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Data Management Plan Guide

Learn how to write a data management plan!

Step 1. Identify your research data

The first thing we need to do before we write our plan is to make a data inventory. Our inventory will need to account for the different types of research data that the project will collect and create. We'll need to think about how we're going to save the data (file formats), which programs will be used (file types), and what data will be collected and produced.

While the complete inventory will not be in the plan it may be helpful to create a list that you can reference. 

Writing prompts

What kind of data be you be creating or collecting?
Examples: Spatial, temporal, observational, experimental, survey responses, etc.


How will the data be collected?
Examples: recorded interviews, surveys, models, sensors, image analysis, DNA sequencing, word counts, camera traps, etc.
How will the data be encoded and formatted? (i.e. file types and file formats)
Example file types: text, spreadsheets, databases, digital images, sound files, digital video, computer code, algorithms, etc.
Example file formats: PDF (portable document format), .csv (comma separated values), .docx (Microsoft Word), .txt (plain text), etc.



  • A good effort should be made to use open file formats over proprietary formats. Not only will it increase your data's shelf life, it will also make data preservation and sharing much easier. 
  • A database is a tool to organize data but it can really complicate data reuse. If you plan to create a database you will need to consider how others will be able to access and export data from it.

For more information and examples see:

Step 1 Example: Jazz songs from the 1930's

Example data identification blurb:

This project will create spreadsheets of word frequencies found in jazz songs from the 1930's. For each song a plain text document containing a transcript of the lyrics will be generated and stored as a .txt file. Word counts for each song analyzed will be recorded in spreadsheets, one for each song. Another spreadsheet will contain the details about each of the songs that were analyzed (such as year written, singer, producer, etc.). A final spreadsheet will combine the word counts from all of the songs analyzed. The spreadsheets will be saved as both Microsoft Excel and .csv files.


  • .txt is a plain text (no formatting) file type for all types of text (including code and prose).
  • .csv is a plain text file used to store tabular (spreadsheet) data. Each column value is separated by a comma which is why it is called CSV (Comma Separated Values).




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