Overview:
LUX: Yale Collections Discovery is a digital platform providing a unified gateway to Yale University’s museums, archives, and library collections. It enables users to discover and engage with objects across cultural heritage domains, including works of art, archives, and scientific specimens. The platform also exposes relationships among items and supports scholarship, research, and public engagement.
Purpose of Our Work:
Takin.solutions supported a semantic documentation project for LUX, focusing on the use of the Linked.Art model within the platform. Our work aimed to document the subset of Linked.Art concepts and relationships that were actually implemented in the Yale collections project and to indicate how original source data fields mapped to these abstract models. This provides a transparent record of model application, supporting data integration, reuse, and sustainability.
Methodology:
The project employed the Zellij platform to document and manage semantic patterns. Using Zellij, we captured:
- The Linked.Art entities and properties utilized in the LUX implementation
- Mappings from source data fields to Linked.Art concepts
This approach provided a reusable, structured record of model application, enabling future updates, integration efforts, and evaluation of semantic alignment.
Outcome:
- Clear documentation of Linked.Art model usage for Yale’s collections
- A referenceable pattern library supporting LUX’s ongoing semantic data management
- Insights into practical deployment of Linked.Art for other institutions or projects
Takin’s Role:
Takin.solutions applied the Semantic Reference Data Modelling (SRDM) methodology to capture and document the semantic use of Linked.Art within the LUX platform.
