Research Data Management Training


TAMU Libraries offers introduction to research data management workshops for graduate students, and on-demand workshops for research labs and groups.

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Introduction to Research Data Management workshop series (Fall 2017 slides)

  1. Build an overview
  2. Collect and document data
  3. Store digital data
  4. Work with data
  5. Share and preserve data
  6. Plan ahead


Research Data Management (RDM) refers to the practices of organizing, documenting, storing, sharing, and preserving data gathered during a research project. The aim of research data management is to ensure that data are usable over time.

Effective management of digital data involves

  • Formatting data for easy analysis.
  • Quality control for integrity.
  • File organization and naming conventions for identification.
  • Documentation and version control for tracking changes and roll-back.
  • Managing storage and access locations for security and collaboration.
  • Back-up procedures for redundancy.
  • Policies for sharing and reuse.
  • Archiving and preservation for future accessibility.