Data management checklist

This checklist helps can help you identify best practices for data management and data sharing.

Planning

Who is responsible for which part of data management?
Are new skills required for any activities?
Do you need extra resources to manage data, such as people, time or hardware?
Have you accounted for costs associated with depositing data for longer-term preservation and access?

Documenting

Will others be able to understand your data and use them properly?
Are your structured data self-explanatory in terms of variable names, codes and abbreviations used?
Which descriptions and contextual documentation 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 be consistent in how data are catalogued?

Formatting

Are you using standardised and consistent procedures to collect, process, transcribe, check, validate and verify data, such as standard protocols, templates or input forms?
Which data formats will you use? Do formats and software enable sharing and long-term sustainability of data, such as non-proprietary software and software based on open standards?
When converting data across formats, do you check that no data, annotation or internal metadata have been lost or changed?

Storing

Are your digital and non-digital data, and any copies, held in multiple safe and secure locations?
Do you need to securely store personal or sensitive data? If so, are they properly protected?
If data are collected with mobile devices, how will you transfer and store the data?
If data are held in multiple places, how will you keep track of versions?
Are your files backed up sufficiently and regularly and are backups stored safely?
Do you know which version of your data files is the master?
Who has access to which data during and after research? Is there a need for access restrictions? How will these be managed after you are dead?
How long will you store your data for and do you need to select which data to keep and which to destroy?

Confidentiality, ethics and consent

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, for example, to remove identifying information or personal data, during research or in preparation for sharing?

Copyright

Have you established who owns the copyright in your data? Might there be joint copyright?
Have you considered which kind of license is appropriate for sharing your data and what, if any, restrictions there might be on re-use?
If you are purchasing or re-using someone else’s data sources have you considered how that data might be shareable, for example negotiating a new licence with the original supplier?
Can you preserve for the long-term, personal information so that it can be used in the future?

Sharing

Do you intend to make all your data available for sharing or how will you select which data to preserve and share?
How and where will you preserve your research data for the longer-term?
How will you make your data accessible to future users?