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Writing a data management plan: versioning

It is important to identify and distinguish versions of research data files consistently. This ensures that a clear audit trail exists for tracking the development of a data file and identifying earlier versions when needed. Thus you will need to establish a method that makes sense to you that will indicate the version of your data files.

  • A common form for expressing data file versions is to use ordinal numbers (1,2,3 and so on) for major version changes and the decimal for minor changes, such as v1, v1.1, v2.6
  • Beware of using confusing labels: revision, final, final2, definitive_copy as you may find that these accumulate
  • Record every change irrespective of how minor that change may be
  • Discard or delete obsolete versions (whilst retaining the original 'raw' copy)
  • Use an auto-backup facility (if available) rather than saving or archiving multiple versions
  • Turn on versioning or tracking in collaborative documents or storage utilities such as Wikis or GoogleDocs.
  • Consider using version control software, like Subversion, TortoiseSVN

Some structured examples of maintaining version control[document name[ [version number] [status: draft/final]:Smith_interview_July2010_V1_DRAFTLipid-analysis-rate-V2_definitive2001_01_28_ILB_CS3_V6_AB_edited

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PILOT - Writing a data management plan by Edina, University of Edinburgh modified by Marion Kelt, GCU is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at http://datalib.edina.ac.uk/mantra/introduction.html