top of page

EarthCube FAIR Initiative

Image by trail

The FAIR Principles for Geoscience Data and Code


The EarthCube Office (ECO) is working to develop community capacity around the production of FAIR data and the implementation of FAIR principles for other research objects such as scientific software. The FAIR Principles are guidelines for improving the value of research data (and code) by making it more “Findable, Accessible, Interoperable, and Reusable.” Building on the EC Leadership Council’s work to promote the FAIR Data and Resources for the Geoscience Community, we are developing tutorials and informational briefings to help the community improve the FAIRness of EarthCube-related data, tools, and services.

The FAIR Principles for Geoscience Data and Code

What is FAIR?


The FAIR Guiding Principles (Wilkinson et al, 2016) provide a frame for considering the state of human and machine readability of a dataset or resource, and the related metadata.


The FAIR Principles identify practices that reach across the data lifecycle, and include possible actions for researchers, data managers and stewards, as well as repositories of all types, to make data (or related) objects and resources *more* FAIR. That is, when assessing a data object or resource through this frame, the Principles should be considered on a continuum, that is a means toward full Findability – Accessibility – Interoperability – Reusability.


There are several key aspects that are core to FAIR operations:

  • Findability requires unique, persistent identifiers, and these are registered or indexed to support search.

    • Data are described with rich metadata (Note that specific standards are not defined in the Principles; selection choices are left up to designated communities or domains to meet its particular needs.)

  • Accessibility requires services that utilize Persistent Identifiers for retrieval, and that support authentication,  authorization, and controls for data usage license restrictions when needed. Service providers can also indicate the extent to which their underlying protocols are open and universally implementable.

    • The Principles specifically state that Metadata Records should persist, even if the data they describe are no longer available. (This provides continuity and persistence of the scientific record.)

  • Interoperability requires the application of formal and accessible knowledge representation tools; those tools (such as standard vocabularies or ontologies) should also follow the FAIR principles

  • Re-usability calls for the use of clear and accessible data usage licenses; and, that metadata include information on source and changes (provenance)


What FAIR is not: The FAIR Principles are silent on “open science” or “open data,” as well as on data quality. It should be noted that data that are compliant with the FAIR Principles and found to be FAIR can also be of poor quality, biased, or falsified. The FAIR community acknowledges that data may be “open as possible, as closed as necessary.” Data may be private, confidential, or proprietary, and under the FAIR Principles this is OK – especially when the aim is for metadata to be complete, fully available, and machine readable. Finally, successful application of the FAIR data principles is not, as yet, easily measured, though many tools are in development.

Image by Olivier Miche
What is FAIR?

FAIR for EarthCube


FAIR-related materials created for the community by the EarthCube Office will be added here first!

Image by Annie Spratt
FAIR for EarthCube



  • provides resources for the broader FAIR and data communities. A recent webinar covered effective Data Access Statements – scroll to “FAIRPoints_Point_4.”

  • FAIRsFAIR in the EU provides a searchable library of FAIR training materials covering a range of topics for different stakeholder groups.

  • The EarthCube Research Coordination Network project "What about Model Data?" has scheduled a workshop at the University of North Dakota, Grand Forks, on July 25-27, 2022. The workshop will focus on tackling open issues in preservation, sharing, and curation of data and software from research that utilizes simulations. 


Stay tuned for more on FAIR!


For questions or topic suggestions, please contact the EarthCube Office at:

bottom of page