CREATE & MANAGE DATA
PLANNING FOR SHARING
DATA MANAGEMENT CHECKLIST
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?