The Archaeology Data Service (ADS) 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 aimed to generalise and extend the data extraction tools produced by STAR to facilitate their adoption by third party data providers. The extracted data is represented in standard formats to allow the datasets to be cross searched and linked by a variety of Semantic Web tools, following a linked data approach.

As a result, the ADS has begun to ingest some of its excavation data into a triple store and expose it as linked data. This paper will briefly discuss the STAR and STELLAR projects to provide context to the ADS linked data. It will also outline the technologies used to develop the ADS triple store and linked data output. In particular, it will discuss the more practical details of creating our triple store, populating it with excavation data, and finally publishing it as linked data. This will hopefully provide some guidance for other interested parties who may want to set up something similar. Finally, with the ADS linked data as a concrete example, an overview of the suspected future directions will be outlined. In particular how we can enrich the existing and forthcoming linked data with both archaeological and non-archaeological data in addition to how the ADS linked data can enrich other data sets. In this sense we hope to identify some of the immediate and potential archaeological questions that can be asked and answered from our linked data.