Essentially, FAIR and open data practices means that research data (including e.g. code and physical samples) are well managed throughout the data life cycle, according to the FAIR principles, and are shared publicly under the maxime „as open as possible, as closed as necessary“.

In practice, for researchers this includes:

• Depositing research outputs (e.g., data, software, physical sample information, etc.) in trustworthy, community-accepted, FAIR-aligned repositories.
• Fully documenting each data set in the metadata, which may include descriptive information about the context, quality and condition, or characteristics of the data.
• Citation of data, software, and other products created or reused for your research in your publications.
• Including a data availability statement in your journal publications.
• Preparing, using, and updating data management plans.
• Educating colleagues in practices that enable open and FAIR research outputs.
• Supporting development of open and FAIR standards and practices in your institutions and organizations, in academic societies, and in scholarly publishing as authors, reviewers, and editors.

Institutions, academic societies and community networks may support FAIR and open data practices by:

• Providing regular education and outreach to their communities regarding these principles and practices.
• Promoting open and FAIR data activities as important criteria in promotion, awards, and honors.
• Providing other credit and recognition for researchers that are following open and FAIR data practices and encourage others to include such recognition as part of regular career advancement.

  

_{The text for bullet points draws strongly from the Enabling FAIR Data „Commitment Statement in the Earth, Space, and Environmental Sciences“.}