Upload
tegan
View
23
Download
0
Tags:
Embed Size (px)
DESCRIPTION
STELLAR Introduction Ceri Binding, Douglas Tudhope Hypermedia Research Unit, University of Glamorgan. STELLAR. 12 month AHRC funded project Hypermedia Research Unit, University of Glamorgan Archaeology Data Service, University of York English Heritage Centre for Archaeology, Portsmouth - PowerPoint PPT Presentation
Citation preview
STELLAR IntroductionCeri Binding, Douglas Tudhope
Hypermedia Research Unit, University of Glamorgan
STELLAR
12 month AHRC funded project Hypermedia Research Unit, University of Glamorgan Archaeology Data Service, University of York– English Heritage Centre for Archaeology, Portsmouth
Builds on previous 3 year AHRC funded STAR Project
Acknowledgments
Andreas Vlachidis (University of Glamorgan)
Keith May, English Heritage (EH)
Stuart Jeffrey, Julian Richards, Michael Charno, Tim Evans, Holly Wright
Archaeology Data Service (ADS)
Archaeology Department, University of York
STAR – Aims and background
• Investigate semantic technologies for integrating and cross searching datasets and associated grey literature
• Current situation - fragmented datasets with different terminology
• Lack of semantic interoperability and cross search
• Need for integrative metadata framework CIDOC CRM (ISO standard) as high level, core ontologytogether with the CRM-EH archaeological extension of the CRM
along with relevant EH thesauri and glossaries
STAR Project - General Architecture
RRAD RPRE
RDF Based Semantic Layer (CRM / CRMEH / SKOS)
Greyliterature
EH thesauri,
glossaries
LEAPSTAN MoLAS
Data Mapping / NormalisationConversionIndexing
Web Services, SQL, SPARQL
Applications – Server Side, Rich Client, Browser
Natural Language Processing (NLP)of archaeological grey literature
Extract key concepts in same semantic representation as for data.
Allows unified searching of different datasets and grey literature
in terms of same underlying CRM-based conceptual structure
Output as RDF triples in Demonstrator and as XML with greylit
“ditch containing prehistoric pottery dating to the Late Bronze Age”
STAR Demonstrator – search for a conceptual pattern
An Internet Archaeology publication on one of the (Silchester Roman) datasets we used in STAR discusses the finding of a coin
within a hearth.-- does the same thing occur in any of the grey literature reports?
Requires comparison of extracted data with NLP indexing in terms of the ontology.
STELLAR aims and outcomes
• Make it easier to map and extract datasets to CIDOC CRM ontology
in a consistent manner
• Generalise the data extraction tools produced by STAR
so third party data providers can use them
• Develop methods for mapping and extraction of archaeological
datasets into RDF/XML conforming to CIDOC CRM-EH ontology
with unique global identifiers for entities and concepts (http URIs)
for publication as linked data
• Freely available tools and guidelines/tutorials
STELLAR background
• In practice mapping to CRM has tended to require specialist knowledge of the ontology
and been resource intensive
• Given the wide scope of the CRM, it is possible to make multiple valid mappings
depending on the intended purpose and focus of the mappings
• STELLAR tools convert archaeological data to CRM/RDF in a consistent manner,
without requiring detailed knowledge of the underlying ontology
• User chooses a template for a particular data pattern
and supplies the corresponding input from their database
(combination of optional elements with a mandatory ID)
• STELLAR templates for – CRM-EH archaeological extension to the CIDOC CRM– Some more general CIDOC CRM templates conforming to the CLAROS Project format– SKOSifying a glossary/thesaurus connected with the dataset – Also capability for user-defined templates
STELLAR Applications
STELLAR.Console
STELLAR.Web STELLAR.Win
import
DatabaseDatabase
Internal templateInternal template
SQL query results
SQL query results
Delimited DataDelimited Data
Data from file
SQL query results
User-defined template
User-defined template
RDF dataRDF data
Other textualData formatsOther textualData formats
Data from file
SQL commands
STELLAR data conversions
// STELLAR template to write RDF header
HEADER(options) ::= <<
<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
xmlns:crm="http://www.cidoc-crm.org/rdfs/cidoc-crm#">
>>
// Template writes RDF entities and properties based on each data row;
// $placeholder.value$ is replaced with the named field data at runtime
RECORD(options, data) ::= <<
<crm:E53 rdf:about="#E53_$data.id$">
<crm:P87F rdf:resource="#E44_$data.id$“/>
</crm:E53>
<crm:E44 rdf:about="#E44_$data.id$">
<rdfs:label xml:lang="it">$data.name$</rdfs:label>
<crm:P87B rdf:resource="#E53_$data.id$“/>
</rdf:Description>
>>
// STELLAR template to write RDF footer – closure of header elements
FOOTER(options) ::= "</rdf:RDF>"
Using STELLAR templates to produce RDF•Templates are just text files. May be copied, edited, exchanged, disseminated.
•XML/RDF syntax and namespace details are handled within the template.
•User input is simple tabular delimited textual data with named fields, e.g.:
id, name1, Bergamo2, Milano Centrale3, Bologna Centrale4, Prato Centrale
•Predefined patterns of entities, properties and inverse properties are created by the template, data populates placeholders at runtime.
•Output is consistent and repeatable.
Archaeology Data Service (ADS) Linked Data
Linked data publication by ADS
• Selected range of archived archaeological excavation datasets (academic and commercial sectors) converted to RDF using STELLAR tools
and ingested into a repository (triple store)
• The SPARQL endpoint allows consumption by semantic technologies
including Pubby (an open source linked data front end) used for publishing linked data
• Content negotiation presents data in formats appropriate for the requesting application
(eg RDF/XML/HTML browsers).
• Effort devoted to ensure URI construction appropriate for the domain.
For ADS archives this includes use of existing DOI identifier codes in the target URI.
For external data sets (not already archived with the ADS, eg from commercial contractors)
site naming conventions validated by the ADS adopted.
• The linked data outputs (and the frontend) are available from ADS website
http://data.archaeologydataservice.ac.uk
Using the RDF data
RDF application / triple store
RDF application / triple store
SPARQL queries RDF enabled applicationsLinked data
browsers
RDF data output from STELLAR
Contact Information
Douglas Tudhope
Faculty of Advanced Technology
University of Glamorgan
Pontypridd CF37 1DL
Wales, UK
http://hypermedia.research.glam.ac.uk/kos/STAR/
http://hypermedia.research.glam.ac.uk/resources/star-demonstrator/
STAR Research Demonstrator
http://intarch.ac.uk/journal/issue30/tudhope_index.html
STAR Internet Archaeology paper (open access)
http://andronikos.kyklos.co.uk/aboutus.php
NLP work - see reports with CRM and CRM-EH composite annotations in Sample Documents
http://hypermedia.research.glam.ac.uk/kos/STELLAR/
http://hypermedia.research.glam.ac.uk/resources/STELLAR-applications/
STELLAR tools, templates and documentation
http://data.archaeologydataservice.ac.uk
STELLAR linked data