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Within the archaeology domain, datasets frequently refer to time periods using a variety of textual or numeric formats. Traditionally controlled vocabularies of time periods have used classification notation and the collocation of terms in the printed form to represent and convey tacit information about the relative order of concepts. The emergence of the semantic web entails encoding this knowledge into machine readable forms, and so the meaning of this informal ordering arrangement can be lost. Conversion of controlled vocabularies to Simple Knowledge Organisation System (SKOS) format provides a formal basis for semantic web indexing but does not facilitate chronological inference - as thesaurus relationship types are an inappropriate mechanism to fully describe temporal relationships. This becomes an issue in archaeological data where periods are often described in terms of (e.g.) named monarchs or emperors, without additional information concerning relative chronological context. An exercise in supplementing existing controlled vocabularies of time period concepts with dates and temporal relationships was undertaken as part of the Semantic Technologies for Archaeological Resources (STAR) project. The general aim of the STAR project is to demonstrate the potential benefits in cross searching archaeological data conforming to a common overarching conceptual data structure schema - the CIDOC Conceptual Reference Model (CRM). This paper gives an overview of STAR applications and services and goes on to particularly focus on issues concerning the extraction and representation of time period information. [ABSTRACT FROM AUTHOR]

Findings from a data mapping and extraction exercise undertaken as part of the STAR project are described and related to recent work in the area. The exercise was undertaken in conjunction with English Heritage and encompassed five differently structured relational databases containing various results of archaeological excavations. The aim of the exercise was to demonstrate the potential benefits in cross searching data expressed as RDF and conforming to a common overarching conceptual data structure schema - the English Heritage Centre for Archaeology ontological model (CRM-EH), an extension of the CIDOC Conceptual Reference Model (CRM). A semi-automatic mapping/extraction tool proved an essential component. The viability of the approach is demonstrated by web services and a client application on an integrated data and concept network. [ABSTRACT FROM AUTHOR]