Most scientific data never fuel the discoveries they should.
For every 100 datasets created, around 80 remain in the lab, 20 are shared but rarely reused, fewer than two meet FAIR standards, and only one typically drives new findings.
The result: delayed cancer treatments, climate models short on evidence, and research that cannot be reproduced.
Frontiers, the open-science publisher, is tackling this problem with the launch of Frontiers FAIR² Data Management, the world’s first all-in-one, AI-powered service for research data. Designed to transform how data is shared so it is reusable and credited, it brings together curation, compliance checks, AI-ready packaging, peer review, an interactive portal, certification, and lifetime hosting in a single workflow — ensuring that research funded today delivers faster breakthroughs in health, sustainability, and technology tomorrow.
FAIR² extends the FAIR principles (Findable, Accessible, Interoperable and Reusable) with an open specification that ensures every dataset is AI-ready and responsibly reusable by both humans and machines. Frontiers FAIR² Data Management is the first implementation, launched at a time when research outputs are growing exponentially and AI is reshaping discovery — turning principles into practical infrastructure for real-world impact at scale.
Dr Kamila Markram, co-founder and CEO of Frontiers, comments:
“Ninety percent of science vanishes into the void. With Frontiers FAIR² Data Management, no dataset and no discovery need ever be lost again — every contribution can now fuel progress, earn the credit it deserves, and unleash science.”
AI at the Core
Tasks that once took months of manual work — from curating datasets and checking compliance to creating metadata and publishable outputs — are now completed in minutes by the AI Data Steward, powered by Senscience, the Frontiers venture behind FAIR².
With one submission, researchers receive four outputs: a certified Data Package, a peer-reviewed and citable Data Article, an Interactive Data Portal with visualizations and AI chat, and a FAIR² Certificate. Together they include quality checks and clear summaries that make data easier to interpret for non-specialists and simpler to combine across disciplines.
Together, they ensure every dataset is preserved, validated, citable, and reusable — ready to drive new discoveries while giving scientists the credit they deserve. Frontiers FAIR² also makes data visible and easy to explore, enabling responsible reuse by researchers, policymakers, practitioners, communities, and even machines — helping society gain more value from its investment in science.
Flagship Pilot Datasets
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SARS-CoV-2 Variant Properties — Covering 3,800 spike protein variants, this dataset links structural predictions from AlphaFold2 and ESMFold with ACE2 binding and expression data. It offers a powerful resource for pandemic preparedness, enabling deeper understanding of variant behavior and fitness.
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Preclinical Brain Injury MRI — A harmonized dataset of 343 diffusion MRI scans from four research centers, standardized across protocols and aligned for comparability. It supports reproducible biomarker discovery, robust cross-site analysis, and advances in preclinical traumatic brain injury research.
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Environmental Pressure Indicators (1990–2050) — Combining observed data and modeled forecasts across 43 countries over six decades, this dataset tracks emissions, waste, population, and GDP. It underpins sustainability benchmarking and evidence-based climate policy planning.
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Indo-Pacific Atoll Biodiversity — Spanning 280 atolls across five regions, this dataset integrates biodiversity records, reef habitats, climate indicators, and human-use histories. It provides an unprecedented basis for ecological modeling, conservation prioritization, and cross-regional research on vulnerable island ecosystems.
Researchers testing the pilots noted that Frontiers FAIR² not only preserves and shares data but also builds confidence in its reuse — through quality checks, clear summaries for non-specialists, and the reliability to combine datasets across disciplines, all while ensuring scientists receive credit.
All pilot datasets comply with the FAIR² Open Specification, making them responsibly curated, reusable, and trusted for long-term human and machine use so today’s data can accelerate tomorrow’s solutions to society’s most pressing challenges.
Recognition and Reuse
Each reuse multiplies the value of the original dataset, ensuring that no discovery is wasted, every contribution can spark the next breakthrough, and researchers gain recognition for their work.
Dr Sean Hill, co-founder and CEO of Senscience, the Frontiers AI venture behind FAIR² Data Management, notes:
“Science invests billions generating data, but most of it is lost— and researchers rarely get credit. With Frontiers FAIR², every dataset is cited, every scientist recognized — finally rewarding the essential work of data creation. That’s how cures, climate solutions, and new technologies will reach society faster — this is how we unleash science.”
What Researchers Are Saying
Dr Ángel Borja, Principal Researcher, AZTI, Marine Research, Basque Research and Technology Alliance (BRTA):
“I highly [recommend using] this kind of data curation and publication of articles, because you can generate information very quickly and it’s useful formatting for any end users.”
Erik Schultes, Senior Researcher, Leiden Academic Centre for Drug Research (LACDR); FAIR Implementation Lead, GO FAIR Foundation:
"Frontiers FAIR² captured the scientific aspects of the project perfectly."
Femke Heddema, Researcher and Health Data Systems Innovation Manager, PharmAccess:
"Frontiers FAIR² makes the execution of FAIR principles smoother for researchers and digital health implementers, proving that making datasets like MomCare reusable doesn’t have to be complex. By enabling transparent, accessible, and actionable data, Frontiers FAIR² opens the door to new opportunities in health research."
Dr Neil Harris, Professor in Residence, Department of Neurosurgery, Brain Injury Research Center, University of California, Los Angeles (UCLA):
"Implementation of [Frontiers] FAIR² can provide an objective check on data for both missingness and quality that is useful on so many levels. These types of unbiased assessments and data summaries can aid understanding by non-domain experts to ultimately enhance data sharing. As the field progresses to using big data in more disparate sub-disciplines, these data checks and summaries will become crucial to maintaining a good grasp of how we might use and combine the multitude of already acquired data within our current analyses."
Maryann Martone, Chief Editor, Open Data Commons:
“[Frontiers] FAIR² is one of the easiest and most effective ways to make data FAIR. Every PI wants their data to be findable, accessible, comparable, and reusable — in the lab, with collaborators, and across the scientific community. The real bottleneck has always been the time and effort required. [Frontiers] FAIR² dramatically lowers that barrier, putting truly FAIR data within reach for most labs."
Dr Vincent Woon Kok Sin, Assistant Professor, Carbon Neutrality and Climate Change Thrust, Society Hub, The Hong Kong University of Science and Technology (HKUST):
“[Frontiers] FAIR² makes our global waste dataset more visible and accessible, helping researchers worldwide who often struggle with scarce and fragmented data. I hope this will broaden collaboration and accelerate insights for sustainable waste management.”
Dr Sebastian Steibl, Postdoctoral Researcher, Naturalis Biodiversity Center and the University of Auckland:
“True data accessibility goes beyond just uploading datasheets to a repository. It means making data easy to view, explore, and understand without necessarily requiring years of training. The [Frontiers] FAIR² platform, with an AI chatbot and interactive visual data exploration and summary tools, makes our biodiversity and environmental data broadly accessible and usable not just to scholars, but also practitioners, policymakers, and local community initiatives.”