Make your collection discoverable. Connect what you hold to what it means.
Cultural heritage institutions hold collections that span centuries. But value locked in disconnected catalog systems, legacy databases, and unstructured finding aids cannot be accessed, explored, or activated. Data Graphs connects collection objects, provenance, creators, events, and historical context in a single knowledge graph, making your holdings genuinely navigable for researchers, educators, and the public.
The missing layer in your cultural heritage ecosystem
Cultural heritage institutions manage collections that are richer and more interconnected than any catalog can capture. A painting is not just an object with dimensions and a date. It is linked to the artist who created it, the period it belongs to, the patrons who commissioned it, the collections it has passed through, the restoration history it carries, the related works it influenced, and the archival documents that record its provenance. A catalog entry captures the object. A knowledge graph captures the meaning.
Data Graphs provides the context layer that makes these connections explicit and queryable. Objects, people, events, places, documents, and media can all be nodes in the same graph, linked by relationships defined to fit your collection's own domain model, whether that is CIDOC-CRM, Dublin Core, or a bespoke schema developed over decades. A researcher navigating the graph is not just searching, they are exploring a network of relationships that no flat catalog or document search could surface. And with AI-powered search built on this connected foundation, the same discovery experience becomes accessible to non-specialist users too.
Let researchers navigate relationships, not just search for keywords
A researcher studying the patronage networks of a specific period needs to find not just the objects commissioned by a particular family, but the artists those patrons supported, the other collections those artists contributed to, the correspondence that documents those relationships, and the historians who have written about them. A keyword search returns documents that mention the family name. A knowledge graph traversal returns the network. With Data Graphs, every entity in your collection is connected to the entities it relates to, and those relationships are traversable in a single query. A researcher asking "Show me all works commissioned by this family, the artists involved, and related archival documents held by partner institutions" is navigating a connected knowledge graph, not a catalog. The result is a research tool that matches the complexity of the questions researchers actually ask.
Make provenance and ownership history transparent and traceable
Provenance is one of the most sensitive and consequential aspects of cultural heritage collection management. The journey an object has taken, through sales, inheritance, wartime displacement, restitution claims, and conservation interventions, is often recorded across multiple documents in multiple archives, with gaps and ambiguities at every stage. Data Graphs makes provenance a first-class data structure rather than a note in a catalog record. Every ownership transfer, location change, loan record, and associated document is a node in the graph connected to the object and to the people and institutions involved. This makes provenance research dramatically faster, supports due diligence for acquisitions and loans, and provides the structured evidence base needed to handle restitution inquiries with transparency and rigor.
Open your collection to public discovery without rebuilding your catalog
Many institutions want to offer public-facing digital access to their collections but face a dilemma: the catalog system that manages the collection is not designed for consumer-facing discovery, and building a separate public interface means maintaining two systems. Data Graphs acts as the knowledge layer that sits between your existing collection management system and any number of public-facing interfaces. Your cataloging workflows stay in place. Data Graphs ingests structured and unstructured data, enriches it with relationships and contextual metadata, and exposes it through APIs that power public search portals, educational apps, augmented reality experiences, and AI-powered Q&A tools. The collection management system does what it does best. The knowledge graph does what it does best. Researchers and the public experience the richness of your holdings.
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See how Data Graphs can transform your glam & cultural heritage data.