SOWL:Spatiotemporal Representation, Reasoning

and Querying over the Semantic Web

Sotiris Batsakis, Euripides G.M. Petrakis

Technical University Of CreteIntelligent Systems Laboratory

SOWL◦ Spatiotemporal OWL ontology◦ Representation of quantitative and qualitative

information◦ Spatiotemporal reasoning using SWRL rules ◦ Spatiotemporal query language

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Introduction

Temporal relations involve at least three arguments◦ OWL represents binary relations◦ Evolution of information in time ?

Existing approaches: Temporal RDF, Named Graphs, Reification, Versioning, 4D fluents◦ No qualitative information◦ No mixing of spatial and temporal information◦ Limited OWL reasoning support

Querying of spatiotemporal information is also a problem

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State-of-the- art

4D Fluents [Welty & Fikes 2006] Classes TimeSlice, TimeInterval are introduced

Dynamic classes become instances of TimeSlice

Temporal properties of dynamic classes become instances of TimeInterval

A time slice object is created each time a (fluent) property changes

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4-D fluents example

Advantages◦Changes affect only related objects, not

the entire ontology◦Reasoning mechanisms and semantics of

OWL fully supported◦OWL 2.0 compatible

Disadvantages ◦Data redundancy

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4-D fluents: Comments

SOWL shows how temporal and spatial information is unified and represented within the same ontology

Information: Points, intervals, list of points..

Quantitative and Qualitative information Qualitative Allen Relations (e.g., Before,

After) are introduced ◦ Qualitative relations connect temporal intervals◦ Intervals with unknown endpoints

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Extending 4-D fluents

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Allen Temporal Relations

Reasoning Infer new relations from existing ones

◦ SOUTH(x,y) AND SOUTH(y,z) SOUTH(x,z) Problem 1: Reasoning over a mix of qualitative and

quantitative information is a problem◦ Extract qualitative relations from quantitative ones ◦ Reasoning over qualitative information

Problem 2: Assertions may be inconsistent or new assertions may take exponential time to compute

Solution: Restrict to tractable sets decided by polynomial algorithms such as Path Consistency [Renz & Nebel 2007]

Based on Path Consistency, composing and intersecting relations until:◦ A fixed point is reached (no additional inferences

can be made)◦ An empty relation is yielded implying

inconsistent assertions Path Consistency is tractable, sound and

complete for specific sets of temporal relations

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Temporal Reasoning(1/2)

Compositions and intersections of relations are defined and implemented in SWRL:

During(x,y) AND Meets(y,z) Before(x,z) (Before(x,y) OR Meets(x,y)) AND

Meets(x,y)Meets(x,y)

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Temporal Reasoning (2/2)

Spatial Representation Different forms of spatial information are

supported in SOWL◦ Topologic Relations (inside/outside,

connected/disconnected …)◦ Directional (North, South, East, SouthEast …)

Computed from raw data (images, points, shape contours), spatial projections

Topologic Relations

Directional Relations

Spatial Reasoning Apply path consistency on topologic and

directional relations Restrict to tractable sets of spatial relations

[Renz, Nebel 2007] Polynomial with respect to the number of

spatial entities Example SWRL rules:

◦ NTPP(x,y) AND DC(y,z)DC(x,z)◦ SOUTH(x,y) AND SOUTH(y,z) SOUTH(x,z)

SOWL Query Language SQL-like query language supporting

spatiotemporal operators SELECT … AS… FROM … AS … WHERE …LIKE “string” AND… Additional operators

◦ Temporal (AT, Allen), Spatial Operators (Topologic, Directional)

◦ General purpose operators (MINUS,UNION, UNION ALL, INTERSECTS, ALL, ANY, IN)

Temporal Operators AT specifies time instants or intervals for

which fluent properties hold true TIME: Return interval that fluent holds. Allen’s operators: BEFORE, AFTER, MEETS,

METBY, OVERLAPS, OVERLAPPEDBY, DURING, CONTAINS, STARTS, STARTEDBY, ENDS, ENDEDBY and EQUALS

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SELECT Company.companyName FROM Company, Employee WHERE Company.hasEmployee:Employee AT(3,5) AND Employee.employeeName LIKE “x”

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AT Temporal Operator Example

SELECT Company.companyName FROM Company, Employee AS E1,

Employee AS E2 WHERE Company.hasEmployee:E1 BEFORE

Company.hasEmployee:E2 AND E1.employeeName like “x” AND

E1.employeeName LIKE “y”

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Allen Operator Example

Spatial Operators Apply on locations Topologic (e.g., INTO), Directional (e.g., NORTH-OF) and Range (e.g., IN RANGE > “distance’’)

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SELECT Company.companyName FROM Company WHERE Company NORTH-OF “Attica” AT(3) AND Company.companyName LIKE “x”

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Spatial Query Example

SOWL is a mechanism for representing and querying spatiotemporal information in OWL ontologies

Offers temporal and spatial reasoning support over qualitative relations

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Conclusion

SPARQL based query language Optimizations for large scale applications Alignment with existing vocabularies (OWL-

Time, GeoRSS)

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Future Work

Thank youQuestions ?