Overview:
Takin.Solutions supported the GLOBALISE project in establishing the semantic data foundations for a large-scale digital research infrastructure centred on the archives of the Dutch East India Company (VOC). The project aims to enable advanced research into approximately five million archival scans by creating structured, interoperable data that captures entities, events, and contextual reference information across the corpus.
Takin’s work focused on developing the semantic architecture and documentation framework needed to integrate archival data, reference datasets, and scholarly annotations into a coherent knowledge graph that supports complex historical research questions and transparent data provenance.
Scope of Work:
- Developed the global ontology framework to structure the project’s entity and event data, aligning archival information with established semantic standards such as CIDOC CRM, CRMaaa, and SKOS
- Supported the modelling of key research entities including persons, places, polities, ships, voyages, cargo, and historical events present in VOC archival material
- Designed and documented Semantic Reference Data Models (SRDMs) to provide reusable conceptual modelling patterns guiding the implementation of the ontology
- Produced structured semantic documentation using the Zellij platform, ensuring that modelling decisions were understandable and reusable by scholars, developers, and data engineers
- Worked collaboratively with historians and technical teams to align semantic modelling with research questions, annotation workflows, and the broader research infrastructure
Outcome:
The project delivered a fully documented semantic framework and set of SRDM modelling patterns that provide the conceptual foundation for the GLOBALISE knowledge infrastructure. This framework enables consistent integration of archival transcriptions, entity and event annotations, and reference datasets, supporting advanced historical analysis and the creation of new, more diverse interpretations of the VOC archives.
