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Open Provenance Model Tutorial Session 4: Use cases from data.gov.uk. Outline. Background about data.gov.uk The use cases XML serialization Data transformation on the fly Complex and nested processes. data.gov.uk. Linking UK government data Aims:
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Open Provenance Model TutorialSession 4: Use cases from data.gov.uk
Outline • Background about data.gov.uk • The use cases • XML serialization • Data transformation on the fly • Complex and nested processes
data.gov.uk • Linking UK government data • Aims: • Provide a set of best practices for government agencies • Provide the minimum set of tooling and specification to facilitate the publication of data • Encourage “responsible” data publishing
XML -> RDF XSLT Parameter Binding RDF File input XSLT Processor output XSLT Stylesheet XSLT Template Who, when, which version, how
Downloaded from; Unzipped from, etc input XSLT Processor output Made accessible RDF File XSLT Parameter Binding XSLT Stylesheet Who, when, which version, how XSLT Template
On-the-fly Transformation Who, when, which version, how http://mytransportatio.db/j10 Data transformation wrapper
Complex Data Creation Pipeline GATE Pipeline GateXMLRegressionTransformation GateXMLRdfaTransformation RdfaRdfXmlTransformation Courtesy of Paul Appleby from TSO (Data Enrichment Service)
Complex Data Creation Pipeline Document Reset PR GATE Pipeline ANNIE English Tokeniser ANNIE English Splitter GateXMLRegressionTransformation ANNIE POS Tagger Data.gov.uk Morphological Analyzer Data.gov.uk Flexible Roof Gazetteer GateXMLRdfaTransformation Data.gov.uk Generic Gazeteer GATE Noun Phrase Chunker RdfaRdfXmlTransformation Data.gov.uk Generic Transducer TSO Coreference Courtesy of Paul Appleby from TSO (Data Enrichment Service)
Services used by executions accessedService wasTriggeredBy wasTriggeredBy Level 1: Provenance of execution at higher level iterationOfProcess hasParentProcess followed Level 0: Provenance of execution at detailed level wasGeneratedBy wasGeneratedBy wasGeneratedBy Artifacts A data collection wasDerivedFrom
Non-digital Data Objects • Organizations • Organizational structure changes over time • Origin organization, resulting Organization • Boundary • Legislation An organization ontology: http://www.epimorphics.com/public/vocabulary/org.html
The Challenges • Data of different representations, of physical forms, of granularity • Not tooling support • Provenance across different types of systems • Identification • Different terminologies
The Gaps • A vocabulary being able to describe provenance of all types of data, from different systems • A vocabulary still providing enough terms to describe provenance accurately
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