STAR Semantic Technologies for Archaeological Resources.
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1 STAR Semantic Technologies for Archaeological Resources
2 Project Outline 3 year AHRC funded project Started January 2007, finish December 2009 Collaborators English Heritage RSLIS, Denmark Aims To investigate the potential of semantic terminology tools for widening access to digital archaeology resources, including disparate datasets and associated grey literature To demonstrate cross search and browsing at detailed, meaningful level
3 Introduction Data Modelling (RDF) CIDOC Conceptual Reference Model (CRM) English Heritage Ontological Model (CRMEH) English Heritage thesauri & glossaries (SKOS) Data Mapping Mapping issues domain specific vs. general model Granularity, coverage Data normalisation issues Data Extraction Custom extraction utility Consolidation to RDF triple store database Pilot Applications SKOS Web Service / Client applications CRM Web Service / Client applications
4 General Architecture Applications Server Side, Rich Rich Client, Browser Web Web Services, SQL, SPARQL RDF RDF Based Common Ontology Data Data Layer (CRM // CRMEH // SKOS) Indexing Conversion Data Data Mapping // Normalisation Grey Grey literature EH EH thesauri, glossaries STAN STAN RRAD RRAD IADB IADB LEAP LEAP RPRE RPRE
5 Data Modelling - RDF CRM [ ] CIDOC Conceptual Reference Model International standard ISO 21127:2006 CRMEH [ ] English Heritage Ontological Model Extends CIDOC CRM for archaeological domain SKOS [ ] Simple Knowledge Organisation System RDF representation of thesauri, glossaries, taxonomies, classification schemes etc.
6 Potential Data Mapping Problems General schema (CRM) General schema (CRM)? Domain specific datasets the abstractness of the [CRM] concepts makes them ambiguous to any human user. If several experts specify mappings independently they will produce incompatible mappings and fail the goal of enabling interoperability. [from BRICKS FP6 IP Poster, ECDL2007] Domain specific datasets STAR approach - domain specific schema (CRMEH)
7 Data Mapping Exercise Mapped DB Field CRMEH Entity manual process, requires expert domain knowledge Needed to Consider Granularity & completeness of mapping Model coverage vs. dataset coverage Event based vs. relational model Events only implicit in mappings and datasets
8 Data Normalisation Issues Identifiers URI References [Prefix]entity.database.table.column.rowid Coordinates EH Recording Manual Easting/northing/AOD (in metres) /190865/ Dates/Periods W3C/ISO8601 big-endian format CCYY-MM-DDThh:mm:ss T16:19:23 Controlled fields - Data cleansing / mapping EH Thesauri from EH DSU, Swindon EH Glossaries from Recording Manual
9 Data Extraction - Scope Extraction of data to RDF triples 5 archaeological datasets Custom data extraction application Conversion of controlled terminology 6 thesauri converted to SKOS 27 glossaries created in SKOS Created based on recording manuals MultiTes XSL transformation to SKOS
10 Custom Data Extraction Application <?xml version="1.0"?> <rdf:rdf xml:base= xmlns:crm= xmlns:crmeh= xmlns:rdf= xmlns:rdfs= > <crmeh:ehe0007.context rdf:about=" <crm:p3f.has_note> <crmeh:ehe0046.contextnote rdf:about=" <rdf:value>upper ploughsoil over whole site no Sub-division for the convenience of finds processing '1' contains finds contexts '3759', '3760' and '3763'.</rdf:value> </crmeh:ehe0046.contextnote> </crm:p3f.has_note> </crmeh:ehe0007.context> <crmeh:ehe0007.context rdf:about=" <crm:p3f.has_note> <crmeh:ehe0046.contextnote rdf:about=" <rdf:value>original recorded coordinates: 0980/0960</rdf:value> </crmeh:ehe0046.contextnote> </crm:p3f.has_note> </crmeh:ehe0007.context> Etc. Generated RDF Data
11 Data Extraction and Consolidation Data Extraction resultant files 6 EH thesauri 6 RDF files 27 EH glossaries 27 RDF files 5 archaeological datasets 305 RDF files Data Consolidation - RDF triple store database 1,148,882 entities, 2,998,005 triples Diverse data held within single DB schema CRM, CRMEH, SKOS, OWL, DC etc. Platform independent import/export RDF-XML, NTriples, Turtle Inbuilt support for SPARQL queries Custom extension for full text search
12 SKOS Web Service and Client Applications Windows based client application SKOS Web Service Web browser based components ( widgets ) SKOS Client Applications
13 SKOS Client Windows Application
14 SKOS Client - Widgets Concept Search Concept Schemes Concept Details Concept Expansion
15 CRMEH Web Service and Client Application CRMEH Web Service Search and browse seamlessly across multiple archaeological datasets CRMEH Client Application
16 CRMEH Client Application
17 Next Steps Query builder expose support for complex query patterns (SPARQL) Closer integration of thesauri into overall search process Browser-based application components (AJAX) Include further archaeological datasets
18 STAR Semantic Technologies for Archaeological Resources
STAR Semantic Technologies for Archaeological Resources. http://hypermedia.research.glam.ac.uk/kos/star/
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