Open Data Badge

Description

Open Data adheres to the F.A.I.R principles, which ensure that data is Findable, Accessible, Interoperable, and Reusable. These principles make data easy to find, access, and use across different systems, and for different purposes. The application of the F.A.I.R principles increases transparency, promotes collaboration, and drives innovation in scientific research by making data from diverse sources readily usable. This not only supports reproducibility and accelerates discoveries, but also upholds the core values of open science: openness, integrity, and accessibility.

Even though not all data can be shared publicly due to ethical and privacy concerns, improving the F.A.I.R compliance of a dataset can significantly improve its internal usability – making it easier to integrate with other data, reducing the risks of loss, and increasing its reuse within your team or lab.

Requirements

To earn the Open Data badge, participants must fulfill requirements for at least one of the following options:

Option 1: Share a dataset following best practices

  1. Publish data: Make one or more dataset(s) underlying the results reported in one of your research publications or preprints available on a suitable data repository.
  2. Adhere to F.A.I.R Principles: Ensure the dataset has a persistent identifier, is accompanied by descriptive metadata, has clear license, and is organized as per community standards where possible (for instance using BIDS or NWB).
  3. Cite the Dataset(s): Cite the dataset properly in your article or preprint, including the persistent identifier to ensure traceability and recognition.

Note: For data involving human participants, ensure you have the necessary consents, Research Ethics Board approval, and that the mode of data sharing complies with these permissions.

Option 2: Improve the F.A.I.R.ness of one or more datasets within your lab

Multiple things can be done to Improve the F.A.I.R.ness of datasets without sharing openly on an online data repository. You can fulfill the requirements by completing at least one of the following actions:

  1. Implement Data Management Tools: Implement tools like Datalad for versioning and tracking data provenance.
  2. Standardize Data Organization: Reorganize a dataset according to community standards (e.g., BIDS, NWB) to facilitate future reuse.
  3. Enhance Metadata: Add detailed, structured metadata using standardized vocabularies to make the data more understandable and usable.
  4. Convert Data Formats: Change proprietary data files into open formats, making them freely accessible for future use.

Submission Checklist

All submissions go through the Open Science Bagdges Submission Form. Here is what to include in your applicaiton file depending on which Option described above you are following:

For Sharing a dataset following best practices (Option 1):

  • Include links to the dataset(s), and to the article or preprint which cite the dataset(s).
  • Include a brief description (max. 250 words) indicating how you fulfilled the requirements.

For Improving the F.A.I.R.ness of one or more datasets within your lab (Option 2):

  • Include a brief description (max. 250 words) indicating how you improved datasets in line with the F.A.I.R principles.
  • Include links, screenshots, or other proof of the work done to fulfill the requirements.

Pro Tip: If you develop code to organize, convert, or describe your data, share this code openly to further progress toward earning the Open Data Badge!

Application

Apply now using this application form to earn your first Open Science badge!