WOBD turns biomedical data silos into a queryable discovery network.

The Web of Biological Data connects harmonized dataset metadata from the NIAID Data Ecosystem with 30+ Proto-OKN knowledge graphs, so researchers and AI assistants can move from a question to mechanisms, exposures, diseases, and supporting datasets in one reproducible workflow.

Continued support has compounding value: every new graph, repository, and metadata relationship widens the set of cross-domain questions WOBD can answer.

How WOBD works
Dataset metadata
Knowledge graphs
Ontologies
Curated resources
WOBD federation layer

Shared identifiers, graph metadata, query guardrails, ontology lookup, and provenance-aware execution.

Guided queries
AI assistants
Auditable answers
30+

Proto-OKN graphs reachable through the federation

3

worked cross-domain analyses shown on this site

2

ways to use WOBD: guided templates or AI assistants

Choose the path that fits your role

WOBD is both a practical discovery tool and a growing research infrastructure layer. These entry points separate hands-on use from strategic context.

Impact case studies

Three worked analyses show the same pattern: WOBD joins separately curated resources into auditable answers that would otherwise require cross-disciplinary teams and manual synthesis.

How WOBD grows in value

The hard part of biomedical research is rarely a single database lookup. It is trusted synthesis across data that was funded, curated, and published separately.

A shared query plane

WOBD publishes dataset metadata, expression evidence, and graph context into a federation that researchers and AI assistants can query consistently.

Provenance by design

Results stay tied to source graphs, executed queries, identifiers, and dataset records, making AI-mediated discovery inspectable and rerunnable.

Compounding growth

Each additional graph, repository, and metadata relationship expands the questions the network can answer without rebuilding one-off integrations.

Start using WOBD

WOBD is part of the broader Proto-OKN effort to build interconnected, trustworthy knowledge graphs for data-driven discovery. Review the growth plan and team →