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Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
Laurini - input2012
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Laurini - input2012

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Robert Laurini on "Geographic Ontologies and Spatial Relations"

Robert Laurini on "Geographic Ontologies and Spatial Relations"

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  • 1. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Example of ontology Physical city Aggregation or Tesselation Network Spatial City-blocks relation Streets Ontologies for geographic 1 – Introduction applications • 1 – Introduction • Oντος = being ; Λογια = discourse • 2 – Theoretical bases of spatial ontologies • Aristotle: « The study of existing objects » • 3 – Spatial relationships • Def1: theory of objects and their relations • 4 – GeoOWL • Def2: theory of entities, especially of entities • 5 – Gazetteers which exist in a language • 6 – Conclusions • Def3: explicit specification of conceptualization (Gruber)INPUT 2012 1
  • 2. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Guarino’s definition Ontological commitment • Nicola Guarino : “An ontology is • Usually, several definitions for the same generally regarded as a designed artifact entity, for instance a horse, a table, etc. consisting of a specific shared vocabulary • used to describe entities in some domain • Several agents/shareholders agree to a of interest, as well as a set of assumptions common definition of an object about the intended meaning of the terms • Consensus about a definition in the vocabulary” • Shared vocabulary Concepts Example about roads • Distinguish between terms and concepts • Distance (km or mile) syntactic • At mathematical level : • Street or motorways semantic Ontology = graph between concepts = semantic networkINPUT 2012 2
  • 3. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini We do have the road file! We do have the road file! The road The road file? The road Water Supply file? Garbage men Postmen Yes, I’ve it file? Company Yes, I’ve it Yes, we’ve it Private roads No Yes ?? Generally Public roads Yes Yes yes Road with ? ? Yes water supply Road without ? ? No Water supply Total 234 251 241 Beginning of an urban ontoloy Beginning of an urban ontoloy City Houses Apartments Land space Network Habitation Working places Built space Non-built space Demography Resides Works Human being Building etc. etc. Spends Recreation Shops Recreation placesINPUT 2012 3
  • 4. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini 2 – Theoretical bases of spatial Examples about coast ontologies • Generic concepts • Geographic objects • Spatial relations • Modeling Courtesy Jonathan Raper of City University London, GISci 2002 Keynote About Geographic Ontologies Geographic features • Two definitions • Geographic features – Conventional ontologies of geographic features – Crisp boundaries (with is-a and part-whole relations) – Fuzzy boundaries – Continuous fields – Ontologies with spatial relationships between • Modeling geographic features – Point, line, area volume – Multi-representations – Multi-scaleINPUT 2012 4
  • 5. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini CONOSCENZE SPAZIALI E CONOSCENZE GEOGRAFICHE Geographic Feature Types Fuzzy Geographic Objects Membership grades (0 – 100 %) • Geodetic objects River: Major bed, major bed • Administrative objects • Human-made features • Natural features 100% – With known boundaries (crisp) – With unknown boudaries (fuzzy) 80% – With « no » boundaries (continuous fields) 60% 40% R. Laurini Geodetic Objects Continent • Theoretical objects onto the geoid – Equator Sea – North and South Poles – Meridians – Parallels Mangrove • Modeled by points and circles Jungle • Basis for coordinatesINPUT 2012 5
  • 6. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Administrative objects Human-made features • No ligitations at boundaries • Made by humans • Non-connex planar polygons (2D) – Parcels, buildings, streets, bridge, tunnels, etc. • Often in hierarchical tesselations • Modeled by non-connex polygons (2D) or – Countries, regions, provinces, cities polyhedra (3D) – Natural parks • At some scale, roads are linear • Total coverage of the globe • At some scale, some objects can disappear Object geometry Multiple representation • Only one storing structure Street represented by a graph Street represented by two polylines • But many layout (mapping) structure issued Traffic Cadaster engineer by generalization officer • When layout geometry < threshold, then Street Street Technical object will disapear maintenance engineer network engineer Street represented Street represented by a surface by a volumeINPUT 2012 6
