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Describe your data

• What kind of data do you produce or use?
  • Do you do interviews, observations or surveys? Do you produce measurement results or code, do you analyze works of art?
  • Do you use previously collected data? If so, tell us where it comes from and how you get it.
  • Raw data is often used to produce new data, e.g. transcriptions, spreadsheets, charts, visualizations, classifications or databases.
• How much space is required to store the data?
  • Gigabytes or physical space, an estimate is sufficient.
  • If your data takes up an exceptional amount of space, acquire the necessary space immediately.
  • Usually, the space already on the U drive is sufficient.
• Is there a need for special software or tools for collection, analysis or handling of the data? 
  • Reserve enough time to familiarize yourself with necessary software or tools.

Ensuring the quality of data

• How do you ensure that the raw data remains unchanged?
• How do you ensure that the data does not inadvertently change?
• How do you ensure that the data remains error-free throughout its life cycle?
• How do you ensure that the data is coherent?
• Are the risks that could jeopardize the reliability and quality of the content of the data?

Keep backups of different versions so that you can revert to a previous version if something has gone wrong if necessary. It is a good idea to store the data and the backups on the U-station, as it is a protected and itself backed up.

In order to ensure the quality and coherence of the data, it is essential to consider what may go wrong when processing the data and how these risks could be avoided. An example of a risk could be that when an interview recording is transcribed, the transcriber accidentally skips over a passage and a piece of the transcript is missing from the interview.