In March, over 100 researchers, data scientists, and program collaborators gathered in Bethesda, Maryland, for the 2025 Common Fund Data Ecosystem (CFDE) spring meeting. Hosted by the Integration and Coordination Center, led by Jake Chen, Ph.D., founding director of the Systems Pharmacology AI Research Center and Triton Endowed Professor in the Department of Biomedical Informatics and Data Science, the two-day event brought together members of the CFDE consortium from across the U.S. to share progress, demonstrate tools, and chart a path forward for data integration and accessibility.
The CFDE is a key initiative designed to enable the broad reuse of data generated by multiple Common Fund programs. Organized around five collaborative centers, CFDE supports the development of infrastructure, tools, and community engagement strategies to ensure that these diverse datasets can be leveraged for novel scientific discoveries.
The meeting provided a dynamic platform for collaboration and learning. Attendees explored a variety of technical updates and emerging tools—from advanced knowledge graphs and gene visualization platforms to immersive virtual reality environments for navigating the Human Reference Atlas. These demonstrations highlighted how CFDE teams are making complex biomedical data more actionable.
A notable feature of the event was the inclusion of early-career researchers. Over 20 lightning talks and 25 poster presentations gave junior scholars a chance to showcase their work, exchange ideas, and connect with potential collaborators.
Key discussions focused on expanding the user base of CFDE tools and identifying sustainable approaches for ensuring the long-term accessibility and utility of Common Fund data. These conversations reinforced the consortium’s shared commitment to building a robust, user-centered data ecosystem that accelerates discovery across biomedical research.
As the CFDE evolves, the collaborative spirit and innovative energy displayed at the Spring Meeting signal a promising future for data-driven science.
