Dave Kolas, BBN TechnologiesTerra Cognita 08

Karlsruhe, Germany 10/26/08

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Supporting Spatial Semantics with SPARQL

Presentation Outline

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Background InformationWhat is SPARQL, anyway?Why does anyone care about spatial semantics?

Related WorkObject-Relational + SpatialXML + SpatialSemantic Web + Spatial

Goals of a Spatial Semantic Query Language What SPARQL can do now What SPARQL can’t do now Implementation Conclusions

What is SPARQL, anyway?

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SPARQL is the SPARQL Protocol and RDF Query LanguageW3C Candidate Recommendation for Semantic Web

queryingRDF – Resource Description Framework

Language for describing data on the webThink XML on steroids

OWL – Web Ontology LanguageLanguage for representing ontologies on the webRicher than RDFBuilds upon RDF as well

Who cares about spatial semantics?

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Combining Semantic Web technologies with spatial helps with several important problemsMultiple references to the same placeMultiple names for the same placeAllows complex class and property

hierarchies and relationships for representing types

Provides a basis for semantic interoperability

Related Work – Object-Relational + Spatial

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Not much work to use an Object-Relational query language for querying spatial OR systemsSQL3 – Geometry objects are defined, as well

as operations that can be performed on themThis does not provide a transport mechanism

for the spatial data!

Related Work – XML + Spatial

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XML has been used with spatial data to provide a data exchange format and languageOpen Geospatial Consortium – GML

Storing data directly in GML is inefficient, difficult to process spatial relationships

Related Work – SemWeb + Spatial

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Relatively new research areaProvides a higher level of data

interoperability with other systems, as formal semantics are defined

Provides more complex relationships than XML can

Goals of a Semantic Query Language

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Maintain the Graph Theoretical Model of Data

Do not specialize SPARQL for spatialSupport appropriate types of spatial

queriesAllow all relevant data to be returned in

one query

Goals – Maintain the Graph

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The fundamental data model of the Semantic Web languages is a conceptual graph

This theoretical model holds from end to end; data is stored as a graph, transferred as a graph, and queried as a graph

Spatial data should not break this paradigm

Goals – No Specialized SPARQL for Spatial

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A goal of RDF, OWL, and SPARQL is to be domain neutralNo matter what the topic of dicsourse is, you should

be able to discuss it in this languageQuery clients can be built to create SPARQL

queries on the flyWhile some clients will obviously know they are

querying for spatial data, others may not; these clients should be supported by spatial SPARQL too

Goals – Types of Queries

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Queries about the spatial properties of an individual

Queries that relate individuals to a known location (point and range queries)

Queries that relate individuals to one another (spatial join, nearest neighbor queries)

Queries that spatially aggregate individuals

Goals – All Relevant Data in One Query

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One query can be posed for one logical questionCombinations of the query types above must

be supportedSpatial data must be retrievable without

knowing the geometry types a priori

Why not just use functions?

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SPARQL already has a mechanism for function calls within a query

Why not just use that?It breaks the graph model (Goal 1); the

relationships then cannot be serialized in the language

It specializes the language (Goal 2); clients have to know they are querying for spatial data

What can SPARQL do now?

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SPARQL already has the capacity to do basic spatial queriesWe can represent geometries ontologicallyWe can represent spatial relationships

ontologically tooDESCRIBE can be used to get spatial

information without knowing geometries

Current SPARQL – Representing Geometries

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We can use an ontology of geometries so that geometry definitions can be put directly in the query!

Base this on GML geometry types, using W3C Geo language

[] a restaurant:PizzaParlor;restaurant:name “Jimmy’s Pizza”;georss:where [

a gml:Point;gml:pos “38 -77”

].

Current SPARQL – Representing Relationships

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We can use an ontology of topological relationships so that they too can be put in the query!

Base this on some formalism (here, RCC8*):rcc:disconnected

a owl:ObjectProperty ;a owl:SymmetricProperty .

rcc:parta owl:ObjectProperty ;rdfs:subPropertyOf rcc:connected .

* We use the terms from RCC8 without necessarily using the reasoning axioms

Current SPARQL – Using Describe

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DESCRIBE is a query mechanism whereby a querier can request unspecified data about an object; what is returned is up to the knowledge service

A spatial knowledge base can use this functionality to return geometry infromation, whether it is in the form of a point, line, polygon, etc.

DESCRIBE ?geo WHERE { <http://data/#JimmysPizza> georss:where ?geo }

What does SPARQL need?

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There are some things that are awkward or just cannot be done with the current specification.Range queries are awkwardGetting back geometry types is challenging

Count queries are impossible

Enhancements – Query Premise

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Concept is that querier declares statements to be true to be considered with the query

Query premises have been used in several other languagesKQMLDAML-QL

Query premises allow us to cleanly express range queries

Query Premise – Example

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SELECT ?xPREMISE {

?b a gml:Buffer;gml:radius “1”;gml:bufferGeometry [

a gml:Point;gml:pos “38 -77”

].}WHERE {

?x a gas:GasStation;georss:where ?y.

?y rcc:part ?b .}

Enhancements – Embedded Describe

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The problem is that it is complex to ask for things within a spatial region and get their geometries in the same queryCan be done, but needs to use series of

OPTIONAL clauses (UGLY)If we could use the DESCRIBE functionality

within other types of queries, we could do it!

Embedded Describe - Example

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SELECT ?landmark ?geometry DESCRIBE(?geometry)WHERE {

?landmark a lm:LandMark;georss:where ?geometry.

?geometry a ?geometryType;rcc:part ?x.

va-counties:Arlington georss:where ?x.}

Enhancements – Counting

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Maybe surprisingly, SPARQL cannot count!This is due to the lack of a unique names

assumptionBut we need to count, and sometimes we

know we can countWhen two things returned *must* be unique!

Potential solution: count references instead of individuals

Counting – Example

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SELECT COUNT(?x)PREMISE {

?b a gml:Buffer;gml:radius “1”;gml:bufferGeometry

<http://data/#JimmysLocation>}WHERE {

?x a restaurant:PizzaParlor;georss:where [

rcc:part ?b] .

}

Implementation

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BBN has developed a prototype knowledgebase for combining Semantic Web data with spatial data, temporal data, and indexing of both

This KB makes use of the Spatial SPARQL suggestions outlined here

There are also extensions to the Lehigh University Benchmark based on this work, for testing scalability of spatial Semantic Web knowledge bases

Conclusions

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SPARQL can already be used for basic querying of spatial semantic systems!

Several enhancements can be added to SPARQL that support spatial data while also being generally useful:Query PremisesEmbedded DESCRIBECounting

Questions?

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