Course Description
Structuring research data, large and small, during all phases of the data life cycle, including after the project has ended so that the larger scientific community can search and reuse it as a science. The course will cover data-related issues, including standard operating procedures, quality control, security, and metadata preservation.
Athena Title
Biological Data Management
Semester Course Offered
Offered fall
Grading System
S/U (Satisfactory/Unsatisfactory)
Course Objectives
1. The ability to determine when a data management plan is needed 2. The ability to discover best practices and minimal information standards for the type of data to be generated 3. The ability to appropriately plan and execute federally mandated (NIH/NSF) data sharing plans 4. Awareness of local, community, and federal data sharing resources 5. An ability to keep data secure 6. Familiarity with common data formats, their creation and use 7. The ability to consume data from external sources and export data for external consumption
Topical Outline
1. Overview of data management: Parts of a complex data management operation. Ethical issues: Belmont report, HIPAA, and other conceptual frameworks 2. Security of data 3. Barcoding and other strategies for managing large numbers of data samples and files 4. Purpose-specific information systems: Data capture and Laboratory Information Management Systems 5. Data and metadata capture (human and ecological field capture strategies, instrument output, machine-2-machine) 6. Storage (file repositories, relational databases, naming convention, retrieval issues) 7. Quality control and quality assurance 8. Pre-processing and post-processing: Analysis pipelines, when applicable 9. Testing software (even if you did not write it): unit, integration and regression tests. Backup and recovery 10. Reproducibility of results 11. Data exchange 12. Transition: What data to preserve for the future and strategies to do it 13. Common data repositories 14. NIH and NSF Data Sharing and access policies and plans; the UGA Library and its tools for data deposition and archive 15. Final project: Create a Data Management Plan for data collection at multiple scales, preferably based on data they are generating/using as part of one of their rotations (but note: we must stress that we are not requesting students or their projects to alter how a lab has set up their data management; the focus is on the student's future data generation)