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Semantic interoperability


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Semantic interoperability

  1. 1. (Geospatial Semantics – Week 4) ANUSURIYA DEVARAJU Institute for Geoinformatics, University of Muenster. (
  2. 2. Here are some of the things you can expect to learn… What i i t Wh t is interoperability? H bilit ? How d does i t interoperability diff f bilit differ from integration? Types of heterogeneities Standards vs. Interpretation Semantic underpinning : Semantic Web Stack Geospatial Semantic Web : Broadening the current vision of Semantic p g Web to include geospatial data representation 2
  3. 3. Semantics– study of meaning ; focuses on the relation between symbols (e g (e.g. words) and what they stand for [wikipedia]– Our context : relations between the computer representations and the corresponding real world features features.Interoperability– Ability of diverse ‘systems’ to operate effectively and efficiently in conjunction, on the exchange and reuse of available resources, services, procedures, and information, according to the intended use of their providers … [Kavouras et al 2010]– ‘System’ do not refer strictly to technical systems. 3
  4. 4. Interoperability may occur at any six levels Levels of interoperability [Bishr 2010] 4
  5. 5. Semantic Interoperability– Focuses on preserving the semantics between communicating p g g entities.– Information is properly interpreted by the ‘receiver’ in the same sense as intended by ‘sender’. yInformation perspective : Integration vs. Interoperability- A fully interoperable solution also requires information integration to y p q g deal with interpretation of data.Semantic Integration– Subset of semantic interoperability [Kavouras 2010]– Necessitates the reconciliation of mismatches, heterogeneities, etc. 5
  6. 6. PrecipitationData is created and maintained independentlyDifferent interests of different provider groups.Diff ti t t f diff t idData is encoded in an uncoordinated way. 6
  7. 7. A Classification Scheme for Semantic and Schematic Heterogeneities in XML Data Sourcesby Pluempitiwiriyawej and Hammer (2000) – Structural conflicts, domain conflict, data conflicts , ,Sources and Classification of Semantic Heterogeneities by Bergman (2006) – Potential sources of heterogeneities: structural, domain, data, languageChanging Focus on Interoperability in Information Systems: From System, Syntax, Structureto Semantics by Sheth (1999) – semantic structural/representation, syntactic/format, system semantic, structural/representation syntactic/format heterogeneitiesOvercoming the semantic and other barriers to GIS interoperability by Bishr (1998) – D t b Database H t Heterogeneities: semantic, schematic, syntactic iti ti h ti t ti 7
  8. 8. Refers to the differences in data representation (i.e., encodings, languages and data format)Image source: 8
  9. 9. Differences in the types, structures of the elements EPA STORET – Water Quality ESRI ArcGIS Hydro Data Model DoD Spatial Data pStandards for Facilities, Infrastructure, and Environment Texas Commission on Environmental Quality 9
  10. 10. Cognitive heterogeneity – describe similar real word objects from different p p j perspectivesNaming heterogeneity – Synonyms, homonyms acronyms Data Stream flow Water Level Standing Water Air Precipitation Provider Level TemperatureDPIPWE Stream Flow River Level Met M (Meters below - Rainfall surface)BOM - WL - Temps RNHT Watercourse Watercourse - - Rainfall Discharge LevelWDS Stream Water level Bore Water Level Air Rainfall Discharge TemperatureMRT - - Standing Water Level - -(a)DPIPWE: Department of Primary Industries, Parks, Water and Environment; (b) BOM: Bureau of Meteorology; (c) HT: Hydro Tasmania;(d) WDS: Water Data Services; (e) MRT: Mineral Resources Tasmania 10
  11. 11. 1. Spatial data – Data schema to manage g g p g geographic features – Naming/coding schemes for features 2. Non-spatial data ( g , observations) p (e.g., ) – Data exchange language for observations or indicators – Vocabulary/dictionary schemes for parameters* Lefort L (2008), Technical report CSIRO ICT Centre 08/111 11
