepared for ingest into the repository. The framework can be applied more broadly for identifying and representing curation requirements and to support description and assessment of existing or planned curation infrastructure and services. It will support full accounts of the data products and workflows required to maintain the coherence and context of complex data collections.
Issue Date:2010-10
Genre:Conference Poster
Peer Reviewed:is peer reviewed
Sponsor:Institute of Museum and Library Services (LG-06-07-0032-07) and National Science Foundation (0830976)
Date Available in IDEALS:2012-04-04

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