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This checklist can help you identify what to put in place for good data practices, and which actions to take to optimise data sharing.

  • Are you using standardised and consistent procedures to collect, process, check, validate and verify data?
  • Are your structured data self-explanatory in terms of variable names, codes and abbreviations used?
  • Which descriptions and contextual documentation can explain what your data mean, how they were collected and the methods used to create them?
  • How will you label and organise data, records and files?
  • Will you apply consistency in how data are catalogued, transcribed and organised, e.g. standard templates or input forms?
  • Which data formats will you use? Do formats and software enable sharing and long-term validity of data, such as non-proprietary software and software based on open standards?
  • When converting data across formats, do you check that no data or internal metadata have been lost or changed?
  • Are your digital and non-digital data, and any copies, held in a safe and secure location?
  • Do you need to securely store personal or sensitive data?
  • If data are collected with mobile devices, how will you transfer and store the data?
  • If data are held in various places, how will you keep track of versions?
  • Are your files backed up sufficiently and regularly and are back-ups stored safely?
  • Do you know what the master version of your data files is?
  • Do your data contain confidential or sensitive information? If so, have you discussed data sharing with the respondents from whom you collected the data?
  • Are you gaining (written) consent from respondents to share data beyond your research?
  • Do you need to anonymise data, e.g. to remove identifying information or personal data, during research or in preparation for sharing?
  • Have you established who owns the copyright of your data? Might there be joint copyright?
  • Who has access to which data during and after research? Are various access regulations needed?
  • Who is responsible for which part of data management?
  • Do you need extra resources to manage data, such as people, time or hardware?