Data Management Plans

1. To ensure your data is accessible for the long-term, consider saving a copy of your data in a non-proprietary, commonly-accessible format.

2. Keep a record of how you produced the data and store it in a text file in the same directory as the data.

3. Use a folder/directory structure with a clear, documented naming scheme.

4. Use naming conventions for your files. If you need to rename a batch of files, there are several tools that can assist.

5. Remember: Lots of Copies Keeps Stuff Safe! Keep 3 copies of your data in geographically distributed locations.

Describe the format of your data and how it will be "documented". Think about what details someone else would need to be able to use these files. For example, you may need a "readme file" to explain variables, structure of the files, etc. (This type of information is commonly referred to as "metadata").

Consider these questions:

• Which file formats will you use for your data, and why?
• What form will the metadata describing/documenting your data take?
• How will you create or capture these details?
• Which metadata standards or best practices will you use and why have you chosen them? (e.g. accepted domain-local standards, widespread usage)
• What contextual details (metadata) are needed to make the data you capture or collect meaningful?

Metadata is the descriptive information about your data, which is crucial to enabling the analysis and re-creation of experiments. Metadata includes information collected during the creation of the data (i.e. the instrumentation being used, date the data was collected, who collected the data, etc.) and the standard information needed for others to retrieve and reuse the data. Metadata standards vary by discipline.