STAR has demonstrated that semantic interoperability can be achieved by mapping and extracting different datasets and key concepts from OASIS reports to a core CRM-EH ontology via the central RDF-based triple store. Mapping datasets conforming to the widely used schemas for EH Recording Manual, MoLA and LEAP (IADB) means that, potentially, mappings to a large number of datasets have been afforded. Previously, it was not possible to search across organisational structures; each dataset remained isolated and no link was made to grey literature.
Mapping to the core ontology has resulted in a significant improvement in the degree and scale of semantic cross search. Currently within archaeology, searching of records is possible using relational databases systems designed to be project or organisation specific. However, the ability to search across data from various projects (or different organisations) held in different database systems is limited. Although systems, such as ADS ArchSearch, go some way to enabling searching between projects using document level metadata, searching across individual data items at the level of primary records from more than one site is generally not possible.
There are overheads in mapping the data structures to the over-arching semantic model. Section 4 has discussed various cost-benefit issues. The STELLAR project aims to reduce the costs of mapping and extracting data to semantic search systems such as the Demonstrator and to linked data representation generally.
Working with the CRM-EH archaeological extension of the CIDOC CRM ontology allows very specific archaeological queries, while permitting interoperability at the more general CRM level. By using the CRM as the underlying model, interoperability with other archaeological datasets mapped to the CRM is afforded, potentially extending to other areas of cultural heritage. It is not necessary to expose the full detail of the ontological model; the Demonstrator shows that user interfaces for retrieval (or mapping) systems can be expressed using familiar archaeological concepts. The search scenarios and subsequent discussion illustrate the variety of semantic cross search enabled via the relationships in the ontology. It is possible to find a conceptual pattern in a familiar dataset and investigate whether it occurs in other datasets or grey literature.
The benefits of full digital publication are perhaps particularly strong for archaeology, in light of the destructive nature of the excavation process. Due to the inevitable need for selection in where to focus excavation activity, initial interpretations are often revised. The need to preserve data for future researchers has been recognised as far back as Pitt-Rivers. In 1993, a classic textbook made the case for preserving and reusing archaeological data:
'Research excavations, therefore, must be planned for posterity, eschewing the quick answer and setting up a framework of excavation and recording which can be handed over, extended, modified and improved over decades and in some cases, centuries.' (Barker 1993, 79)
As more data becomes available in standard formats, semantic techniques will allow much greater reuse of that data. Semantic cross search will have the potential for discovering new connections and contributing substantively to archaeological research. It also opens wider possibilities for revisiting and extending previous interpretations. Providing the evidential basis for interpretations via excavation datasets opens the possibility for alternative interpretations to be investigated and recorded alongside the underlying context data. The ability to connect published datasets with the under utilised grey literature holds great potential for meta research studies across a wide range of projects, where aggregate patterns can be compared and hypotheses for future detailed investigation uncovered.
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| File last updated: Mon July 18 2011