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General description and quality assurance of the data

tekijä: timapupu Viimeisin muutos torstai 14. maaliskuuta 2024, 12.46

This material is expired! Please go to the new and updated Research Data Management guide for students.


Related to the FAIR principles of Findable, Accessible and Re-usable.  

At the beginning of your data management plan (DMP), describe briefly

  • what kind of data you intend to collect or produce, or
  • what kind of existing data you will use, or
  • what archived data you will reuse.
For example: interviews, surveys, texts, figures, photos, measurement results, statistics, physical samples or code. 
Your data is usually not a static piece of information!
  • Layers of data. You might create something new from the original data: tables, figures and compilations. These create new layers of data.
  • Moving the data. Data are often transferred from one form or place to another. E.g. from the survey forms to analysis software or from recordings to transcriptions.

How you will ensure the coherence of your data? In other words, how do you ensure with quality assurance that the data do not accidentally change and that they remain faultless during their entire life cycle? For example:

  • Take a copy of the original data and work on the copy, not the original files, if possible.
  • Make sure the original content is preserved if data are exported from one system or place to another.
    • E.g. from the survey forms to analysis software or from recordings to transcriptions.
  • Let someone else check the transcriptions of recorded and/or filmed materials.
    • This is only possible if you work in a research group or with a thesis partner, since recorded/filmed materials contain personal data.
  • Store backup copies of different versions.
  • Verify that your digitised data correspond precisely enough to the original physical or analogue data.
  • Check the calibration of measuring equipment.
  • Use checksums if the software provides them.

Source

If you want, you can check some examples at DMP Tuuli’s public data management plans. Remember that copying is not recommended.  Note that the public plans do not follow the same framework and their content may contain gaps or errors.