  12. 12. Geospatial features conceptual model and schema GML Encodes Feature Geometry and Properties* Feature representation in ArcHydro* 12
  13. 13. ISO 191** series (GI Metadata, Spatial Schema)OGC - GML, Web Feature Service (WFS), etc.DoD’s Spatial Data Standards for Facilities, Infrastructure and Environment (SDSFIE) FacilitiesINSPIRE Data SpecificationsEIONET Data DictionaryHydrology – USGS National Hydrography Dataset Standards – ESRI ArcHydro – National Hydrography Dataset Plus – INSPIRE Data Specification on HydrographyMeteorology – Climate Sciences Modelling Language (CSML) – Geo interface for Atmosphere Land Earth and Ocean netCDF (GALEON) Geo-interface Atmosphere, Land, Earth,Geology – GeoSciML 13
  14. 14. Observations exchange languages and vocabulary/dictionaryfor observed parameters STORET-NWIS Water-Quality Services Water observation encoding in WaterML 14
  15. 15. OGC SWE Framework (SensorML, O&M, etc.) Hydrology – CUAHSI (WaterOneFlow WaterML ODM master controlled vocabulary etc ) (WaterOneFlow, WaterML, vocabulary, etc.) – USGS StreamStats – NWIS + STORET parameter codes – EPA Water Quality Exchange (WQX) – French Data Reference Centre for Water (SANDRE) – Australian National Groundwater Data Transfer Standard (ANGDTS) – Hydro XC – Gl b l R Global Runoff D t C t (GRDC) D t F ff Data Centre Data Formatt – Australian Bureau of Meteorology - Water Data Transfer Format (WDTF)Meteorology – Climate Sciences Modelling Language (CSML) – NetCDF Climate and Forecast (CF) Metadata Conventions – NOAA NWS - National Digital Forecast Database (NDFD) Extensible Markup Language (XML) – NOAA Standard Hydrometeorological Exchange Format (SHEF) 15
  16. 16. Standards/specifications provide a syntactic approach toencoding geospatial information [Doerr 2004] – Source information needs adaptation to the standard. – Symbols in a data schema need to be interpreted by users. – A standard is one for its domain It cannot be optimal for all domain. applications.Semantic interoperability requires [Kavouras 2010]] p y q [ – Existing heterogeneities identification – Their importance and priority analysis – A systematic strategy too resolve them 16
  17. 17. The Semantic Web = a Web with a meaning A definition by Tim Berners Lee et al. (2001) Lee, al “The Semantic Web is an extension of the current web in which information is given well- defined meaning, better enabling computers and people to work in cooperation.” Idea : to allow computer machines to understand semantics of contents which are distributed in the Web*Image : 17
  18. 18. Unicode : character set for different human languages URI (Uniform Resource Identifier) identifies a web resource Reference System For GI is taught by Prof. Dr. Werner Kuhn GEO3880 Reference Systems for GI ont#taughtBy g y source (globe) : 18
  19. 19. XML (eXtensible Markup Language) – A markup language to ‘carry’ data, not to display data – XML tags are not predefined. You must define your own tags. – Problems : semantics is missing; no agreement on the vocabulary naming. g<?xml version=“1.0”?> <?xml version=“1.0”?><ifgi-courses> <university name = “muenster”><subject code =“GEO380” <institute> IFGIinstructor =“WK”> <courses-offered> GEO380 ReferenceReference System for GI System for GI</subject> <instructor>Prof. Dr. Werner Kuhn....... </instructor></ifgi-courses> </courses-offered> ....... </university> 19
  20. 20. Namespaces provide a method to avoid element name conflicts. Example* : HTML table vs. table (a piece of furniture)* 20
  21. 21. RDF (Resource Description Framework) – Written in XML – Describes resources on the web in triple form Resource Property Property Value(anything that can have a URI) (a Resource that ( the value of a Property; has a name) note that a property value also can be another Resource ) R http://ifgi...csa/ p g edu:taughtBy http://ifgi...../~kuhn/ http://ifgi /~kuhn/ RefSysGI Representation as RDF Graph p p 21
  22. 22. A Statement = a Resource + a Property + a Property value((known as the subject, predicate and object of a Statement) j ,p j ) 22
  23. 23. RDFS - RDF’s vocabulary description language– Example : rdfs:Class, rdfs:Literal, rdfs:Property, rdfs:Datatype…… p , , p y, yp 23
