I’ve written a lot about the fundamentals of data management, usually from the viewpoint of a single researcher trying to make their data a little easier to deal with. However, a lot of research is collaborative, so it’s worth taking a little time to detail the data management practices that benefit collaborative research.

I actually co-wrote a paper a few years ago about the data management processes for a large collaborative project that I was a member of, the Data Doubles project. While a big part of the article centered on the project’s living data management plans (DMPs), I want to get explicit about some of the data management strategies that were particularly helpful:

1. Common storage
   • Collaborative research requires a common storage area where researchers can expect to find shared files. It’s important that everyone knows where this storage is and has access to it.
2. File organization
   • Shared files are even more likely to be disorganized than data files from a single researcher. It’s critical for collaborators to work out a system for organizing files so that everyone knows where data is expected to be within the storage system. A file organization system will save everyone so much time when searching for a specific file, especially if you didn’t create it yourself.
3. File naming
   • File naming is the last piece of the storage-file organization-file naming trifecta that will help files move seamlessly between collaborators. If everyone knows and uses a shared file naming convention, it becomes easy for anyone to identify files at a glance and know what data has already been collected. Have someone propose a naming scheme then refine it as a group to help get buy-in.
4. Documentation
   • I’m a big fan of having an index/inventory for data files when doing collaborative research. Of course you’ll need other project documentation like standard research notes, but an index provides a couple extra benefits: it allows for an alternate method to discover and locate data files, and allows collaborators to track the process of data collection. A spreadsheet works great for an index.
5. Permissions
   • It’s extra important in collaborative research to be clear what people can and cannot do with the project data. This might be as formal as a Data Use Agreement but could also just be a discussion about how project members should ask for permission before reusing data for other research projects.
6. Living DMP
   • The living DMP basically collects all of the above into one document to help collaborators remember data management decisions. The document should be reviewed and updated occasionally and is especially useful for onboarding new project members.
7. Data manager
   • If the project is large enough, it’s worthwhile to designate someone as the “data manager.” This person might: propose the file organization and naming systems; update the data index; draft the living DMP; remind everyone of data management strategies; and clean up disorganized data, as needed. Not every project needs a data manager, but it’s usually good to make data management someone’s responsibility or else it might be no one’s responsibility and never get done.

I’m sure there are more data management strategies that are useful for collaborative projects, but I think these are some of the most basic. What have you found helpful when managing data in collaborative research?

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