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Geospatial semantics research at Ordnance Survey. Cathy Dolbear, Paula Engelbrecht, John Goodwin, Glen Hart and Ian Holt . Ordnance Survey GeoSemantics research. Motivation – why is a mapping agency interested in semantics? Ontology authoring RDF data Semantic data integration

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geospatial semantics research at ordnance survey

Geospatial semantics research at Ordnance Survey

Cathy Dolbear, Paula Engelbrecht, John Goodwin,

Glen Hart and Ian Holt

ordnance survey geosemantics research
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

ordnance survey who we are
Ordnance Survey – who we are
  • National Mapping Agency of Great Britain
  • One of the largest geospatial databases
  • 2000+ concepts
  • Customers use GIS systems & spatially enabled databases to process data
motivation

Data Mining

Customer benefits

Data & Product Repurposing

Ontological

representation

Semi-automated data integration

Semantic Web Enablement

Quality Control

Better Classification

Benefits to OS

Time

Motivation
ordnance survey geosemantics research5
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

slide6

Topographic domain ontology

  • Describes what we as an organisation know
  • Beyond a simple taxonomic classification
  • Provides a framework for specifying product content:
    • What our customers need
    • What can be captured and stored.
slide7

Topographic domain ontology

  • Developed Hydrology, Administrative Geography, Buildings and Places
  • ~ 600 concepts, ALCOQ expressivity (OWL 1.1)

“Every Allotment is owned by exactly 1 Local Authority”

  • Working on Addresses, Settlements and Land forms
  • Plus supporting modules: Mereology, Spatial Relations, Network topology.

http://www.ordnancesurvey.co.uk/ontology

slide8

Our approach to building ontologies

Conceptual Aspect

Computational Aspect

Conceptual

Ontology

Computational Ontology

Knowledge represented in a form manipulable by computers

Knowledge represented in a form understandable to people

<owl:ObjectProperty rdf:ID="directPartOf">

<rdf:type rdf:resource="&owl;FunctionalProperty"/>

</owl:ObjectProperty>

<owl:Class rdf:ID="River"/>

<owl:Class rdf:ID="RiverStretch">

<rdfs:subClassOf>

<owl:Restriction>

<owl:onProperty rdf:resource="#directPartOf"/>

<owl:someValuesFrom rdf:resource="#River"/>

</owl:Restriction>

</rdfs:subClassOf>

</owl:Class>

EveryRiver Stretchis part ofa River

River_Stretch⊏ direct_part_of∃River

slide9

Rabbit: Controlled natural language

  • Structured English, compilable to OWL
  • Intelligible to domain expert
    • Can author conceptual ontology
    • Guides good modelling practice
    • Other domain experts are able to validate the work
    • Acts as documentation for the OWL
  • Part of OWL 1.1 task force to develop a controlled natural language syntax
ordnance survey geosemantics research11
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

semantically enabling data an rdf gazetteer
Semantically enabling data - an RDF Gazetteer

Experiment to semantically describe gazetteers

  • OWL ontology to describe the concepts
  • RDF version to represent the data
  • Currently includes administrative regions
  • Adding cities and other settlements, addresses etc
  • Adding more topographic relationships
  • Spatial boundary information embedded in the RDF using GML
problems with pure rdf
Problems with pure RDF
  • Oracle RDF
    • Limited expressivity
    • How much do we really need?
  • Benefits likely to be using RDF as a data supply format rather than storage model
  • RDF likely to degrade performance: we have > 10 billion triples
  • Spatial component must be executed after RDF filtering
    • Would it be more efficient to perform the spatial query first to minimise the size of the RDF graph?
ordnance survey geosemantics research14
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

