Basic guidelines for authors

• Ensure you’ve met any ethical or legal requirements. Remove any identifying information from your data, and ensure that by releasing the data you are not breaching any prior ethical or legal agreements.
• Share as much data as possible. Your complete, reported analysis should in principle be reproducible from the data you share. Unless there is some reason why one cannot share all the data, it is often easier to simply share the entire data set.
• Do not password protect the files. For the data to be truly publicly available, they should be obtainable without interaction or permission from the authors. This does not preclude authors from placing licensing conditions on the use of the data, but requiring interaction is undesirable because if the authors are busy or unavailable the data may become difficult or impossible to obtain.
• Share data in a non-proprietary, text format. Some data formats — for instance, SPSS and SAS — cannot be opened easily by those researchers without the proprietary programs. Also, as new versions of these programs are released or as software falls out of use, old formats cease to be supported. Export your data to a text format, such as CSV.
• No “mystery meat”. All files should be accompanied by enough explanation that another person can understand the contents of the files, and how these are related to what is discussed in the paper. Simply posting your data is not enough; without sufficient explanation, the data are useless.
• Use reliable hosting. Do not use personal cloud storage providers, or personal web hosts, to host your data. These are prone to be lost as you clean or reorganize your own files, or change website hosts. Use a third party designed for this purpose, such as the Open Science Framework or a data journal/repository (see below).

Helpful resources

• PLOS recommended repositories: A great list of repositories for all sorts of data and materials
• Open science framework: Provides resources for research collaboration, including the storage of documents and data.
• Data Dryad and figshare: Online data and document repositories, designed specifically around the needs of scientific researchers.
• Data journals, such as the Journal of Open Psychology Data, offer resources for publishing data.
• Reproducibility in Science: A Guide to enhancing reproducibility in scientific results and writing
• In the UK, the UK Data Archive offers archival services for social science and economics data.
• Check with your University to see if they offer, or are planning to offer, resources for public data archiving.