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Evaluating Data Quality: Challenges and Competencies
Imagine you’re the librarian asked to help a researcher find and use data for their project. What are your next steps to ensure no data quality problems surface? Join data librarians from Princeton (Bobray Bordelon), Stanford (Ron Nakao), and Yale (Barbara Esty) for an introduction to building competencies for understanding and evaluating data quality. Documentation is a fundamental complement to usable data. Without good documentation, data has little, if any, value. The trio will describe the data-focused reference interview, discuss different sources of data, review examples of data documentation, and offer strategies for handling incomplete or inaccurate documentation. This session will prime attendees to the challenges librarians encounter with data quality issues and provide adaptable techniques for identifying and addressing these challenges.

This webinar commences the 7 National Forum Series in Building Capacity of Academic Librarians in Evaluating Data Quality. This project is organized by West Chester University, Stanford University, and the University of Illinois at Urbana-Champaign and is made possible in part by the Institute of Museum and Library Services (RE-252357-OLS-22). Find future webinars and project details at https://sites.google.com/view/imls2022-data-quality/

Jan 26, 2023 11:00 AM in Pacific Time (US and Canada)

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