AI Revolutionizes Research Data Management for Faster Discovery

Significant advancements in research data management have emerged with the introduction of an artificial intelligence (AI) system designed to enhance the usability and accessibility of scientific data. The FAIR2 Data Management platform, developed by the open-science publisher Frontiers, aims to unlock vast quantities of valuable research data that remain underutilized in laboratories worldwide.

Research indicates that approximately 80% of all datasets generated remain confined within research settings. Only about 20% are shared, with fewer than 2% meeting the standards necessary for widespread use. Alarmingly, typically just one dataset leads to new findings. The FAIR2 initiative seeks to address these inefficiencies by making datasets not only reusable but also verifiable and citable.

Transforming Data Sharing

The FAIR2 Data Management system integrates essential processes such as curation, compliance checks, peer review, and interactive visualizations into a single platform. This comprehensive approach ensures that researchers can share their findings responsibly and receive appropriate credit for their contributions. By streamlining these steps, the system significantly reduces the time and effort required to prepare datasets for publication.

FAIR2 builds on the FAIR principles—Findable, Accessible, Interoperable, and Reusable—established in a March 2016 publication in the journal *Scientific Data*. These principles received international recognition at the G20 Hangzhou summit, where leaders endorsed their application to research. The FAIR2 platform represents the first practical implementation of these principles, coinciding with a period of rapid growth in research output and the increasing role of AI in scientific discovery.

Enhancing Scientific Collaboration

The platform is designed to overcome existing barriers in scientific research, including the slow pace of advancements in critical areas such as cancer treatment and climate modeling. Traditional data management practices often require extensive manual work, which the AI Data Steward, powered by Senscience, now automates, completing tasks that once took months in mere minutes.

Researchers utilizing FAIR2 receive four integrated outputs: a certified Data Package, a peer-reviewed and citable Data Article, an Interactive Data Portal with visualizations and AI chat features, and a FAIR2 Certificate. Each output is subject to rigorous quality controls, providing clear summaries to enhance understanding for a broader audience and ensuring compatibility across various research disciplines.

An exemplary dataset, titled Environmental Pressure Indicators (1990-2050), combines observed data and modeled forecasts across 43 countries over six decades, tracking emissions, waste, population, and GDP. This dataset is pivotal for sustainability benchmarking and informs evidence-based climate policy planning.

According to Dr. Ángel Borja, Principal Researcher at AZTI and member of the Basque Research and Technology Alliance (BRTA), the FAIR2 platform is highly recommended for its efficient data curation and publication capabilities. He notes, “You can generate information very quickly, and it’s useful formatting for any end users.”

By facilitating responsible reuse of data among researchers, policymakers, and practitioners, FAIR2 enhances visibility and accessibility, thus allowing society to derive greater value from investments in scientific research. As the platform continues to evolve, it stands to revolutionize the landscape of data management in research, paving the way for accelerated discovery and innovation across multiple fields.