Semantic Technologies Enhancing Links and Linked data for Archaeological Resources

STELLAR – Project

STELLAR is an AHRC funded project (£110k). The project is in collaboration with co-investigator Stuart Jeffrey from York University Archaeology Department and the Archaeology Data Service and project partners, English Heritage (collaborator Keith May). STELLAR builds on outcomes and tools from the previous AHRC funded STAR project, which in its turn extended semantic search techniques initially developed through the EPSRC funded FACET project, a collaboration with the Science Museum. Doug Tudhope is PI and Ceri Binding is the Research Fellow on the project.


The benefits for semantic interoperability in mapping and extracting datasets to an integrating conceptual framework, such as the CIDOC CRM, are widely recognized. However, achieving mappings in practice has required specialist knowledge of the ontology and has been resource intensive. STELLAR aims to provide suppport for non-specialist users to map and extract datasets.


STELLAR tools, tutorials and reports are now freely available.
Conference and journal outputs can be found under KOS publications.
Results from the final Linked Data publication phase are available from Archaeology Data Service Linked Data


  • Develop best practice guidelines for mapping and extraction of archaeological datasets into RDF/XML representation conforming to the CIDOC CRM-EH standard ontology
  • Develop an enhanced mapping tool for non-specialist users to map and extract archaeological datasets into RDF/XML representation conforming to CIDOC CRM-EH
  • Map and extract archaeological datasets into RDF/XML representation conforming to CIDOC CRM-EH (by non-specialist users)
  • Develop best practice guidelines and tools for generating Linked Data corresponding to extracted datasets
  • Publish corresponding Linked Data
  • Evaluate the mapping tool and the Linked Data provision
  • Engage with the archaeological community to inform research and disseminate outcomes


The Archaeology Data Service (ADS) at York has a mandate to provide a digital repository for outputs from research funded by AHRC, NERC, English Heritage and other bodies. Archaeology has seen increasing use of the Web in recent years for data dissemination, and the ADS holds a wide range of datasets from archaeological excavations. However datasets and applications are currently fragmented and isolated. Different terminology and data organisation hinders search and comparison across datasets. Because of these impediments, archaeological data is rarely reused and re-examined in light of evolving research questions and interpretations.

The STAR project addressed these concerns by developing semantic and natural language processing techniques to link digital archive databases and the associated grey literature, via an overarching framework (the CIDOC Conceptual Reference Model, extended for archaeological purposes by English Heritage). STELLAR aims to generalise and extend the data extraction tools produced by STAR to facilitate their adoption by third party data providers. The extracted data will be represented in standard formats that allow the datasets to be cross searched and linked by a variety of Semantic Web tools, following a Linked Data approach.