Data Quality Assurance Practices in Research Data Repositories, Sponsored by SIG-STI
Data quality assurance (DQA) is fundamental to facilitating research data sharing and reuse, significantly impacting research reproducibility, transparency, and credibility. Despite the extensive literature on research data curation, there is a notable absence of theory-guided evaluations of DQA practices within research data repositories (RDRs). This webinar will present on a study that addresses this gap. The study involved a thorough analysis of the literature, 12 DQA-related standards and knowledge tools, 122 Core Trustworthy Data Repositories Certification applications, and 32 interviews with RDR curators and managers. The core of the presentation will be a DQA ontology (DQAO) that is grounded in the study’s findings and conceptualizes DQA activities and their structure within RDRs. This ontology provides a framework for predicting, evaluating, intervening in, and communicating data quality issues.
Presenters
Dr. Besiki Stvilia is a Professor in the School of Information at Florida State University. He received his M.S. and Ph.D. in Library and Information Science from the University of Illinois at Urbana-Champaign and his M.S. in Applied Mathematics from Tbilisi State University, Georgia. His primary research interests are information and data quality assurance, digital data curation, research information management, and social informatics. In particular, he studies collaborative work organization and data practices in various communities and develops models for information and data management, dynamics, and intervention.
Dr. Dong Joon Lee is an Associate Professor in the Department of Information and Operations Management at the Mays Business School. He holds a Ph.D. in Information Studies from the School of Information, Florida State University, an M.S. in Information Management from the University of Washington, and a B.S. in Computer Information Systems from Grove City College. Dr. Lee’s research interests span several areas, including the core values and benefits of socio-technical information systems (such as research information management systems and digital asset management systems), information and data quality, and information organization tools (such as metadata design, identifiers, linked data, and ontologies).
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