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Research Data Management

Introductory information and links for deeper investigation on research data management topics. Guide 3 of a 3-part series.

Ohio University OIT's Data Storage by Type Tips

This page ( is intended to guide those decisions based on common data types and available centrally managed IT services. It is not intended to be a complete or comprehensive catalog of IT services available at Ohio University. Should you have any questions about appropriate storage or sharing solutions please consult with the Information Security Office.

Reference our Storing Data by Type Table to see which service can store specific data types.

Data Organization and Storage Tips

Collect and Organize Data from the Start

  • Use good naming scheme for your files
  • Organize files logically and uniformly
  • Use spreadsheets thoughtfully, add details!
  • Use an appropriate metadata scheme throughout the project

Use the 3-2-1 method:

  • Have 3 copies of your work
  • On 2 different types of media
  • With at least 1 remote copy

File Naming Matters: Do Not Rely on File Nesting

Don’t rely on nesting in folder --- 2016/fall/project/data/script.R
Be descriptive

  • Bad: notes.docx
  • Better: pubh6646_notes.docx
  • Best: infolit_pubh6646_notes.docx

Use numerical dates -- YYYYMMDD rather than Aug15   

  • Avoid file names with UPPERcase letters, weird characters (/,#?), or spaces between words

Use consistent structure that falls into useful order (for sorting) and decide if shared terminology is necessary. List versions alphanumerically

  • Bad: draft, finaldraft, reviseddraft
  • Better: v1, v2, v3
  • Best: v01, v02, v03

screenshot of file nesting

Additional Guidelines for Naming and Describing your Data:

Attributable: signed, dated, any changes attributed
Legible: can be easily read and understood
Contemporaneous: data recorded immediately as generated
Original: original data, or if not original, location of the original source is included and accuracy confirmed
Accurate: clean, objective recording including all contextual and explanatory information


Best practice: an uncompressed, non-proprietary version of data files. For example:

For this...

Use this...

Not this...


.pdf, .txt, .html





Tabular Data





.wmv, .arf, .mov


Back up does not equal preservation because of these:

  • Media Failure
  • Software Obsolescence
  • Bit-level corruption

Consider a data repository for long-term preservation of your data and think about your data security needs and requirements.