A readme file is an important addition to your raw data collections. Readme files allow others to understand and reuse your data after you have submitted it to repositories by explaining the nuances of your unique data collection.
Here are a couple of examples of data records that include readme files:
- Paleosol data from Kenya deposited in UO Scholars’ Bank record
- Clinical trial mandatory reporting study data deposited in Dryad
These guidelines may help you organize and complete a readme file for your completed dataset. You’re always welcome to contact the UO data librarians for assistance with creating readme files.
- Getting Started
You can start preparing for your readme file when you start collecting your data. While collecting your data, make notes that will help you and others interpret and understand your data later. Although you might think you will remember everything about your data collection process, you might be surprised what you forget six months down the road.
- Getting Organized
Embarking on the creation of a readme file may seem daunting, but starting with a well-organized outline can help ease the process. Cornell University’s Research Data Management Service Group offers a great, concise to get you started on organizing your document.
- Completing a Readme File
Now that you have outlined what you are going to talk about in your readme file, it’s time to add the details! Fill out this form to the best of your abilities concentrating on the information in bold as this information will be the most helpful in the preservation and reuse of your data. Be thorough, yet succinct–only include information that will be helpful in understanding your data collection.
- Submitting Your Dataset and Readme File
Once you have finished preparing your dataset and readme files, you can submit them to your chosen repository. Including a readme file with your data ensures that others will be able to understand and reuse your data (with respect to copyrights and permissions) for years to come.