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Research Data Management

Introductory information and links for deeper investigation on research data management topics.

Research Data Management

What is Research Data Management?

Research Data Management (or RDM) describes the organization, storage, preservation, and sharing of data collected and used in a research project. Good RDM practices involve planning and managing around and through the entire data lifecycle of your project (from collection to preservation).

Learn about best practices in RDM:

  • Research Data Management: A Primer by Carly Strasser via NISO. This primer covers the basics of research data management, with the goal of helping researchers and those that support them become better data stewards. (**This document and author provided much of the inspiration and information throughout this guide.)
  • Data Management General Guidance from DMPTool - Excellent overall guidance, as well as links to file renaming tools, and some details on metadata (data documentation),
  • Managing and Sharing Data: Best Practices for Researchers from the UK Data Archive - A detailed forty page document aimed at the UK researcher, but with valuable recommendations, especially around formatting and storing all types of data.
  • Briney, Coates, & Goben. (2020). "Foundational Practices of Research Data Management," Research Ideas & Outcomes. - Includes suggestions on naming conventions and version control.
  • Flanders & Muñoz. An Introduction to Humanities Data Curation. Digital Humanities Data Curation. - Includes basics for humanities scholars and a section on "Unique Features of Humanities Data Curation.

Rethinking Research Data

Kristin Briney, PhD, explains why research practices should adapt and adopt the pop culture sentiment, "Pics or it didn't happen."