This repository contains ETL scripts and loaders for building the SciLake Pilot knowledge graphs. The graphs are built in three layers: core structure, common enrichments, and pilot-specific enrichments.
SciLake Pilot graphs are constructed in a layered approach:
- Core Structure (SKG-IF): Foundation knowledge graph with core entities and relationships
- Common Enrichments: Cross-domain enrichments applied to all pilot graphs
- Pilot-Specific Enrichments: Domain-specific enrichments tailored to each research domain
The SKGIF directory provides the foundational knowledge graph structure:
- Core Entities: Agents, Grants, Venues, Topics, Datasources, Products
- Core Relationships: HAS_PID, HAS_CONTRIBUTED_TO, HAS_TOPIC, FUNDED_BY, and more
- Parsers: Transform raw data dumps into structured JSONL files ready for loading
See skgif/README.md for details.
The enrichments/common/ directory contains enrichments that apply to all pilot graphs:
- Research Artifacts: Links datasets and software to products
- Citances: Citation relationships with semantic annotations
- Technologies: Technology mentions extracted from products
- Text Mentions: Aggregated mention relationships
See enrichments/common/README.md for details.
The enrichments/graph-specific/ directory contains domain-specific enrichments for each pilot:
- Cancer Research: BCMO gene relationships, Cancer Knowledge Graph (CKG) integration
- Energy Research: Geographic entities, energy types, IRENA entities
- Neuroscience: Neuro entities (techniques, species, UBERON parcellations), EBRAINS integration
- Transport-CCAM: CCAM entities
- Transport-Maritime: Maritime vessel types
See enrichments/graph-specific/README.md for details.
To build a complete pilot graph, follow this order:
- Load Core Structure: Execute SKGIF parsers and loaders to create the foundation
- Apply Common Enrichments: Load common enrichments that apply across all domains
- Apply Pilot-Specific Enrichments: Load domain-specific enrichments for your pilot
See individual README files for specific instructions and requirements.
This work was supported by the European Union's Horizon Europe research and innovation programme under grant agreement No. 101058573 SciLake.