0 or 3 credits
Fall 2025 Distance Learning Upper Division
This course will provide students working with quantitative data an overview of major issues in quantitative data management such as data set organization; data versioning, backup, and archiving; computer file and directory organization; data quality control, exploration, visualization and analysis; and data sharing, publication, copyright and ownership. Students will be introduced to a wide range of public databases to serve as examples of data organization, sources of reusable research data, and possible platforms for data publication. Recent trends and emerging issues in data and information science will be discussed, but the primary focus will be on encouraging students to apply critical thinking so they can develop practical strategies to their own research data issues. Accordingly, the course places a strong emphasis on active learning with theoretical lectures and discussions reinforced by applied lab sessions using tools such as Excel, R, Unix, Git, and parallel computing. Permission of department required.
Learning Outcomes1Demonstrate mastery of using a computer as their primary data management tool through online labs, a data management notebook, and discussions.
2Demonstrate mastery of efficient use of Excel, R, and Git through the online lab exercises and data management notebook.
3Demonstrate use of public data repositories in their discipline through written assignments and the final data management project.
4Demonstrate preparing dataset for publication through the online lab exercises and the final data management project.
5Demonstrate creation of a data management plan through completing a written data management plan for a specific data set.
Restrictions
made by Purdue students.