20130905_feng_chia_gis_center_geospatial_ontology

Geo-Ontology and -Semantics: From Theoretics to Practices

Institute of Information Science, Academia Sinica

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente

Dongpo Deng

dongpo.deng@gmail.com

Tuesday, September 10, 2013

What is ‘O’ntology?

• The term originated from a philosophical discipline

• A branch of philosophy that deals with the nature and the organization of reality

• It was defined by Aristotle in Metaphysics, IV, 1

• It tries to answer the questions:

• What is being?

• What are the features common to all beings?

• How should things be classified?

2Tuesday, September 10, 2013

What is ‘o’ntology?

• a specification of a conceptualization (Gruber, T. 1993)

• a formal specification of a shared conceptualization (Borst et al., 1997)

• is a hierarchically structured set of terms for describing a domain that can be used as a skeletal foundation for knowledge base (Swartout et al., 1996)

• the method to extract a catalogue of things or entities (C) that exist in a domain (D) from the perspective of a person who use a certain language (L) to describe it (Sowa, 2000)

What is ‘o’ntology?

• From AI perspective (Agarwal, 2005)

• “conceptualization” is explained as an abstract model of some phenomenon in the world by having identified the relevant concepts of that phenomenon.

• “explicit” means that type of concepts used and the constraints on their use are explicitly defined

• “formal” refers to the fact that the ontology should be machine-readable

• “shared” refers to notion that on ontology captures consensual knowledge

An example of ontology description

• Example Vocabulary and meaning (“definitions”)

• A ‘Carnivore’ is a concept whose members are exactly those animals who eat only meat

• A ‘Bear’ is a concept whose members are a kind of ‘Carnivore’

• A ‘Cub’ is a concept whose members are exactly those ‘Bear’ whose age is less than one year

• A Panda is a individual of a ‘Bear’

An example of ontology description

• Background knowledge/constraints on the domain (“general axioms”)

• No individuals can be both a Herbivore and a ‘Carnivore’

• Each ‘Bear’ has a period of ‘Cub’

• The age of adult ‘Bears’ is at least 1 year old

The meaning triangle

Syntax-Semantics-Pragmatics

• Syntax (語法) deals with the study of relationships between symbols

• Semantics (語意) analyzes the relationships between symbols and things in the real world they denote (referent)

• Pragmatics (語用) goes beyond syntax and semantics, and researches how symbols are used for particular purposes. Thus, is analyzes relationships between symbols and specific agents

Ontologies for communication

Adapted by Maedche, 2001

Ontology in Computer Science

• An ontology refers to an engineering artifact consisting of:

• A vocabulary used to describe (a particular view of) some domain

• An explicit specification of the intended meaning of the vocabulary

• almost always includes how concepts should be classified

• Constraints capturing additional knowledge about the domain

• Ideally, an ontology should:

• Capture a shared understanding of a domain of interest

• Provide a formal and machine manipulable model of the domain

Why develop ontology?

• To share common understanding of the structure of information among people or software agents

• To enable reuse of domain knowledge

• To make domain assumptions explicit

• To separate domain knowledge from the operational knowledge

• To analyze domain knowledge

Ontology spectrum

Logical Theory

Conceptual Model

Thesaurus

Taxonomy

is Disjoint Subclass of with Transitivity property

is Subclass of

has Narrower meaning then

is Sub-Classification of

Model LogicFirst Order Logic

Description LogicDAML_OIL, OWL

RDF/SXTM

Extended ER

ERDB Schemas, XML Schema

Relational Model, XML

strong semantics

weak semantics

Semantic Interoperability

Structure Interoperability

Semantic Interoperability

Syntactic Interoperability

物種分類名錄 (taibif.tw)

OpenStreetMap Map Features

ADL Gazetteer Feature typesFrom http://www.alexandria.ucsb.edu/~lhill/FeatureTypes/ver070302/00000250.htm

ADL Gazetteer Feature types

From http://wordnetweb.princeton.edu/ 16Tuesday, September 10, 2013

The application ontology inheriting GeoSPARQL

Edited by Protege

Different kinds of ontologies and their relationships

top-level ontologyvery general concepts, e.g. toopology, mereology, geometry, ...

vocabularies related to a generic domain by specializing the top-level ontologies, e.g. GeoSPARQL

domain ontology task ontology

application ontology

vocabularies related to a generic task or activity by specializing the top-level ontologies, e.g. Semantic Sensor Network (SSN) ontology

concepts inheriting domain or task ontologies for supporting in certain activities, e.g. we use SSN and GeoSPARQL to create an ontology for ecological observation

Courtesy: Pascal Hitzler, GeoSemantics, 2009

Description Logics

Ontology and reasoning

What’s the (Geo) Problem?

• What’s special about Spatial?

• spatial-time-attributes

• What is geospatial interoperability?

• GML? WFS? or more alternatives?

• semantic Web - microformat tagging and (multiple) identity

• Semantic Web - (actionable) relationships and triple identity

• geosemantic - geotagging position

• Geosemantic - spatial(-temporal) theories, relationships, mediations, transformations

28Adapted from J. Lieberman (2007) Geospatial Semantic Web: Is there life after geo:lat and geo:long ?

What’s the (Geo) Problem?

