A set of purpose-built digital tools for cultural heritage provenance research — from knowledge graph integration to AI-powered narratives, conversational queries, and multi-dimensional analytics.
BecaGraph is the integration engine that powers the entire platform. It transforms raw Excel or CSV exports from museum collection management systems into a CIDOC CRM-compliant RDF knowledge graph queryable via SPARQL — with LLM-powered entity resolution that identifies the same actor, place, or object across multiple institutional datasets.
BecaChat lets researchers and museum professionals query the BECACO knowledge graph in plain language — no SPARQL expertise needed. Type a question, and the LLM translates it into a SPARQL query, executes it against the Graph DB endpoint, and returns a structured, readable answer.
Beca Narratives bridges the gap between raw provenance data and human-readable stories. Enter any object identifier from the knowledge graph, and the tool retrieves its structured metadata, feeds it to an LLM, and generates a compelling, historically informed narrative. The text is then converted to audio for accessible, multi-modal playback — validated by both domain experts and museum visitors.
The Analytics Dashboard provides six integrated modules for exploring the knowledge graph from temporal, spatial, relational, and qualitative angles. It also groups five additional specialised tools — provenance tracing, actor intelligence, collection browsing, and data quality monitoring.
The BECACO tool suite is designed for research collaboration with ethnographic and archaeological museums. If you are interested in integrating your collection data or exploring any of these tools for your own provenance research, get in touch.