AAG 2014 Talk on Ontology Views, Reusue, Alignment
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AAG 2014 Talk on Ontology Views, Reusue, Alignment

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AAG 2014 Talk on Ontology Views, Reusue, Alignment AAG 2014 Talk on Ontology Views, Reusue, Alignment Presentation Transcript

  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS SEMANTIC SHORTCUTS AND VIEWS: BRIDGING THE GAP BETWEEN ONTOLOGIES AND LINKED DATA Krzysztof Janowicz, Pascal Hitzler, and Adila Krisnadhi STKO Lab, University of California, Santa Barbara, USA DaSe Lab, Wright State University, USA AAG Meeting 2014 SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS LINKED DATA MOTIVATION LINKING DATA AS NEXT-GENERATION INFRASTRUCTURE Data Silos Web services Databases Web pages hinder ad-hoc combination enforce data models limit re-usability SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS LINKED DATA MOTIVATION FROM LINKED DOCUMENTS TO LINKED DATA Use Uniform Resource Identifiers (URI) to identify entities, link them to other entities, encode information about these entities using the machine-understandable RDF, and make them available on the Web. SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS LINKED DATA MOTIVATION BERNERS-LEE’S LINKED DATA PRINCIPLES AND STARS Four Rules for Linked Data Use URIs as names for things Use HTTP URIs so that people can look up those names. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL) Include links to other URIs. so that they can discover more things. Is your Linked Open Data 5 Star? Available on the web (whatever format) but with an open licence, to be Open Data Available as machine-readable structured data (e.g. excel instead of image scan of a table) as (2) plus non-proprietary format (e.g. CSV instead of excel) All the above plus, Use open standards from W3C (RDF and SPARQL) to identify things, so that people can point at your stuff All the above, plus: Link your data to other people’s data to provide context See http://www.w3.org/DesignIssues/LinkedData.html SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS EXPLORING AND QUERYING LINKED DATA EXPLORING LINKED DATA ABOUT PLEACES, PEOPLE, EVENTS Follow-your-nose: Explore information using Linked Data (DBpedia). SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS EXPLORING AND QUERYING LINKED DATA HOW TO QUERY LINKED DATA (OVER MULTIPLE SOURCES)? Integration by searching equivalent classes or/and same features in data sets. This requires ontologies/vocabularies, their alignment, and/or ontology reuse. SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY STAR RATING ONTOLOGIES TO MAKE YOUR DATA MORE USABLE Five Stars of Linked Data Vocabulary Use Linked Data without any vocabulary. There is dereferencable human-readable information about the used vocabulary. The information is available as machine-readable explicit axiomatization of the vocabulary. The vocabulary is linked to other vocabularies Metadata about the vocabulary is available (in a dereferencable and machine-readable form). The vocabulary is linked to by other vocabularies. See http://semantic-web-journal.net/content/ five-stars-linked-data-vocabulary-use SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY REUSE VOCABULARY/ONTOLOGY REUSE A typical statement: ’Reuse external vocabulary whenever possible.’ <http://dbpedia.org/resource/Copernicus_(lunar_crater)> ... geo:lat "9.7"^^xsd:decimal; geo:long "20.0"^^xsd:decimal; ... a dbpedia-owl:Crater, ... ns5:Place, ... Concerns: Most ontologies are under-specific, how are they maintained, versioning /evolution strategies are unclear, contact persons, are they community-driven, legal issues, proper documentation,...? SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY REUSE REUSE DIFFICULTIES EXAMPLE The Fluidops interface renders the DBpedia RDF data from the Copernicus crater and places it on the Surface of the Earth instead of realizing that the given coordinates are selenographic coordinates. SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT Alternative statement: ’Align your vocabulary to other vocabulary whenever possible.’ dbpedia − owl : Crater ADL: Crater (1) dbpedia − owl : Person ≡ FOAF : Person (?) (2) Concerns: Most ontologies are under-specific, requires reasoning, simple alignments may not be sufficient (despite improving tool support),...? SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES a:flowsInto a:IsConnected (1) a:IrrigationCanal a:Canal (2) ∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3) a:Waterbody a:Land ⊥ (4) a:AgriculturalField a:Land (5) b:flowsInto b:IsConnected (6) b:Canal (≥2 b:IsConnected.b:Waterbody) (7) b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody) (=1 b:flowsInto.b:AgriculturalField) (8) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES a:flowsInto a:IsConnected (1) a:IrrigationCanal a:Canal (2) ∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3) a:Waterbody a:Land ⊥ (4) a:AgriculturalField a:Land (5) b:flowsInto b:IsConnected (6) b:Canal (≥2 b:IsConnected.b:Waterbody) (7) b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody) (=1 b:flowsInto.b:AgriculturalField) (8) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES a:flowsInto a:IsConnected (1) a:IrrigationCanal a:Canal (2) ∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3) a:Waterbody a:Land ⊥ (4) a:AgriculturalField a:Land (5) b:flowsInto b:IsConnected (6) b:Canal (≥2 b:IsConnected.b:Waterbody) (7) b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody) (=1 b:flowsInto.b:AgriculturalField) (8) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES a:flowsInto a:IsConnected (1) a:IrrigationCanal a:Canal (2) ∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3) a:Waterbody a:Land ⊥ (4) a:AgriculturalField a:Land (5) b:flowsInto b:IsConnected (6) b:Canal (≥2 b:IsConnected.b:Waterbody) (7) b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody) (=1 b:flowsInto.b:AgriculturalField) (8) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS VOCABULARY ALIGNMENT VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES a:flowsInto a:IsConnected (1) a:IrrigationCanal a:Canal (2) ∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3) a:Waterbody a:Land ⊥ (4) a:AgriculturalField a:Land (5) b:flowsInto b:IsConnected (6) b:Canal (≥2 b:IsConnected.b:Waterbody) (7) b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody) (=1 b:flowsInto.b:AgriculturalField) (8) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS WHAT/HOW TO MODEL? FRAGMENT OF A MAP LEGEND ONTOLOGY DESIGN PATTERN Ontological commitments Should Geographic Feature Types be classes or instances? Do we want to explicitly define the depictedBy relation Is stating that a Legend consists of LegendItems redundant? . . . SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS INSTANCES VS. CLASSES MODELING DIFFERENCES: INSTANCES VS. CLASSES As illustrated before alignments and mappings can be difficult However, often, even major modeling differences can be aligned/mapped Instances vs. classes Florence rdf : type City (1) Florence xyz : hasType ”City”@en (2) Mapping between those cases Classname ∃hasType.{classname} (3) ∃hasType.{classname} Classname (4) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS ROLE CHAINS FRAGMENT OF THE MAP LEGEND ONTOLOGY NC = {LegendItem, Symbol, Label, FeatureType} (1) NR = {consistsOf, isLabelFor, isLabelOf, depictedBy} (2) ¬∃N. (3) LegendItem ∃consistsOf.Symbol ∃consistsOf.LegendItem (4) Label ∃SymbolizedBy.Symbol ∀SymbolizedBy.Symbol (5) ≤ 1isLabelFor. (6) ≤ 1isLabelOf. (7) ≤ 1SymbolizedBy. (8) Label ∃isLabelFor.FeatureType (9) Label Symbol ⊥ (also for Symbol, Label, FeatureType, LegendItem) (10) isLabelOf− ◦ isLabelFor depictedBy− (11) ¬∃consistsOf− Legend (12) . . . (13) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI
  • LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS ANOTHER SIMPLE VIEW EXAMPLE SIMPLE VIEW FOR THE AGENT ONTOLOGY PATTERN STUB Guarded domain and range restrictions of performsAgentRole ∃performsAgentRole.AgentRole Agent (1) Agent ∀performsAgentRole.AgentRole (2) Pairwise-disjointness axiom Agent AgentRole ⊥ (3) This axiom provides the role isPerformedBy as a view for the pattern. performsAgentRole− isPerformedBy (4) SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI