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Good Data Practices

Best practices for creating reusable data publications

So, you want to share your research data in Dryad, but are unsure where to start or what you 'should' share? Don't worry, it's not always clear how to craft a dataset with reusability in mind.

We want to help you share your research with the scientific community to increase its visibility and foster collaborations. The following guidelines will help make your Dryad datasets as Findable, Accessible, Interoperable, and Reusable (FAIR) as possible.

No time to dig into the details? Check out our quickstart guide to data sharing.


Gather all relevant data needed for reanalysis

Make sure your data are shareable

Make sure your data are accessible

Preferred file formats

Dryad welcomes the submission of data in multiple formats to enable various reuse scenarios. For instance, Dryad's preferred format for tabular data is CSV, however, an Excel spreadsheet may optimize reuse in some cases. Thus, Dryad accepts more than just the preservation-friendly formats listed below.

Organize files in a logical schema

File naming

Name files and directories in a consistent and descriptive manner. Avoid vague and ambiguous filenames. Filenames should be concise, informative, and unique (see Stanford's best practices for file naming).

Avoid blank spaces and special characters (' '!@#$%^&") in filenames because they can be problematic for computers to interpret. Use a common letter case pattern because they are easily read by both machines and people:

Include the following information when naming files:

Dataset organization

Describe your dataset in a README file

Provide a clear and concise description of all relevant details about data collection, processing, and analysis in a README document. This will help others interpret and reanalyze your dataset.

Plain text README files are recommended, however, PDF is acceptable when formatting is important.

If you include a README in a compressed archive of files, please also upload it externally in the README section so that users are aware of the contents before downloading.

Cornell University's Research Data Management Service Group has created an excellent README template

Details to include:

Ready to get started? Log in and go to the "My Datasets" to begin your data submission now!

Examples of good reusability practices

Further resources