Visual Analysis & Collection Research
Visual Search
In museum and heritage collections, the image itself often plays a central role. Yet visual properties such as form, colour, composition, technique or repetition are not always fully captured in metadata or descriptions. As a result, important relationships between objects, images and subcollections can remain hidden.
With Visual Analysis & Collection Research, you add an extra layer of insight to your collection. AI helps identify visual similarities and recurring characteristics, enabling researchers and collection managers to recognise patterns faster and formulate new research questions. Not as a replacement for subject-matter expertise, but as support for the research process.
New access points for collection research
Visual analysis makes it possible to approach collection material not only through title, maker, dating or keywords, but also through the image itself. This provides an additional research access point, especially in collections where visual characteristics play an important role.
Making patterns and relationships visible
By comparing images with one another, similarities in composition, motifs, forms, colour use or stylistic features can emerge. Such relationships are relevant for collection research, provenance questions, thematic analysis and the recognition of visual traditions within a collection.
Support for interpretation and selection
Visual analysis can help explore large volumes of image material faster. It supports researchers, curators and collection managers in selecting relevant material for further study, presentation or public projects.
Valuable for large and heterogeneous collections
In large collections or collections with diverse object types, it is not always easy to recognise coherence. Visual analysis helps create overview faster and identify starting points for further interpretation.
AI as a research instrument, not a final conclusion
The results of visual analysis are intended to support the research process. AI can suggest, signal similarities and group material, but interpretation remains in the hands of the people who know the collection. The human perspective remains leading.
Strengthening existing collection knowledge
Visual analysis does not stand apart from existing documentation and metadata, but complements them. Combined with collection information, provenance data and subject-matter expertise, it creates a richer and better-founded picture of the collection.