Data quality is a top priority in data science and a critical aspect of data lifecycle management. Poor data quality leads to poor data-informed decisions and poor contributions to the research literature. If you work with data or researchers or teach data management, you know the importance of quality data in research.
Wei Zakharov, PhD, the leader of an NSF-funded project on data management education for undergraduates, will be your guide to identifying the characteristics of quality data, using literature-informed best practices and tools to evaluate data quality, and integrating data quality checking into your data literacy instruction. This will empower you to improve the quality of your service to researchers and students.
Through a demonstration of data quality evaluation tools, hands-on activities, lecture, and Q&A, you’ll learn how to address central issues of data quality, including data credibility, timeliness, information completeness, accuracy, consistency, and duplication. You’ll leave the session with sample datasheets and checking guides for your teaching sessions.
This webinar is an approved elective for Level II of the Data Services Specialization.
Learning Outcomes
By the end of this course, you will be able to:
- Describe what data quality is
- Explain the key dimensions of data quality
- Apply a checking guide to assess data quality as a data consumer or creator
- Integrate data quality instruction into data literacy instruction
Audience
Librarians and health information professionals who teach data management or want to improve their data quality management skills.
Presenter

Wei Zakharov, PhD, https://orcid.org/0000-0002-7805-6675, is an Associate Professor and Engineering Information Specialist in Libraries and School of Information Studies at Purdue University. Wei teaches and conducts research in data and information literacy education and technology-enhanced learning. She leads an interdisciplinary team on a three-year project funded by the National Science Foundation in 2023 aimed at prioritizing and broadly disseminating data management education for undergraduate students.
Registration Information
- Length: 1.5 hour webinar
- Register, participate, and earn 1.5 MLA continuing education (CE) contact hours.