Linked Data Hypercubes - Semtech London
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The document discusses the implementation of linked data hypercubes for describing various datasets, particularly in education and local government contexts. It emphasizes the use of a data cube vocabulary for organizing and making sense of multi-dimensional data, allowing for better integration, comparison, and visualization. Several case studies illustrate the effectiveness of this framework in real-world applications, such as environmental monitoring and local authority spending data.
![Exampleeg: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 .](https://image.slidesharecdn.com/reynoldsdavid-111004081457-phpapp02/85/Linked-Data-Hypercubes-Semtech-London-17-320.jpg)
Linked Data Hypercubes - Semtech London
- 1. Linked data hypercubesDave Reynolds, Epimorphics Ltd
- 3. Linked Data - great for describing “things”datae.g. Schools in England and Wales
- 4. Linked Data - great for describing “things”datamodelontology developmentclassificationsphase of educationlocation, contactreportingclass sizes etcURI schemereference data to link toadmin geography, LLSC, charity ...
- 5. Linked Data - great for describing “things”datamodelpublishconvert to RDF in a triple storeentity URIs as linked dataSPARQL endpointLinked data API
- 6. Linked Data - great for describing “things”datamodelpublishuse
- 7. But what about ... dataGovernment budget analysislocal authority spend with suppliersregional demographic trendsperformance metricsair quality measurementsenergy consumption
- 8. Publishing tabular data as linked data?why?how?does it work?
- 9. Benefitsdata slices and values becomes addressableannotate, explain, qualify valuesprovenance for valuestrace back for derived reportsintegrate, compare, slice across datasetscommon terms for dimensions and unitscommon identifiers for values (regions, departments ...)link to non-tabular dataput the data in context
- 10. Data cube vocabulary collaborative development sponsored by data.gov.uksimple, flexible vocabularymirrors core information models from:SDMX (Statistical Data and Metadata eXchange)DDI (Data Documentation Initiative)extension to SCOVO vocabulary
- 11. Data cube modelA set of observationsindexed by dimensionsdescribing measuresinterpreted according to attributesattributesmeasure(s)dimension(e.g. region) population = 32,567unit of measure = countstatus = preliminary...dimension(e.g. time)
- 12. Data cube vocabulary1. Top levelDataSetprovenance and metadatastructure qb:componentqb:DataStructureDefinitionqb:sliceKeyqb:structureqb:SliceKeyqb:DataSetqb:sliceqb:sliceStructureqb:datasetqb:Sliceqb:subSliceqb:observationqb:Observationdimension valuesmeasure value(s)attribute values
- 13. Data cube vocabulary1. Top levelDataSetprovenance and metadatastructure Observationmeasured values, at dimensions with attributesdirect link to DataSetqb:componentqb:DataStructureDefinitionqb:sliceKeyqb:structureqb:SliceKeyqb:DataSetqb:sliceqb:sliceStructureqb:datasetqb:Sliceqb:subSliceqb:observationqb:Observationdimension valuesmeasure value(s)attribute values
- 14. Data cube vocabulary1. Top levelDataSetprovenance and metadatastructure Observationmeasured values, at dimensions with attributesdirect link to DataSetSliceoptional grouping by fixing dimensionsguide to presentationallows for abbreviated dataqb:componentqb:DataStructureDefinitionqb:sliceKeyqb:structureqb:SliceKeyqb:DataSetqb:sliceqb:sliceStructureqb:datasetqb:Sliceqb:subSliceqb:observationqb:Observationdimension valuesmeasure value(s)attribute values
- 15. Data cube vocabulary2. Data Structure Definitionexplicit definition of cube structure, inline in the dataenablesvalidationvisualizationdiscoveryabbreviationstill open worldqb:DataSetqb:structureqb:DataStructureDefinitionqb:componentqb:ComponentSpecificationqb:componentRequired qb:componentAttachment qb:order qb:dimensionqb:measureqb:attribute
- 16. Data cube vocabulary3. Coding valuesnumeric or symbolicexplicit link to coding schemeallows for hierarchical codesSDMX coding schemes and role markers availableqb:ComponentPropertyqb:conceptqb:DimensionPropertyqb:measureTypeskos:Conceptqb:AttributePropertysdmx:Conceptqb:MeasurePropertysdmx:ConceptRoleqb:CodedPropertyqb:codeListsdmx:FrequencyRolesdmx:CountRolesdmx:EntityRolesdmx:TimeRolesdmx:MeasureTypeRolesdmx:NonObsTimeRolesdmx:IdentityRolesdmx:PrimaryMeasureRoleskos:ConceptSchemesdmx:CodeList
- 17. Exampleeg: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 paymentsdataUK local authorities publish data on all spending above £500linked data version to enable comparison
- 19. Case study: Local government paymentsdatamodelcube structuremeasureamount net of recoverable VATattributescurrencydimensionstimepayerpayeeexpenditure codeitempackage as an ontology
- 20. Case study: Local government paymentsdatamodelpublishvisualizationsLD APIAPI structure mirrors cube dimensional structure
- 21. Case study: Local government paymentsdatamodelpublishuse
- 22. Case study: Environmental monitoringdataEnvironment Agency bathing water quality monitoring
- 23. samples
- 24. assay
- 25. compliance assessmentCase study: Environmental monitoringdatamodelmeasurestotal coliform count, entero virus count, ...sample classificationdimensionssampling pointsampling weeksampling yearattributesabnormal weather
- 26. Case study: Environmental monitoringdatamodelpublishvisualizationsLD APIAPI structure mirrors cube dimensional structure
- 27. Case study: Environmental monitoringdatamodelpublishuse
- 28. Data Cube : Summaryfoundational approach to publishing multi-dimensional data as linked dataenablesaddressing – annotate, explain, provenance, contextintegration – slice, dice and compare across setsputs data in contextexplicit declarative structure =>validationdiscoveryautomation - web APIs, visualizations, exploration tools
- 29. AcknowledgementsJohn Sheridan (The National Archive) for sponsoring the development of data cubeRichard Cyganiak, JeniTennisonco-developers of the data cube vocabularyPaul Davidson instigator of the Payments ontologyStuart Williams, Ian Dickinsondevelopers of the bathing water use casePhotos:dullhunk @ flickr Martin Pettitt @ flickrkikasso @ flickrTax_Rebate @ fliCkr