Whether you’ve opted to share your data publicly or you are sharing to fulfill a funder or publisher requirement, the fact of the matter is data sharing is an extra step in the research process. The best way to minimize time and resources needed for data sharing at the end of the study is to carefully document decisions every step of the way.
Document the basics
- Who contributed to the project (authors, research assistants, etc.)?
- What kinds of data and analysis were used?
- When was the data collected? When was analysis performed? Any other pertinent dates?
- Where does the project take place? Does it involve a particular geographic area, such as the state of Minnesota, or the Twin Cities, or Antarctica?
- Why is the work important? What is the impetus for the project? What questions are you trying to answer?
Imagine that you are taking over a project in the middle of the grant, but you have no way to contact the former project manager. What type of information would you need to continue successfully?
- File handling (naming convention, folder structure)
- Processing steps (how to get from point A to B)
- Protocols (what decisions were made and why)
- Field abbreviations/name glossary (what does ABC3130 stand for)
Keep documentation in one place
Download an Example Readme.txt (plain text file) template that can be adapted for your data. Update the template frequently throughout the project. The file will contain all the metadata related to your research.
Metadata is data about your data. It is searchable, descriptive information about your research data. If your metadata is incorrect or contains errors, there is the likelihood that it will be less discoverable by a search engine when you share publicly. There are certain characteristics that you should focus on when creating your metadata:
- Be specific
- Be consistent
- Be timely
- Check your spelling
- Consider concise (variable labels) versus descriptive (data collection methods) metadata fields
- Ask questions and consult experts