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Data Curation and Data Analytics for Advancing Science and Scholarship

This presentation explores the interplay between data curation and data analytics to advance science and scholarship. It highlights the importance of developing a shared understanding of data concepts, addressing disciplinary differences, and promoting data sharing and reuse across fields. The discussion includes needs analysis for professional skills in data curation within the humanities, barriers to using preservation metadata, and the synergy achieved by aligning curation with analytics. Education programs are suggested to extend beyond traditional frameworks, fostering new specializations in socio-technical data analytics.

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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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