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Dahlgren Memorial Library

Research Data Management

Best practices and tools for managing your research data.

Best Practices for Documenting the Data Process

It is important to document your work so that others can understand what you did. Be sure to maintain records of the context of your research data, information about variables, processes involved in data cleanup and analysis, file naming schemas and directory structures, and the roles and responsibilities of project personnel.

Depending on your preferences and the needs of your research project, you can document this information using README.txt files, data dictionaries or codebooks, lab notebooks, a data narrative, or some combination of the aforementioned.

Tools for Documenting the Research Process

Best Practices for Metadata

Metadata is documentation that helps other researchers discover and cite your dataset. The term, “metadata” is also sometimes used to refer to data documentation more generally.

Ideal metadata uses standardized language to enable machine readability and interoperability with various search systems. Metadata standards vary in their complexity, and repositories often have specific metadata requirements to be submitted with your dataset.​

Become familiar with disciplinary metadata standards in your field, so that you choose the correct terminology and level of detail to describe your research.