DataShare: Empowering researcher data curation

Abstract

Researchers are increasingly being asked to ensure that all products of research activity – not just traditional publications – are preserved and made widely available for study and reuse. Open data principles are becoming a routine matter of disciplinary best practice, and data sharing is often a precondition for publication or grant funding. More generally, the widespread adoption of good data curation practices is critical to open scientific inquiry, discourse, and advancement. With their long history in the management and dissemination of multifarious information resources, libraries can play a key role in providing scholars with the tools and services necessary for the effective long-term curation of research data, encompassing data lifecycle management, preservation, sharing, dissemination, and reuse. One such service is DataShare, a joint offering of the University of California Curation Center, the University of California, San Francisco Library and Center for Knowledge Management, and UCSF’s Clinical and Translational Science Institute. Using DataShare, faculty, staff, and student researchers at the 10 campuses of the University of California can easily: Prepare for curation by reviewing best practice recommendations for the creation or acquisition of digital research data. Select datasets for curation using intuitive file browsing and drag-and-drop interfaces. Describe their data for enhanced discoverability in terms of the DataCite metadata schema. Preserve their data by uploading to a public access collection in the UC3 Merritt curation repository. Cite their data in terms of persistent and globally-resolvable DOI identifiers. Expose their data through registration with well-known abstracting and indexing services and major internet search engines. Control the dissemination of their data through enforceable data use agreements. Discover and retrieve datasets of interest through a faceted search and browse environment. Since the widespread adoption of effective data management practices is highly dependent on ease of use and integration into existing individual, institutional, and disciplinary workflows, the emphasis throughout the design and implementation of DataShare is to provide the highest level of curation service with the lowest possible technical barriers to entry by individual researchers.

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