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Research Data Services

This guide was created to help researchers locate available resources for data management and sharing.

About Data Organization and Documentation

Proper organization and documentation of research data helps others access and understand your work. Learn more about best practices below or arrange a consultation

Data Organization

A logical structure of folders/files can facilitate access to research data. If you need assistance organizing your research data, please contact us at

Directory Structure 

  • Use a hierarchical folder structure to organize your data files.
  • Consult with us to create a customized folder organization scheme for your research data.
  • Electronic Lab Notebooks (ELNs) can be used to help manage your research data. Consult with us to select an appropriate ELN for your laboratory.

File Naming Conventions

  • Create meaningful, relevant to content, independent of location and brief names
  • Use underscores _ for separation
  • Use file names to classify broad types of files, i.e. .txt, .csv, .xml
  • Avoid using spaces and special characters, i.e. ~ ! # & @ ( ) { } [ ] ‘ “ | % $ ; ^
  • Avoid very long file names
  • Example: Survey21 _Smith_2015_06_01.txt is a survey in a text file with participant 21, conducted by Smith on June 1st 2015.

Version Control

  • Record version and status of a file (i.e. draft, interim, final, internal) or add ascending, decimal version numbers. For example, Survey21_Smith_2015_06_01_v1.txt is a survey of the first version in a text file with participant 21, conducted by Smith on June 1st 2015.
  • Decide how many versions and which versions of a file to keep, for how long, and how to organize versions.
  • Identify milestone and master versions of files to keep and identify a single location for the storage of milestone and master versions of files.

Data Documentation

It's important to create some form of documentation to describe your research data to those outside your research group. We recommend a simple ReadMe.txt file with the following components. If you need assistance creating data documentation, please contact us at

Components of Your Data Documentation (i.e. a ReadMe.txt file)

  • What types of data are included?
  • When, where and how your data was collected?
  • Notes about your file formats. The non-proprietary/open and unencrypted/uncompressed file formats are more likely to be accessible in the future.
    • Non-proprietary or open formats are readable by more than the device or application that generated them. Usually proprietary file formats can be converted to open formats. For example, analysis software programs like Gen5 can export data in a matrix format of a text file.
    • Unencrypted and uncompressed files: If files are encrypted and/or compressed, the method of encryption/compression used will need to be both discoverable and usable for future access. 
    • Some examples of preferred formats for various data types 
      • Still Images: TIFF, JPEG 2000, PDF, PNG, GIF, BMP
      • Text: XML, PDF/A, HTML, ASCII, UTF-8
      • Moving Images: MOV, MPEG, AVI, MXF
      • Sounds: WAVE, AIFF, MP3, MXF
      • Geospatial: SHP, BDF, GeoTIFF, NetCDF
      • Databases: XML, CSV
      • Statistics: ASCII, DTA, POR, SAS, SAV
      • Containers: TAR, GZIP, ZIP
      • Web Archives: WARC
  • Notes about protocols, standards, and any other methodologies used in your research.