  24. 24. 24
  25. 25. RDFS is useful, but doesnt solve all the possiblerequirements; complex applications may require more q ; p pp y qpossibilities.OWL is an ontology language; extends RDF with morevocabulary to describe properties and classes: • Equivalency - owl:sameAs, owl:equivalentProperty…. • Property characteristics - owl:inverseOf, owl:TransitiveProperty…. • Property type restrictions - owl:allValuesFrom, owl:intersectionOf.. • Header ontology information – owl:imports, owl:priorVersion….Three flavors of OWL : OWL Lite OWL DL OWL Full Lite, DL, 25
  26. 26. Example 1: Identifying inverse properties (owl:inverseOfProperty)This allows a reasoner to infer that :<Course> <taughtBy> <AcademicStaffMember> 26
  27. 27. Example 2: Equivalent Individuals (owl:sameAs). The following two URIreferences actually refer to the same professor 27
  28. 28. An RDF query language comprises – Prefix declarations (PREFIX) ( ) – Dataset definitions (FROM) – A result clause (SELECT) – Query Pattern (WHERE) – Query Modifiers (e.g., ORDER BY, FILTER, etc.) Get all instances of a particular class (e g Course) : (e.g. PREFIX edu:<> SELECT ?a WHERE { ?a rdf:type edu:Course. }Note: Declaration of rdf, rdfs prefixes omitted for clarity 28
  29. 29. An RDF query language comprises – Prefix declarations (PREFIX) ( ) – Dataset definitions (FROM) – A result clause (SELECT) – Query Pattern (WHERE) – Query Modifiers (e.g., ORDER BY, FILTER, etc.) Get all instances of a particular class (e g Course) : (e.g. PREFIX edu:<> SELECT ?a WHERE { ?a rdf:type edu:Course. }Note: Declaration of rdf, rdfs prefixes omitted for clarity 29
  30. 30. Tim Berners-Lee (2001) Tim, Lucy, and The Semantic Web…An imaginary girl named Lucy, whose mother has just been told by her doctor that she needs to seea specialist At the doctor’s office Lucy instructed her Semantic Web agent through her handheld specialist. doctor s office,Web browser. The agent promptly retrieved information about Mom’s prescribed treatment from thedoctor’s agent, looked up several lists of providers, and checked for the ones in-plan for Mom’sinsurance within a 20-mile radius of her home and with a rating of excellent on trusted rating g gservices. SPACE TIME THEME GI usually deals entities which exists in the real world, their physical locations and temporal properties 30
  31. 31. River in Newcastle… Newcastle UKNewcastleAustraliaThe need for spatial component within Semantic Web Example : geospatial data + spatial operator [Egenhofer, 2002] 31
  32. 32. What is ‘Amsterdam’ to a computer… 32
  33. 33. A definition by Thuraisingham et al. (2008)…“Geospatial semantic web refers to an intelligent, machine understandable web wheregeospatial data are encoded in a semantic rich data model to facilitate automated decision semantic-richmaking and efficient data integration.” One of the immediate research priorities proposed b UCGIS i iti d by UCGIS, 2002. *(GSWIE) Why GSW? y unstructured /informal – The need to include space & GI in the Web time dimensions to the Semantic Web – Web users search exclusively for geospatial data on the Web structured geo-databases scientific materials (Different forms of Geographic Information on the Web) 33
  34. 34. Source : Bishr (2008), Geospatial Semantic Web: Applications 34
  35. 35. (Querying Layer) (Logical Layer) GeoSPARQL W3C GeoOWL, GeoNames Ontology, SWEET, CSDGM, etc. Querying : SPARQL Ontologies : OWL (Ontological Primitive Layer) Taxonomies: RDFS (Individuals) SKOS Data Interchange: RDF Syntax: XML (Basic Relational Language Layer) Identifiers: URI W3C Geo (GeoRDF), rdfgeom2d (Symbol/Reference Layer) (Transport/Syntax Layer) RFC 5870 GeoURI GML Google KML GeoRSS μFormat etc. GML, KML, GeoRSS, μFormat, etcOWL ontologies: 35
  36. 36. Building highly formalized representations (e.g., ontologies)of the available geographic information resources g g pLinking and mapping informal geo-centric resources to thehighly formalized representation structures being built by theSemantic WebGeospatial query – formulate geospatial request, representthe results (URI or real spatial data) ( p )Geo-data distribution policy and legal issues 36