semantic data integration

OS Buildings and Places ontology

VO Data ontology

OS Data ontology

Semantic data integration

Query: Find all addresses with a taxable value over £500,000 in Southampton

VO Domain ontology

Merge

OS Address Layer 2

Valuation Office Data

slide16

Alignment: currently at data level

Ordnance Survey

Valuation Office

Has Form Education Services

School and Premises

School

Local Authority School

Junior School

High School

Infant School

Public & Independent School

Private Primary School

Private Secondary School

merging ontologies
Merging ontologies
  • Evaluation
    • Assess which concepts from one ontology should be included in another
  • Modularisation
    • Isolate these concepts from the rest of the donor ontology
  • Integration
    • Map and/or adapt the donor module for integration into the receiving ontology.
merging ontologies some thoughts
Merging ontologies – some thoughts
  • Ontologies are never perfect: not a complete descriptions of any domain
  • Automatic tools [PROMPT, FOAM, SWOOP modularisation etc] can help with navigation / suggestion but
    • Domain experts needed to add in their knowledge/ judgement
    • Some concepts are more important than others
    • Need to restrict the referencing of a concept
  • Early stages of research
ordnance survey geosemantics research19
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

semantic data integration20

OS Buildings and Places ontology

VO Data ontology

OS Data ontology

Semantic data integration

Query: Find all addresses with a taxable value over £500,000 in Southampton

VO Domain ontology

Merge

OS Address Layer 2

Valuation Office Data

slide21

Linking ontologies to databases

  • D2RQ - maps SPARQL queries to SQL, creating “virtual” RDF [Bizer et al, 2006]
  • No need to convert data to RDF explicitly
  • Modifying the API to:
    • Use OWL-based description of mapping (data ontology)
    • Map queries via spatial relations to SQL spatial operators
    • Use views to reduce number of triples and improve efficiency
simplified example building
Simplified Example: “Building”

Building

Domain Ontology

Has Footprint

Is a

House

SELECT FID, Theme, Polygon

FROM TopographicArea

WHERE Theme = ‘Buildings’;

Footprint

Is a

Topographic AreaTable

and hasColumn (Theme

and

(has FieldValue

has

“Buildings”))

Theme

DB

Building

Is equivalent to

Has Column

Is a

Topographic

Area

Table

Polygon

Data Ontology

Has Column

slide23

More complex example - Islands

“Every Island is a kind of Land that is surrounded by Water”

ordnance survey geosemantics research24
Ordnance Survey GeoSemantics research
  • Motivation – why is a mapping agency interested in semantics?
  • Ontology authoring
  • RDF data
  • Semantic data integration
    • Merging ontologies
    • Linking ontologies to relational databases
    • Spatial and semantic reasoning

and querying

spatial and semantic reasoning
Spatial and semantic reasoning
  • Several options in the literature:
    • Convert OWL reasoner to RCC8 reasoner
    •  Connections to link the two logics
    • Concrete domains
  • Trying something simpler – data ontology spatial relationships mapped to Oracle SDO_RELATE operators

spatially_inside maps to SDO_INSIDE(<geometry1>,<geometry2>) = ‘TRUE’

finding islands

Database.owl

(Table, Column,

Primary Key)

SpatialRelations.owl

(Inside, Contains,

Touches)

Finding Islands

SELECT ta1.FID, ta1.Theme, ta1.Polygon

FROM TopographicArea ta1, TopographicArea ta2

WHERE ta1.Theme = ‘Land' AND

ta2.Theme = 'Water'

AND SDO_INSIDE(ta1.Polygon, ta2.Polygon) = 'TRUE';

finding islands next steps

Database.owl

Spatial

Relations.owl

SELECT ta1.FID, ta1.Theme, ta1.Polygon

FROM TopographicArea ta1, TopographicArea ta2

WHERE ta1.Theme = ‘Land' AND

ta2.Theme = 'Water'

AND SDO_INSIDE(ta1.Polygon, ta2.Polygon) = 'TRUE';

OS spatial

database

Finding Islands – next steps

Find me a detached house on an island

DL

Reasoner

RDF

spatial and semantic querying
Spatial and semantic querying
  • Graph matching using SPARQL
    • Can do SPARQL custom functions for spatial queries
    • Or split the query into spatial (SQL) and semantic (SPARQL) parts?
  • Waiting for conjunctive query language (SPARQL DL)
  • Should knowledge be included in the query or the ontology?
  • How do we make it easier for domain experts to make queries?
conclusions
Conclusions
  • “Semantics” research often doesn’t consider the semantics!
  • Domain experts need to be at the centre of the process
  • Technology transfer is difficult:
    • Benefits of semantics in products and applications must be clarified
thank you for your attention
Thank you for your attention

http://www.ordnancesurvey.co.uk/ontology