Tag Archives: Well Known Text

GSTAR: investigation of methods for working with geosemantic data, integrating geospatial data with semantic data

Archaeogeomancy: Digital Heritage Specialists - archaeological geomatics - the majick of spatial data in archaeology - archaeological information systems for the digital age:

Mapping rubble by Brian Hoffman

Mapping rubble by Brian Hoffman

The first investigation in the GeoSemantic Technologies for Archaeological Research (GSTAR) research project is nearing completion, an assessment of approaches to the integration of geospatial archaeological data into a semantic framework to provide geosemantic capabilities.

The investigation draws on archaeological excavation data lodged with the Archaeology Data Service (ADS) and made available as Linked Data (LD) through the ADS’s Linked Data platform. The data relates to the Cobham Golf Course site and was produced by Oxford Archaeology (OA) as part of the Channel Tunnel Rail Link (CTRL) project then turned into a Linked Data resource through the Semantic Technologies Enhancing Links and Linked data for Archaeological Resources (STELLAR) project, undertaken by the Hypermedia Research Unit at the University of South Wales (USW).

Mapping a feature by Wessex Archaeology

Mapping a feature by Wessex Archaeology

The GSTAR literature review identified two strands of integration approaches within published literature. Emerging from the semantic web and Linked Data communities, an approach involving the direct inclusion of geospatial data within semantic resources, leveraging World Wide Web Consortium (W3C) standards for Resource Description Framework (RDF) and Open Geospatial Consortium (OGC) standards for Well Known Text (WKT, part of the Simple Features specification) and GeoSPARQL. Emerging from the Geographic Information Science (GISc) community, approaches involving the use of Web Feature Services (WFS) within broader Spatial Data Infrastructures (SDI) running in parallel and linked to to semantic resources.

This initial GSTAR investigation looked at both these strands with a view to assessing suitable modes for subsequent use in the next phases of the GSTAR project. A WISSKI installation has also been setup to allow for the minting of any additional URIs needed.

GeoSPARQL route

This involved creating geosemantic data aligned with the CRM-EH extension to the CIDOC CRM ontology, stored within the Oracle Spatial & Graph platform and accessed via GeoSPARQL using an Oracle WebLogic web server and the Jena Framework.

[code language="xml"]
<owl:Class rdf:about="http://purl.org/crmeh#EHE0022_ContextDepiction">
<rdfs:isDefinedBy rdf:resource="http://purl.org/crmeh#CRMEH"/>
<rdfs:subClassOf rdf:resource="http://erlangen-crm.org/110404/E47_Spatial_Coordinates"/>
<rdfs:label>Context Depiction</rdfs:label>
The Spatial co-ordinates of a Context, defining the actual spatial extent of the context. Usually recorded at the time of excavation or other investigative work
The OWL definition of the EHE0022 class used to describe depictions

Further triples were also added to describe the depiction using the GeoSPARQL ogc:hasGeometry and ogc:asWKT properties.

[code language="xml"]
<owl:ObjectProperty rdf:about="#hasGeometry">
<rdfs:isDefinedBy rdf:resource=""/>
<rdfs:isDefinedBy rdf:resource="http://www.opengis.net/spec/geosparql/1.0"/>
<skos:prefLabel xml:lang="en">hasGeometry</skos:prefLabel>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2011-06-16</dc:date>
<dc:contributor>Matthew Perry</dc:contributor>
<dc:description xml:lang="en">
A spatial representation for a given feature.
<rdfs:range rdf:resource="#Geometry"/>
<rdfs:comment xml:lang="en">
A spatial representation for a given feature.
<rdfs:domain rdf:resource="#Feature"/>
<rdfs:label xml:lang="en">hasGeometry</rdfs:label>
<dc:creator>OGC GeoSPARQL 1.0 Standard Working Group</dc:creator>
<skos:definition xml:lang="en">
A spatial representation for a given feature.

The OWL definition of the hasGeometry property

GIS Server route

A second approach used the same base platform and data but accessed the geospatial component via WFS provided by GeoServer, drawing on the Oracle database.

Next steps

The results of this stage and the GSTAR project in general will be presented at the Computer Applications and Quantitative Methods in Archaeology (CAA) conference to be held in Paris, France during April 2014.

Thanks are due to the University of South Wales for funding the GSTAR project and to the people and organisations responsible for the tools, technologies and data being used. Also my PhD supervisor (Prof. Douglas Tudhope; USW), advisors (Dr Mark Ware and Dr Alex Lohfink: USW) and fellow researchers Ceri Binding (USW), Dr Andreas Vlachidis (USW) and Michael Charno (ADS) for their input.

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