Research Data Management: Metadata

A guide to KU Libraries' services for managing and preserving research data.

Metadata Basics

Data sets should be accompanied by information that explains the data. This information is called metadata, but academic disciplines often have their own language for this information, e.g.: a survey codebook or a scientific instrument's settings and calibration.

Metadata helps organize data and facilitates data sharing, discovery and curation. Metadata is essential for re-use and preservation, answering the who, what, where, and when created for a data set.

Metadata can be created in one or more standard formats, or schema. The choice to use a formal metadata scheme is often dictated by the discipline from which the data originates. Committing to a formal scheme requires knowledge of the scheme and the tools that support its creation and use.

Metadata can also be created in nonstandard, informal formats. Research notes and lab notebooks are two examples of informal metadata. Plain text documents called Read Mes are an effective and easy way to record information about research data.


Formal Metadata

An extensive guide to disciplinary metadata standards, extensions, and tools is available at the U.K.'s Digital Curation Center.

Some common descriptive metadata standards with wide adoption include:

Informal Metadata

Examples of informal metadata that can be created during the research process include:

  • ReadMe.txt
    An introduction from the Data Ab Initio blog (K. Briney)
  • Lab Notebooks
  • Data Dictionaries
    An introduction from the Data Ab Initio blog (K. Briney)

These and other methods of creating informal metadata are accessible and relatively easy to incorporate into existing research practice.

Learn more about creating informal metadata:

Metadata Tools

Some useful tools for creating metadata for your research data include: