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Research Data Management: Overview

Research data is loosely defined as information collected, observed, or created for purposes of analysis to produce original research. This guide provides resources for managing your research data no matter the discipline.

Quick Data Management Checklist

1. Plan

Begin planning for data management when your research project starts – and assign data management responsibilities to team members early on. Many research groups, and the organizations who fund them, standardize this process by writing a data management plan.

2. Organize

Name and organize data according a schema (preferably an established data and metadata standard).

3. Document

Document your data, metadata, variables, and other contextual information that would help someone understand and interpret the data (e.g., data dictionaries, READMEs, etc).

4. Store

Keep original data files, use version control, and back up data in multiple locations. Learn more about data storage options.

5. Secure

Know your data's risk. Secure data appropriately and adhere to Yale data security policies based on your data’s classification status, which can be determined with this questionnaire. In addition, review Yale's Research Data and Materials Policy.

6. Validate

Assess for data validity and quality.

7. Share

Where appropriate, share data. Yale considers data sharing a "key precept of the University." Learn more about data reuse and reproducibility, data citation, data repositories, data use agreements, and other sharing resources.