A unified platform for cross-study data discovery and meta-analysis study building within the NHLBI BioData Catalyst (BDC) ecosystem.
Study Palette replaces fragmented search interfaces with a semantic, modular platform that enables researchers to discover data, explore variables, build studies, and transition to analysis — all from a single portal.
The system is organized into four layers:
- Front End (ReactJS) — Semantic search, query builder, visualizations, and data actions
- Modular APIs (FastAPI) — Search, Query, Analyze, and Workflows services
- Metadata Index — A LinkML-based "source of truth" generated during data ingestion, enabling consistent cross-study search at the variable and participant levels
- External Integrations — Monarch ontologies for entity resolution, DMC data ingestion, BDC analytic widgets, and foundational BDC services
See ARCHITECTURE.md for the full architecture reference and DEVELOPMENT.md for the project roadmap.
| Repository | Description |
|---|---|
| NHLBI-BDC-DMC-HM | BDC Harmonized Data Model (BDCHM) — the LinkML data model |
| dm-bip | Data Model-Based Ingestion Pipeline — harmonizes and transforms data upstream of Study Palette |
study-palette/
├── api/ # FastAPI backend + DuckDB
├── ui/ # React + TypeScript + Vite front end
├── docker/ # Dockerfiles
├── docs/ # Architecture docs and decisions
└── .github/workflows/ # CI/CD pipelines