This is the "Best Practices for Managing Your Data" page of the "Data Management Planning" guide.
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Data Management Planning   Tags: archiving, data_curation, digital_assets, grant_proposals, publishing, research_data  

Tips and tools of data management for researchers.
Last Updated: Mar 11, 2014 URL: Print Guide RSS UpdatesEmail Alerts

Best Practices for Managing Your Data Print Page

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Susan Borda - Digital Curation Librarian
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File Formats

Best Practices:

  • Accessible in the future, non-proprietary, commonly used by research community
  • Unencrypted and uncompressed,
  • Not proprietary use: PDF not Word, XML or RDF not RDBMS, CSV not XLS



Establish a Descriptive File and Dataset Naming Convention

A consistent convention will help you easily identify your files and what they contain. Use abbreviated descriptive information such as

  • project
  • content or parameter
  • location, date and/or time (yyyymmdd for easy sorting; hhmmssTZD for time)
  • version number (establish numbering system for versions)

Use numbers, letters, dashes, underscores. Do not use spaces or special characters. Stay concise to be practical.


Data Documentation and Metadata

Best Practices:

  • Make good use of "readme.txt" files for documenting details
  • Document:
    • Data collection methods
    • Context of data collection
    • Variable names and description
    • Algorithms used
    • Transformations of data from the raw data through analysis
    • Software and systems used for analysis
  • Use discipline specific metadata standards
  • Use a script rather than GUI during data analysis, better for documentation and makes results easier to reproduce
  • Incorporate a workflow tool such as Kepler, Taverna or VisTrails



About this guide

Acknowledgements: Sara Rutter, University of Hawaii at Manoa, for sharing her guide; UC3 (University of California Curation Center).

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

Creative Commons License


File Organization


Using Excel

Best Practices:

  • Use in conjunction with a "Data Dictionary" (similar to that listed below) containing information about:
    • Variable name
    • Variable types
    • Codes and Ranges
    • Missing values
  • Place variable names in row 1
  • Always have a unique identifier per entity
  • Keep track of changes made to worksheet
  • Format columns to matchthe variable type (date, numeric, text, etc.)
  • Data entry guidelines:
    • Freeze column headings so they will not scroll of the screen
    • Enter string variables in a consistent case
    • Do not leave any blank rows in the spreadsheet
    • Do not include unessential text or fancy formatting in the spreadsheet
    • Get rid of formulas - copy the entire spreadsheet into a new sheet using "Values" option
    • Sort data with caution (always SAVE first) 
  • Verify data using double data entry
  • Save as .csv for forward compatibility and interoperability


  • DataUp - An Excel add-in that will assist individuals in documenting and preparing Excel for archiving and sharing
  • Elliott, A C. (2006). Preparing data for analysis using Microsoft Excel. Journal of investigative medicine, 54(06), 334-341. 

Define Your Data Dictionary

Example Data Dictionary

Example from Hook, Les A., et al. 2010. Best Practices for Preparing Environmental Data Sets to Share and Archive. Available online ( from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. doi:10.3334/ORNLDAAC/BestPractices-2010


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