1 / 24

Representing Contextual Aspects of Data

Representing Contextual Aspects of Data. WP2 - Andreas Harth. 1st year review Luxembourg, December 2011. Work Plan View. 24. 12. 0. 6. 18. 30. 36. 42. 48. D2.1 Conceptual model and best practices for high-quality data publishing. D2.2 Methods for quality repair.

baird
Download Presentation

Representing Contextual Aspects of Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Representing Contextual Aspects of Data WP2 - Andreas Harth 1st year review Luxembourg, December 2011

  2. Work Plan View 24 12 0 6 18 30 36 42 48 D2.1 Conceptualmodelandbestpracticesfor high-quality datapublishing D2.2 Methodsforqualityrepair D2.6 Methodsforassessingthequalityofsensordata Task 2.1 Data qualityassessmentandrepair D2.4 Update of D2.1 FUB D2.3 Modellingandprocessingcontextualaspectsofdata D2.5 Proof-of-conceptevaluationformodellingspaceand time Task 2.2 Temporal, spatial and social aspects of data KIT D2.7 Recommendationsforcontextualdatapublishing Task 2.3 Recommendationsforenhancingbestpracticesfordatapublishing KIT

  3. Outline • Motivation • NeoGeoVocabularies • Mappingsand Community Activities • Demo • Conclusionand Future Work

  4. Motivation

  5. Motivation • Geospatial data is becoming increasingly relevant • Location-based services, mobile applications • Ever increasing amount of sensor data (phones, satellites…) • Applications require integrated access to geospatial data • Spatial querying • Spatial reasoning

  6. Geospatial Data Scenario Integration Wrapper 1 Mapping 1 Mapping 2 Mapping n ... Source 1 Source 2 Source n

  7. Challenges • Disparate dataformats • Integrated dataformat (syntax) andaccess (datatransferprotocol) - LinkedData (RDF, HTTP) • Most datasourcesprovide just points (geo:lat, geo:long) • Create vocabulary/methodforpublishingregions • Eachdatasourceusesownwaytoencodegeospatialdata • Allowforsyntaxdifferences, providemappingswherepossible (KML, GML, WKT, RDF…) • Instance data not interlinkedacrosssources • Create mappingsbetweeninstances • Geospatialdataispolitical

  8. „Unpolitical“ Datasets • GADM-RDF– http://gadm.geovocab.org/ • RDF representation of the administrative regions of the GADM project (http://gadm.org/) • NUTS-RDF– http://nuts.geovocab.org/ • RDF representation of Eurostat's NUTS nomenclature. GADM and NUTS serve as: • New geospatial information on the Semantic Web. • Bridges between already published spatial datasets. • Experimentation and evaluation datasets.

  9. NeoGeoVocabularies

  10. Prototypical Geo-Ontology Feature Geometry geometry Spatialfunctions Spatialrelations geometry „Luxembourg“ in „Europe“

  11. Features vs. Geometries • NeoGeo vocabularies are based on the General Feature Model • General Feature Model makes a distinction between the feature (resource to which the region belongs), and the actual geometry. • Semantics of the feature are more important than the representation of the geometry. • Instances of the feature are related to the type of the feature. • A feature can be related to multiple distinct geometries; also allows for modelling different geometric properties for one single feature (e.g. different scales).

  12. NeoGeo Vocabularies • Spatial Vocabulary • Representation and reasoning on topological relations based on the Region Connection Calculus (RCC). • Geometry Vocabulary • Representation of geo-referenced geometric shapes. spatial:Feature ngeo:Geometry ngeo:geometry spatial:* RESTfulservices RCC: Randell, D. A., Cui, Z. and Cohn, A. G.: A spatial logic based on regions and connection, 3rd Int. Conf. on Knowledge Representation and Reasoning, 1992.

  13. Modelling Spatial Relations

  14. RCC-8 Properties proper part (PP) proper part inverse (Ppi) part (P) part inverse (Pi) overlaps (O) connectswith (C) discretefrom (DR) partiallyoverlapping (PO) tangential proper part (TPP) non-tangential proper part (NTPP) equal (EQ) tangential proper part inverse (TPPi) non-tangential proper part inverse (NTPPi) externallyconnected (EC) disconnected(DC)

  15. SpatialVocabulary • http://geovocab.org/spatial# • Uses RCC for the representation of topological relations between regions • Supports RCC5 and RCC8 relations • Inference available for most RCC relations • However some rules require „negation as failure“, which requires closed world assumption

  16. Modelling Regions

  17. ModellingRegions - Alternatives • RDF List of W3C Geo Points • RDF List oflatitude/longitudepairs • RDF Literaloflatitude/longitude • RDF Literal in GML/WKT format (GeoSPARQL) • … • Geometries haveown URI, contentformatnegotiated (KML, GML, WKT…) • Geometryvocabularydescribes high-level featuresofgeospatialregions

  18. Mappingsand Community Activities

  19. VocabularyMappings SC: rdfs:subClassOf, SP: rdfs:subPropertyOf, SA: owl:sameAs

  20. Instance Mappings

  21. VoCamp • PlanningunderwayforVoCampat UPM (jointlyorganisedwith KIT), weekendof Feb 4th and 5th • Co-locatedwithVoCamp Santa Barbara. • http://vocamp.org/

  22. Demo!

  23. Summary • NeoGeovocabulariesandexperiences on publishing geo-spatialdataasLinked Data • NUTS and GADM datasets online • Integration vocabulary online, includingvocabularymappings • GADM mappingsto NUTS, DBpedia, LinkedGeoData… • Linked Data Services foraccessing/queryingspatialindices (withinRegion, boundingBox) • Work on similaritymetrics (withoptimisationsandevaluation) forgeospatialregions

  24. Future Work • FinaliseNeoGeo vocabularies (VoCamp) • Improvement of precision of spatial similarity; publish similarity service online • More instance mappings to GADM • Earth and space science data • More experiments: querying of integrated data • Reasoning • Temporal context • First deliverable due in March 2012

More Related