  • 7. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini 3 – Spatial relationships Spatial relations • Conventional spatial relations • Topological (Allen, Egenhofer, Clementini, etc.) • New spatial relations • Projective (cardinal) • Distances Egenhofer relations Projective relationsINPUT 2012 7
  • 8. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Main semantic properties Examples of spatial relations of geographic concepts Semantic properties Scope Date Agent Duration Coverage Size Shape Frequence Location Main semantic relations Jungert operators (1/2) of geographic concepts Semantic Relations SEPARATION IS-A A ADJACENCY A<B center(A) < center(B) B IS-PART-OF CONNECTIVITY A=B center(A) = center(B) AB HAS-PART OVERLAP RELATIVE POSITION INTERSECTION A|B Side by side A B CONTAINMENT SOURCE - DESTINATION EXCLUSION Min(A) > Min (B) A PROXIMITY A%B Max(A) < Max (B) SURROUNDNESS Length(A) < Length(B) B DIRECTION EXTENSIONINPUT 2012 8
  • 9. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Jungert operators (2/2) Streets Min(A) = Min (B) A A[B Length(A) < Length(B) B Max(A) = Max (B) A A]B Length(A) < Length(B) B Min(A) < Min (B) A AB Length(A) ≤ Length(B) B Sidewalk Lane Sidewalk Max(A) > Max (B) A A/B Length(A) ≤ Length(B) Lane B Motorway New spatial relations (2D) • Horizontally – Ribbon Median – Relations Lanes • End-to-end noted = • Side-by-side noted II Emergency lane Verge/ShoulderINPUT 2012 9
  • 10. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Motorway Sections Shoulder • Example: Motorway Emer. – Divided into « sections » End-to-end Lane Section = = Ribbon Ribbon = = – Each section divided into « ribbon » Side-by-side Lane = Median Motorway = = Section = Emerg. Section = = II Shoulder II II Lane II Median Lane II CONOSCENZE SPAZIALI E CONOSCENZE GEOGRAFICHE New spatial relations (3D) Mountain • Vertically – layer – Relations • Bottom-to-top • Top-to-bottom • End-to-end ==> Geology • Side-to-side Buildings R. LauriniINPUT 2012 10
  • 11. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Vegetation layers 4 – GeoOWL • Fuzzy layers • OWL: Ontology Web Language • As 3D objects (bottom-to-top) • Geographic ontology based on OWL • 8 million names for 6.5 million features • As 2D surfaces (side-by-side) • Modeling aspect • Links with avec GeoNames – Placenames (toponyms) – Name of features (in English) Key-concepts of GeoOWL GeoNames <owl:Class rdf:about="&gml;/_Feature" /> <owl:ObjectProperty rdf:about="&gml;/exterior"> <owl:Class rdf:about="&gml;/_Geometry" /> <owl:Class rdf:about="&gml;/Point"> <owl:DatatypeProperty rdf:about="&gml;/lowerCorner"> <owl:Class rdf:about="&gml;/Polygon"> <owl:DatatypeProperty rdf:about="&gml;/upperCorner"> <owl:Class rdf:about="&gml;/Envelope"> <owl:DatatypeProperty rdf:about="&gml;/featurename"> <owl:Class rdf:about="&gml;/LineString"> <owl:DatatypeProperty rdf:about="&gml;/featuretypetag"> <owl:Class rdf:about="&gml;/LinearRing"> <owl:DatatypeProperty rdf:about="&gml;/relationshiptag"> <owl:ObjectProperty rdf:about="&geo;/where"> <owl:DatatypeProperty rdf:about="&geo;/point"> <owl:DatatypeProperty rdf:about="&geo;/line"> <owl:DatatypeProperty rdf:about="&gml;/pos"> <owl:DatatypeProperty rdf:about="&geo;/polygon"> <owl:DatatypeProperty rdf:about="&geo;/box"> <owl:DatatypeProperty rdf:about="&gml;/posList"> <owl:DatatypeProperty rdf:about="&geo;/elev"> <owl:Class rdf:about="&gml;/Point"> <owl:Class rdf:about="&gml;/LineString"> <owl:DatatypeProperty rdf:about="&geo2003;#lat"> <owl:Class rdf:about="&gml;/LinearRing"> <owl:DatatypeProperty rdf:about="&geo2003;#long">INPUT 2012 11
