Linked Data Hypercubes - Semtech London

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Presentation on the Data Cube vocabulary, and its uses, given at the Semantic Technologies Business Conference in London.

Presentation on the Data Cube vocabulary, and its uses, given at the Semantic Technologies Business Conference in London.

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  • 1. Linked data hypercubes
    Dave Reynolds, Epimorphics Ltd
  • 2.
  • 3. Linked Data - great for describing “things”
    data
    e.g. Schools in England and Wales
  • 4. Linked Data - great for describing “things”
    data
    model
    ontology development
    classifications
    phase of education
    location, contact
    reporting
    class sizes etc
    URI scheme
    reference data to link to
    admin geography, LLSC, charity ...
  • 5. Linked Data - great for describing “things”
    data
    model
    publish
    convert to RDF in a triple store
    entity URIs as linked data
    SPARQL endpoint
    Linked data API
  • 6. Linked Data - great for describing “things”
    data
    model
    publish
    use
  • 7. But what about ... data
    Government budget analysis
    local authority spend with suppliers
    regional demographic trends
    performance metrics
    air quality measurements
    energy consumption
  • 8. Publishing tabular data as linked data
    ?
    why?
    how?
    does it work?
  • 9. Benefits
    data slices and values becomes addressable
    annotate, explain, qualify values
    provenance for values
    trace back for derived reports
    integrate, compare, slice across datasets
    common terms for dimensions and units
    common identifiers for values (regions, departments ...)
    link to non-tabular data
    put the data in context
  • 10. Data cube vocabulary
    collaborative development sponsored by data.gov.uk
    simple, flexible vocabulary
    mirrors core information models from:
    SDMX (Statistical Data and Metadata eXchange)
    DDI (Data Documentation Initiative)
    extension to SCOVO vocabulary
  • 11. Data cube model
    A set of observations
    indexed by dimensions
    describing measures
    interpreted according to attributes
    attributes
    measure(s)
    dimension(e.g. region)
    • population = 32,567
    unit of measure = count
    status = preliminary
    ...
    dimension(e.g. time)
  • 12. Data cube vocabulary1. Top level
    DataSet
    provenance and metadata
    structure
    qb:component
    qb:DataStructureDefinition
    qb:sliceKey
    qb:structure
    qb:SliceKey
    qb:DataSet
    qb:slice
    qb:sliceStructure
    qb:dataset
    qb:Slice
    qb:subSlice
    qb:observation
    qb:Observation
    dimension valuesmeasure value(s)
    attribute values
  • 13. Data cube vocabulary1. Top level
    DataSet
    provenance and metadata
    structure
    Observation
    measured values, at dimensions with attributes
    direct link to DataSet
    qb:component
    qb:DataStructureDefinition
    qb:sliceKey
    qb:structure
    qb:SliceKey
    qb:DataSet
    qb:slice
    qb:sliceStructure
    qb:dataset
    qb:Slice
    qb:subSlice
    qb:observation
    qb:Observation
    dimension valuesmeasure value(s)
    attribute values
  • 14. Data cube vocabulary1. Top level
    DataSet
    provenance and metadata
    structure
    Observation
    measured values, at dimensions with attributes
    direct link to DataSet
    Slice
    optional grouping by fixing dimensions
    guide to presentation
    allows for abbreviated data
    qb:component
    qb:DataStructureDefinition
    qb:sliceKey
    qb:structure
    qb:SliceKey
    qb:DataSet
    qb:slice
    qb:sliceStructure
    qb:dataset
    qb:Slice
    qb:subSlice
    qb:observation
    qb:Observation
    dimension valuesmeasure value(s)
    attribute values
  • 15. Data cube vocabulary2. Data Structure Definition
    explicit definition of cube structure, inline in the data
    enables
    validation
