Explore the latest research published through Frontiers FAIR² Data Management: reusable, AI-ready, and citable datasets designed to accelerate discovery and maximize impact across disciplines.

FAIR² DATA article

Atoll biodiversity and environments

An interactive portal mapping biodiversity and environmental data across 310 Indo-Pacific atolls, curated by a Frontiers Planet Prize champion.

FAIR² DATA article

Global waste sector dataset (1990-2050)

An AI-ready dataset linking municipal waste, emissions, and socioeconomic drivers for 43 countries curated by a Frontiers Planet Prize champion.

FAIR² DATA article

Multi-site, in vivo MRI dataset of brain diffusivity measures

The dataset presented here, developed by the Translational Outcomes Project in NeuroTrauma (TOP-NT) Consortium, addresses a persistent limitation in the field: the lack of multi-site, harmonized diffusion MRI data.

FAIR² DATA article

Structure-based prediction of SARS-CoV-2 variant properties

This dataset presents a structure-enriched resource of theoretical and empirical SARS-CoV-2 spike receptor-binding domain (RBD) variants, developed under the STAYAHEAD project for pandemic preparedness.

The FAIR² Data Article is a new article type designed to focus exclusively on a single dataset rather than testing specific hypotheses. Published alongside a unique interactive data explorer, this new publication format ensures that high-value datasets receive the same recognition, visibility, and citation opportunities as traditional research articles while remaining accessible and reusable for the global research community.

What makes the FAIR² Data Article unique?

• Dataset-centric: unlike traditional articles, which focus on hypothesis-driven analysis, FAIR² Data Articles are dedicated solely to the dataset, its structure, provenance, and reuse potential.

• Peer-reviewed and citable: ensures that datasets are rigorously assessed for quality, completeness, and adherence to FAIR principles

• Interoperable and AI-ready: published datasets are structured for seamless reuse, analysis, and integration with computational models and AI-driven research.

• Start your submission. Begin within your chosen Frontiers journal by selecting 'FAIR² Data' as the article type in the submission process

• Upload. Securely upload your dataset to Frontiers FAIR². Our AI data steward Clara helps with metadata and initial preparation

• Curate. Organize methods and data dictionary, validate quality and consistency with FAIR² standards, and explore your data through visualizations to check completeness.

• Compose. Draft your FAIR² Data Article with structured methods, metadata, and visual summaries automatically generated from your dataset — supporting alignment and integrity checks throughout.

• Showcase. Your FAIR² Data Article automatically includes a custom interactive data portal, tailored to your dataset — with AI chat, visualizations, and notebooks for computation and reuse.

• Submit for peer review. Finalize and submit your FAIR² Data Article and portal for peer review and publication in a Frontiers journal. Once accepted, your dataset becomes a citable, open access scientific contribution — certified, preserved, and discoverable.

Learn more about FAIR², an intelligent way to organize, share, and publish data - making it AI-ready, reusable and impactful.