File names and a simple hierarchy will make files easier to locate. Set up conventions for your project, document them for all team members and be consistent!
Creative Commons Attribution 4.0 (CC BY)
Adapted from the University of British Columbia's "Organize"
Without description, data is hard to understand and use. Make your data FAIR (findable, accessible, interoperable, reusable) by describing it with metadata (data about data). Metadata is sometimes captured through deposit in data repositories, but you can also prepare data dictionaries, codebooks and README files to further describe and contextualize your work.
README files are plain text documents that sit at the top level of project folders and describe the purpose of the project, contact details, and organization of files. Including a README with your work helps ensure that future users will understand the data, any terms, and more.
README files should include:
For more information about writing README files for data, Cornell University has a comprehensive guide and template.
Metadata standards or schemas consist of specific elements used to describe or document your data. Some disciplines have established metadata standards. In addition, some data repositories have their own standards. There are also several general purpose schemas that you can adapt to fit your needs. Below are some metadata standards:
Metadata Concept Map by Amanda Tarbet is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
(Adapted from Queen's University Research Data Management LibGuide)