It's About Time: Temporal Reasoning in Biomedical Knowledge Graphs Challenge
NIH Challenges seeks novel solutions for temporal reasoning in biomedical knowledge graphs to better model evolving scientific and clinical information.
Funder: NIH Challenges
Due Dates: January 15, 2027 (Phase 1 Submission End) | November 12, 2027 (Phase 2 Submission End)
Funding Amounts: Total prize pool: $1,000,000. Phase 1: up to $250,000 (up to 10 x $25,000 awards); Phase 2: $750,000 (1st: $350,000, 2nd: $250,000, 3rd: $150,000).
Summary: Supports innovative solutions for temporal reasoning in biomedical knowledge graphs to improve the modeling of evolving evidence and clinical workflows.
Key Information: Only Phase 1 winners may enter Phase 2; non-U.S. citizens/residents may participate but are not eligible for monetary prizes.
Description
This NIH Challenge aims to advance the field of biomedical knowledge graphs by incentivizing the development of methods, tools, or frameworks that enable robust temporal embeddings and temporal reasoning. Most current biomedical knowledge graphs are static and do not capture how entities, relationships, and evidence change over time, which limits their usefulness for research, clinical decision-making, and public health analytics. The challenge seeks solutions that allow knowledge graphs to encode and reason about temporal aspects, such as event sequencing, duration, validity intervals, and evolving evidence, thereby enabling more accurate, context-aware, and future-oriented insights. The competition is structured in two phases: Phase 1 focuses on conceptual design and feasibility, while Phase 2 emphasizes prototype implementation and demonstration.
