III-SGER: Spatio-Temporal-Thematic Queries of Semantic Web Data: a Study of Expressivity and Efficiency

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III-SGER Spatio-Temporal-Thematic Queries of
Semantic Web Data a Study of Expressivity and
Efficiency

• Query Rewriting Framework for Spatial Data
• Funded by NSF AwardIIS-0842129 "III-SGER
  Spatio-Temporal-Thematic Queries of Semantic Web
  Data a Study of Expressivity and Efficiency
• http//knoesis.org/research/semweb/projects/stt/

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Increased retrieval of spatial information
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But spatial querying still needs improvement
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User expected to pose proper query
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Whats the problem

• There is a need to analyze spatial information
  and queries beyond lexical and syntactic level.
• Datasets on which queries are executed might have
  information, but not in the form expressed by
  query constraints.
• Question Find schools in NJ,
• Answer Sorry! Information is available for
  schools in counties.
• Semantic relationship such as part of between
  query terms may or may not be understood properly
  
• Find Schools in Greene County

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What needs to be done?

• Information should be retrieved even if mismatch
  exists between granularity of query constraints
  and knowledge base
• User should not be burdened with knowing how the
  ontology is structured
• Words which express semantic relations between
  entities should be included in the query mechanism

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Proposed approach

• Ease writing of expressive queries to implicitly
  exploit relations between entities.
• Propose operators which hides the complexity of
  user knowing and expressing named relations
  between entities in query constraints
• Behind the scene utilization and identification
  of semantic relations such as partonomy in
  answering queries.
• Define transformation rules for operators to use
  work by Winstons taxonomy of part-whole
  relations.
• Rule based approach allows applicability in
  different domains such as life science with
  appropriate modifications.

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Geonames schema modeling schools
County
School
Contains feature
Contains feature
Ohio
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SPARQL query for schema

• PREFIX rdf http//www.w3.org/1999/02/22-rdf-syn
  tax-ns
• PREFIX geo lthttp//www.geonames.org/ontologygt
• SELECT ?school
• WHERE
• ?state geofeatureClass geoA
• ?schools geofeatureClass geoS.
• ?state geoname "Ohio
• ?state geochildrenFeatures ?county .
• ?county geochildrenFeatures ?schools .

Users must know exactly how schools, counties,
and states are modeled, which is not trivial
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Our approach
SELECT ?school WHERE ?state
geofeatureClass geoA ?schools
geofeatureClass geoS. ?state
geoname "Ohio ?schools
in ?state .
Identify triple constraints to be replaced
Query Re-Writer
Triple constraints and variables rewritten using
transformation rules
SELECT ?school WHERE ?state
geofeatureClass geoA ?schools
geofeatureClass geoS. ?state
geoname "Ohio ?state
geochildrenFeatures ?county . ?county
geochildrenFeatures ?schools .
Rewritten constraints and variables plugged into
query envelope
Approach allows writing queries more naturally
and independent of the underlying knowledge base
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Architecture

• SELECT ?school
• WHERE ?school in Ohio.

User submits SPARQL Query

• Triple Constraints
• Query Variables

Mapping of ontology properties to Winstons
categories
Query Rewriting Engine
Domain Specific Transformation Rules


Meta rules for Winstons Categories

• Altered Triple Constraints
• Altered Query Variables

Rewritten Query according to the data structure
SELECT ?school WHERE ?state geoname
"Ohio ?state
geochildrenFeatures ?county . ?county
geochildrenFeatures ?schools .
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Evaluation plan

• Utilize publicly available datasets Geonames and
  Sensor Ontology for identifying partonomical
  relationships
• Identify meaningful queries and their rewrite
• Expose infrastructure as a web resource for
  utilization on other datasets.

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Publication/Community Contribution

• A Framework to Support Spatial, Temporal and
  Thematic Analytics over Semantic Web Data
  ,Matthew Perry, Amit Sheth and Prateek Jain
  (Under review in Transaction of Database Systems)
• Submission for International Semantic Web
  Conference in June 2009.
• Sensor Ontology, linked with Geonames Dataset to
  be made part of Linked Data Cloud
  (http//linkeddata.org/data-sets).

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Thanks