Document Your Data

Help your future self. Document your data now to understand and use it later. Documentation also enables data sharing and reuse. Data collection site, recording method, unit of measurement: these are just a few essential pieces of information about your data.

Informal Documentation

Effective data documentation does not require complex tools. A text editor or lab notebook can be used to document data. Tools, formats, and methods for data documentation can vary by discipline and even by lab or research group.

Read Me files

A Read Me is a file created using a plain text editor and saved using the name README.txt. A Read Me file is a very flexible form of documentation. It can describe the context of a project, the contents of a folder, or any other information that you will need later. Create and save a Read Me using plain text (.txt) to ensure the file is readable now and in the future.

Further resources for creating Read Me documents:

Data Dictionaries

A data dictionary describes the contents of a structured data set in a file that's separate from the data itself. Data dictionaries document necessary information for interpreting the data now and reusing the data in the future. Kristin Briney's Data Ab Initio blog includes an informative post about data dictionaries.

Templates

A template is a way to remind yourself and your research partners to record essential information about a project or data. Templates are helpful for ensuring consistency over time. You can create as many templates as you need and use them with paper and pen or with a computer. Kristin Briney's Data Ab Initio blog includes a helpful post about templates.


Formal Metadata

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.

Common descriptive metadata standards with wide adoption include:


Tools for Creating Metadata

  • Colectica for Excel
    A free Excel plug-in used to document spreadsheet data using the DDI specification
  • Extended Attributes for SAS 9.4 and higher
    A SAS Enterprise Guide add-in to describe variable attributes using the DDI specification
  • Morpho
    A KNB (Knowledge Network for Biocomplexity) application that allows scientists to describe their data sets in the EML specification and share their descriptions and data via KNB Metacat
  • Other DDI tools
    A list of metadata tools maintained by the DDI Alliance

GIS and Data Contacts

Geographic Information Systems
Rhonda Houser, Senior GIS Analyst
Watson Library
rhouser@ku.edu
785-864-1238

Research Data
Jamene Brooks-Kieffer, Data Services Librarian
Watson Library
jamenebk@ku.edu
785-864-5238

Digital Humanities
Watson Library
Institute for Digital Research in the Humanities
idrh@ku.edu