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A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer Paul R. Smart, Alistair Russell, Dave Braines, Yannis Kalfoglou,,

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Presentation on theme: "A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer Paul R. Smart, Alistair Russell, Dave Braines, Yannis Kalfoglou,,"— Presentation transcript:

1 A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer Paul R. Smart, Alistair Russell, Dave Braines, Yannis Kalfoglou,, Jie Bao and Nigel R. Shadbolt Presented by Kristine Monteith CS 652 – Information Extraction and Integration 5/21/09

2 Overview Semantic Query Languages such as SPARQL are important tools for Information Retrieval This paper presents a tool to aid in the process of query formation Visual Query Systems Syntactically valid queries Avoid lexical and syntactic errors Possibility of improved efficiency, understanding, and reduced training requirements

3 vSPARQL Visual Query Language Set of graphic notations that support the visual representation of SPARQL query components Outline Core SPARQL Features Triple Patterns Simple Select Query Graph Patterns Solution Sequence Ordering SPARQL CONSTRUCT Queries Other SPARQL Features

4 Core SPARQL Features

5 Triple Patterns

6 Simple Select Query PREFIX rdf: PREFIX edto: SELECT ?activity ?date WHERE { ?activity rdf:type edto:Activity. ?activity edto:hasDate ?date }

7 Simple Select Query

8 Graph Patterns Each variable has local scope with respect to the graph pattern in which it is contained PREFIX rdf: PREFIX edto: SELECT ?activity WHERE { {?activity rdf:type edto:MilitaryActivity}. {?activity rdf:ytpe edto:BiologicalActivity} }

9 Graph Patterns

10 Other Graph Patterns Optional graph patterns Union graph patterns Allow users to specify alternatives for graph pattern matching

11 Solution Sequence Ordering Specify the order in which query results are returned

12 Filtering PREFIX rdf: PREFIX edto: SELECT ?activity ?activityDate WHERE { ?activity rdf:type edto:Activity ?activity edto:hasDate ?activityDate FILTER (?activity>" T00:00:00Z"^^xsd:dateTime) }

13 Filtering

14 SPARQL CONSTRUCT Queries Define both a set of triples to match against the rdf graph and a template for rdf construction CONSTRUCT { _:a rdf:type edto:TerroristAttack. _:a edto:hasICN ?aaip_ICN. ?x owl:sameAs _:a } WHERE { ?x rdf:type aaip:TerroristIncident ?x aaip:hasICN ?aaip_ICN ?y rdf:type edto:TerroristAttack ?y edto:hasICN ?edto_ICN }

15 SPARQL CONSTRUCT Queries

16 Other SPARQL Features Supported in the NITELIGHT tool Not part of the vSPARQL specification ASK and DESCRIBE query forms DISTINCT, LIMIT and OFFSET solution modifiers

17 NITELIGHT Tool

18 Additional Application Areas Rule Creation Take advantage of multiple knowledge bases Information Integration and Interoperability Ontology alignments between ostensibly disparate ontologies

19 Rule Creation CONSTRUCT { ?z edto:hasSuspectedResponsibilityFor ?x } WHERE { ?x rdf:type edto:TerroristAttack. ?x edto:isPerformedBy ?y. ?y edto:isMemberOf ?z. ?z rdf:type edto:TerroristOrganization }

20 Information Integration and Interoperability PREFIX edto: PREFIX ito: PREFIX rdf: PREFIX rdfs: PREFIX owl: PREFIX xsd: CONSTRUCT { _:t rdf:type edto:TerroristAttack. _:t edto:isSuicideAttack xsd:true. _:d ref:type edto:ExplosiveDevice. _:t edto:uses edto _:d } WHERE { ?x rdf:type ito:TerroristIncident. ?x ito:hasType ito:Bombing. ?x ito:involvesWeapon ito:Explosive. ?x ito:hasVictim ?victim. ?victim ito:isFatality xsd:true. ?victim rdf:type ito:Terrorist. ?x ito:perpetratedBy ?victim }

21 Strengths Helped me understand SPARQL better Enforces correct syntax Seems like an attractive, easy-to-use program

22 Weakness Requires the user to already be familiar with SPARQL Tool not available online Ontology not available online

23 Future Work User evaluation study already planned

24 QUESTIONS?


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