  • 12. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini Sub-classes Excerpt from the list of geographic concepts • ontology:A country, state, region • DTCH ditch a small artificial watercourse dug for draining or irrigating the land • ontology:H (water bodies) • DTCHD drainage ditch a ditch which serves to drain the land • DTCHI irrigation ditch a ditch which serves to distribute irrigation water • ontology:L (parks, areas) • DTCHM ditch mouth(s) an area where a drainage ditch enters a lagoon, lake or bay • ESTY estuary a funnel-shaped stream mouth or embayment where fresh water mixes with sea water • ontology:P city, village • under tidal influences FISH fishing area a fishing ground, bank or area where fishermen go to catch fish • FJD fjord a long, narrow, steep-walled, deep-water arm of the sea at high latitudes, usually along • ontology:R road, railroad mountainous coasts • FJDS fjords long, narrow, steep-walled, deep-water arms of the sea at high latitudes, usually along • ontology:S spot, buildings, farms, • mountainous coasts FLLS waterfall(s) a perpendicular or very steep descent of the water of a stream • ontology:T mountain, hill, rock • • FLLSX section of waterfall(s) FLTM mud flat(s) a relatively level area of mud either between high and low tide lines, or subject to flooding • ontology:U undersea • FLTT tidal flat(s) a large flat area of mud or sand attached to the shore and alternately covered and uncovered by the tide • ontology:V forest, heath • GLCR glacier(s) a mass of ice, usually at high latitudes or high elevations, with sufficient thickness to flow away from the source area in lobes, tongues, or masses • GULF gulf a large recess in the coastline, larger than a bay GeoNames Ontology URI • Ex. : for Cagliari, there are 2 URI 1: City: http://www.geonames.org/maps/google_39.207_9.135.html 2: Province: http://www.geonames.org/maps/google_39.245_9.091.html – 1 : location – 2 : informationINPUT 2012 12
  • 13. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini http://sws.geonames.org/3020251/ Linked data • Components of Italy (contains) : http://www.geonames.org/3175395/contains.rdf • Neighboring countries of Italy (neighbours) : http://www.geonames.org/3175395/neighbours.rdf • Geographic features (For example, the Eiffel Tower) http://sws.geonames.org/6254976/nearby.rdf http://www.geonames.org/3175395/neighbours.rdf GeoNames Services • 1 astergdem • 18 gtopo30 • 2 children • 19 hierarchy • 3 cities • 20 neighbourhood • 4 countryCode • 21 neighbours • 5 countryInfo • 22 ocean • 6 countrySubdivision • 23 postalCodeCountryInfo • 7 earthquakes • 24 postalCodeLookup • 8 extendedFindNearby • 25 postalCodeSearch • 9 findNearby • 26 rssToGeo • 10 findNearbyPlaceName • 27 search • 11 findNearbyPostalCodes • 28 siblings • 12 findNearbyStreets • 29 srtm3 • 13 findNearByWeather • 30 timezone • 14 findNearbyWikipedia • 31 weather • 15 findNearestAddress • 32 weatherIcao • 16 findNearestIntersection • 33 wikipediaBoundingBox • 17 get • 34 wikipediaSearchINPUT 2012 13
  • 14. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini 5 – Gazetteers Examples • Byzantium, Constantinople, Istanbul • Gazetteer = dictionary of placenames • Roma of Romulus and of today • What to store: • Cagliari, city or province – Names with variants along time • Etc – Names in different languages – Geometry (varying) – Feature type Many-to-many – Neighbors Placenames Places – Rivers: confluence Geonaming Generic tables • From the coordinates of a place, assigning a name to Names (idn, text) this place Geographic – line Category (idc, category-type) Ontology – area Geometry (idn, idc, date, not-connected-polygon) • Problems of linguistics – multilingual problem Other-names (idn1, idn2, type, language) • What name? – Name in the official language of the country – Name in the language of the user – Name in the language of the systemINPUT 2012 14
  • 15. Geographic Ontologies and Spatial Relationships Prof. Robert Laurini For municipalities For countries Belongs-to (idn, date, country-name) Population (idn, date, poulation) Population (idn, date, poulation) Neighbours (idn, (neighbouring-countries)*) Neighbours (idn, (neighbouring-municipalities)*) For rivers Confluence (idn, main-confluent-river-idn) 6 – Conclusions • Ontologies as tools • For interoperability • For clarifying vocabulary • Difficulties to properly define geographic features • Semantically • Geometrically • Topologically • Importance of spatial relationships • Possibly of using new spatial relations • Links with gazetteers • Geographic ontologies (with spatial relationships)INPUT 2012 15

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