    visualization
    discovery
    abbreviation
    still open world
    qb:DataSet
    qb:structure
    qb:DataStructureDefinition
    qb:component
    qb:ComponentSpecification
    qb:componentRequired qb:componentAttachment qb:order
    qb:dimension
    qb:measure
    qb:attribute
  • 16. Data cube vocabulary3. Coding values
    numeric or symbolic
    explicit link to coding scheme
    allows for hierarchical codes
    SDMX coding schemes and role markers available
    qb:ComponentProperty
    qb:concept
    qb:DimensionProperty
    qb:measureType
    skos:Concept
    qb:AttributeProperty
    sdmx:Concept
    qb:MeasureProperty
    sdmx:ConceptRole
    qb:CodedProperty
    qb:codeList
    sdmx:FrequencyRolesdmx:CountRolesdmx:EntityRolesdmx:TimeRole
    sdmx:MeasureTypeRole
    sdmx:NonObsTimeRole
    sdmx:IdentityRole
    sdmx:PrimaryMeasureRole
    skos:ConceptScheme
    sdmx:CodeList
  • 17. Example
    eg:dsd-le a qb:DataStructureDefinition;
    # The dimensions
    qb:component [qb:dimension eg:refArea; qb:order 1];
    qb:component [qb:dimension eg:refPeriod; qb:order 2];
    qb:component [qb:dimension sdmx-dimension:sex; qb:order 3];
    # The measure(s)
    qb:component [qb:measure eg:lifeExpectancy];
    # The attributes
    qb:component [qb:attribute sdmx-attribute:unitMeasure;
    qb:componentAttachment qb:DataSet;] .
    eg:dataset-le1 a qb:DataSet;
    rdfs:label "Life expectancy"@en;
    rdfs:comment "Life expectancy in Welsh Unitary authorities"@en;
    qb:structure eg:dsd-le ;
    sdmx-attribute:unitMeasure <http://dbpedia.org/resource/Year> .
    eg:o1 a qb:Observation;
    qb:dataset eg:dataset-le1 ;
    eg:refArea admingeo:newport_00pr ;
    eg:refPeriod <http://reference.data.gov.uk/id/year/2004> ;
    sdmx-dimension:sex sdmx-code:sex-M ;
    eg:lifeExpectancy 76.7 .
  • 18. Case study: Local government payments
    data
    UK local authorities publish data on all spending above £500
    linked data version to enable comparison
  • 19. Case study: Local government payments
    data
    model
    cube structure
    measure
    amount net of recoverable VAT
    attributes
    currency
    dimensions
    time
    payer
    payee
    expenditure code
    item
    package as an ontology
  • 20. Case study: Local government payments
    data
    model
    publish
    visualizations
    LD API
    API structure mirrors cube dimensional structure
  • 21. Case study: Local government payments
    data
    model
    publish
    use
  • 22. Case study: Environmental monitoring
    data
    • Environment Agency bathing water quality monitoring
    • 23. samples
    • 24. assay
    • 25. compliance assessment
  • Case study: Environmental monitoring
    data
    model
    measures
    total coliform count, entero virus count, ...
    sample classification
    dimensions
    sampling point
    sampling week
    sampling year
    attributes
    abnormal weather
  • 26. Case study: Environmental monitoring
    data
    model
    publish
    visualizations
    LD API
    API structure mirrors cube dimensional structure
  • 27. Case study: Environmental monitoring
    data
    model
    publish
    use
  • 28. Data Cube : Summary
    foundational approach to publishing multi-dimensional data as linked data
    enables
    addressing – annotate, explain, provenance, context
    integration – slice, dice and compare across sets
    puts data in context
    explicit declarative structure =>
    validation
    discovery
    automation - web APIs, visualizations, exploration tools
  • 29. Acknowledgements
    John Sheridan (The National Archive)
    for sponsoring the development of data cube
    Richard Cyganiak, JeniTennison
    co-developers of the data cube vocabulary
    Paul Davidson
    instigator of the Payments ontology
    Stuart Williams, Ian Dickinson
    developers of the bathing water use case
    Photos:
    dullhunk @ flickr Martin Pettitt @ flickr
    kikasso @ flickrTax_Rebate @ fliCkr