SPARC is FAIR

FAIR Data Principles

High-level principles designed to make data Findable, Accessible, Interoperable and Reusable (FAIR) for both humans and machines. The principles encompass 15 guidelines designed to improve the usability of digital data. More details can be found at the GO FAIR initiative . In conjunction with the UCSD FAIR Data Informatics Lab, SPARC is adopting these principles, e.g., the use of persistent identifiers, FAIR vocabularies, and community standards to ensure that SPARC data is FAIR.

What is FAIR data?

FINDABLE: rich metadata with explicit data identifiers that are searchable in a registry or index

ACCESSIBLE: open protocols with unique identifiers; metadata available even after data is not

INTEROPERABLE: represent knowledge with FAIR-approved terminology

REUSABLE: sustainable metadata that complies with SPARC data sharing standards

SPARC is FAIR

SPARC is an established data repository designed in accordance with best practices according to the FAIR (https://doi.org/10.1038/sdata.2016.18) and TRUST (https://doi.org/10.1038/s41597-020-0486-7) principles.

SPARC is one of the few neuroscience-specific repositories accepting multi-modal data, computational models, and simulations (Martone, 2023).3 SPARC is listed as an open neuroscience repository on the primary repository listing services maintained by the National Library of Medicine, International Neuroinformatics Coordinating Facility (INCF), Re3data, and FAIRSharing. In addition, the SPARC Portal is recognized as one of the recommended data repositories for the NIH HEAL initiative. We note that becoming a HEAL-compliant repository requires an extensive evaluation of repository capabilities such as persistence, FAIR alignment, data governance, and resources. Similarly, listing in INCF requires a rigorous evaluation against their list of recommended characteristics for neuroscience repositories. 6