Making NIH Common Fund (CF) datasets FAIR is just the first step in unlocking their potential in the era of big data. Scientific progress depends on accessible knowledge, yet non-computational researchers often struggle with interpreting knowledge graphs (KGs) due to their logic-based reasoning, which can overlook scientific context and uncertainty, leading to invalid inferences.

Our CFDE Knowledge Center (KC) will focus on presenting scientifically valid knowledge from CF projects in a KG format aligned with CFDE and external curation efforts. To ensure accuracy, we will emphasize careful knowledge extraction—ensuring each KG edge is based on primary experimental findings or expert analysis—and thoughtful knowledge presentation, using tailored visualizations instead of general graph traversal.

Leveraging our experience from four large-scale NIH-funded projects, we will develop a user-friendly portal that enhances data accessibility and scientific validity, empowering a diverse range of researchers to engage with CF-generated knowledge.