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dc.contributor.authorKhan, Huda
dc.contributor.authorCaruso, Brian
dc.contributor.authorCorson-Rikert, Jon
dc.contributor.authorDietrich, Dianne
dc.contributor.authorLowe, Brian
dc.contributor.authorSteinhart, Gail
dc.date.accessioned2011-05-25T16:55:00Z
dc.date.available2011-05-25T16:55:00Z
dc.date.issued2010-12
dc.identifier.urihttps://hdl.handle.net/1813/22945
dc.descriptionPaper presented at the 6th International Conference on Digital Curation. December 6-8, 2010. Chicago, IL.en_US
dc.description.abstractIn disciplines as varied as medicine, social sciences, and economics, data and its analysis are an essential part of researchers’ contributions to their respective fields. While sharing research data for review and analysis presents new opportunities for furthering research, capturing this data in digital form and providing the digital infrastructure for sharing data and metadata pose several challenges. This paper reviews the motivations behind and design of the Data Staging Repository (DataStaR) platform that targets specific portions of the research data curation lifecycle (Higgins, 2008): data and metadata capture and sharing prior to publication and publication to permanent archival repositories. The goal of DataStaR is to support both the sharing and publishing of data while at the same time enabling metadata creation without imposing additional overhead for researchers and librarians (Steinhart, 2010). Furthermore, DataStaR is intended to provide cross-disciplinary support by being able to integrate different domain-specific metadata schemas according to researchers’ needs. DataStaR’s strategy of a usable interface coupled with metadata flexibility allows for a more scaleable solution for data sharing, publication and metadata reuse.en_US
dc.description.sponsorshipThis material is based upon work supported by the National Science Foundation under Grant No. III- 0712989. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.en_US
dc.language.isoen_USen_US
dc.subjectdata curationen_US
dc.subjectdata repositoryen_US
dc.subjectmetadataen_US
dc.subjectsemantic weben_US
dc.titleDataStaR: Using the Semantic Web approach for Data Curationen_US
dc.typearticleen_US


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