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Data Curation and Data Analytics for Advancing Science and Scholarship

Data Curation and Data Analytics for Advancing Science and Scholarship. Carole Palmer & Cathy Blake Center for Informatics Research in Science & Scholarship. GSLIS Research Showcase 9 April 2011. D isciplinary differences, focus on small science

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Data Curation and Data Analytics for Advancing Science and Scholarship

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  1. Data Curation and Data Analytics for Advancing Science and Scholarship Carole Palmer & Cathy Blake Center for Informatics Research in Science & Scholarship GSLIS Research Showcase 9 April 2011

  2. Disciplinary differences, focus on small science • Supporting sharing and reuse across fields • Informing infrastructure and policy Data Conservancy Data Concepts • No shared understanding of basic concepts • Need for common nomenclature • Developing a formal logic-based framework Data Curation in the Humanities Data Practices • Data levels • Identity and change in digital objects • Needs analysis of professional skills Sample related projects • Appraisal of “career” data collections • Barriers to using preservation metadata

  3. Socio-technical Data Analytics (SoDA)

  4. Synergy between curation and analytics Going forward in research . . . tighter association between two areas - data curation informs data analytics - results of data analytics informs collection and curation of data. Education programs . . . extend specializations beyond data curation masters and PhD to begin programs in socio-technical data analytics

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