Research Data Management

Organize and name files meaningfully.

What makes sense for you:

• File type
• Date
• Type of analysis

Use file naming conventions for related files

• Be consistent
• Short yet descriptive
• Avoid spaces and special characters

Possible elements for file names:

• Project/grant name and/or number.
• Date of creation: useful for version control, e.g. YYYYMMDD
• Name of creator/investigator: last name first followed by (initials of) first name.
• Name of research team/department associated with the data.
• Description of content/subject descriptor.
• Data collection method (instrument, site, etc.).
• Version number.

Use open file formats for long term storage of data: Some file formats are less susceptible to obsolescence than others

• pick TXT over DOCX
• CSV over XSLX
• TIF over JPG

Project- & folder-level

• Create a readme file. Good example: http://hdl.handle.net/2022/17155 
• Document any data processing and analyses.
• Don’t forget written notes!

Use Readme Files

• Names + contact information for people associated with the project
• List of files, including a description of their relationship to one another
• Copyright + licensing information
• Limitations of the data
• Funding sources / institutional support
• Any information necessary for someone with no knowledge of your research to understand and / or replicate your work.
• more about Readme files from Cornell.

An Example of Readme file and metadata for a dataset in Dryad.

Readme file for this data

Metadata for the data set

http://datadryad.org/resource/doi:10.5061/dryad.jg05d