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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.

Contents:

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:

Examples

A) Organized by File type

DatasetA.tar.gz
|- Data/
|  |- Processed/
|  |- Raw/
|- Results/
|  |- Figure1.tif
|  |- Figure2.tif
|  |- Models/
|- README.md

B) Organized by Analysis

DatasetB.tar.gz
|- Figure1/
|  |- Data/
|  |- Results
|  |  |- Figure1.tif
|- Figure2/
|  |- Data/
|  |- Results/
|  |  |- Figure2.tif
|- README.md

Describe your dataset in a README file

Provide a clear and concise description of all components of your dataset in a README document. This will help others interpret and reanalyze your data.

We provide a README template in Markdown format to guide you through the creation of your README documentation.

If your dataset includes compressed archives, please upload your README externally as a stand-alone file in the 'Data' category so that users can view its contents before downloading the full dataset.

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