• Feature (type) and Geometry (representation)

• Model dependencies

• Community of discourse

• Scale

• Reference frame / coordinate system

• Perspective

• Geospatial plus other (semantic) dimensions

Two approaches for studying on geo ontologies

• There are two distinct approaches that applied ontology in GIScience.

• The philosophical approaches aim to identify specifications of top-level categories from a formal ontology perspective,

• The domain-specific and task-oriented approaches focus on explicating the actions, terms and relation for particular specification and ranging from natural language to rigorously formal specifications.

How difficult to develop geospatial ontology?

• Geographic objects are typically complex, and they will in every case have parts. (Simons, 1987; Smith and Mark, 1998)

• The geographic domain has specific issues regarding ontology primarily because of its unstructured characteristics

• A standard terminology is not prevalent within the GIScience domain and is dependent on the context of use and the user

• causes confusion in specification of universally accepted entities, concepts, rules, relation, and semantics as the basis of a consensual ontology.

Geographical Entities are Indeterminate and Ambiguous Objects

Philosophically speaking: Where does themountain begin and the valley end?

How can we derive a commonsemantics which can refer accuratelyto these kinds of objects?

B. Smith and D. Mark, 2003. Do Mountains Exist? Towards an Ontology of Landforms. Environment and Planning B, 30(3), 411-42732

Geographical Entities are Indeterminate and Ambiguous Objects

Philosophically speaking: Where does themountain begin and the valley end?

How can we derive a commonsemantics which can refer accuratelyto these kinds of objects?

B. Smith and D. Mark, 2003. Do Mountains Exist? Towards an Ontology of Landforms. Environment and Planning B, 30(3), 411-42732

Geospatial objects: vagueness and ambiguity

• Geographic categorization and classification are scale- and size-dependent,

• regionalization in space and time is human-dependent, and location and structure of boundaries shape many geographical categories.

• The ways that space and time determine relations and property inheritance are not yet clear.

• Human dependence means that geographic categories and nomenclature can have different meanings in different application contexts.

• fiat (tennis court) and bona fide (shoreline or riverbanks)

• open (bay) and closed (lake)

33B. Smith and D. Mark, 2003. Do Mountains Exist? Towards an Ontology of Landforms. Environment and Planning B, 30(3), 411-427

Conceptual model in General Feature Model (GFM)

W3C Basic Geo Vocabulary

35http://www.w3.org/2003/01/geo/Tuesday, September 10, 2013

Map4RDF

http://oeg-dev.dia.fi.upm.es/map4rdf/

Geonames.org

37http://www.geonames.org/maps/google_25.048_121.532.htmlTuesday, September 10, 2013

‘Taipei’ in Geonames

38http://sws.geonames.org/1668341/about.rdf

Geonames ontology

http://lov.okfn.org/dataset/lov/details/vocabulary_gn.html

Ordnance survey Ontologies

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

Spatial Relations in OS ontologies

41http://data.ordnancesurvey.co.uk/ontology/spatialrelations/contains

Spatial Relations in OS ontologies

42http://data.ordnancesurvey.co.uk/ontology/spatialrelations/contains.ttl

GeoSPARQL

• The GeoSPARQL will be a new OGC standard, which provides three main components for encoding geographic information:

• (1) The definitions of vocabularies for representing features, geometries, and their relationships;

• (2) A set of domain-specific, spatial functions for use in SPARQL queries;

• (3) A set of query transformation rules

43Robert Battle, Dave Kolas, 2011. Enabling the Geospatial Semantic Web with Parliament and GeoSPARQL

Components of GeoSPARQL

• Vocabulary for Query Patterns

• Classes

• Spatial Object, Feature, Geometry

• Properties

• Topological relations

• Links between features and geometries

• Datatypes for geometry literals

• ogc:wktLiteral, ogc:gmlLiteral

• Query Functions

• Topological relations, distance, buffer, intersection, …

• Entailment Components

• RDFS entailment

• RIF rules to compute topological relations

44Courtesy from M. Perry (2012)The GeoSPARQL OGC Standard, Terra Cognita.

GeoSPARQL Vocabulary: Basic Classes and Relations

Details of ogc:wktLiteral

Details of ogc:gmlLiteral

Topological Relations between ogc:SpatialObject

RCC8, Egenhofer & Simple Features

Example Data

Why Encode Geometry Data as a Literal?

Why don’t GeoSPARQL support W3C Basic Geo?

• Too simple to meet our requirements

• Can’t use different datums and coordinate systems

• Limited number of geometry types

• W3C Basic Geo data can easily be converted to wktLiteral

GeoSPARQL Query Functions

GeoSPARQL Topological Query Functions

Example Query

GeoSPARQL RDFS Entailment Extension

Simple Features Geometry Types

GeoSPARQL Query Rewrite Extension

Query Rewrite Rules

• Used to compute Feature-Feature spatial relations basedon default geometries

• Specified as a collection of RIF rules

• Example: ogcr:sfEquals

Summary of Conformance Classes

• Parameters

• Serialization

• WKT

• GML

• Relation Family

• Simple Features

• RCC8

• Egenhofer

Determines geometry classes and geometry literal datatype

Determines topology properties and topology functions

Courtesy from M. Perry (2012)The GeoSPARQL OGC Standard, Terra Cognita.Tuesday, September 10, 2013

Why don’t you support W3C Basic Geo?

• Too simple to meet our requirements

• Can’t use different datums and coordinate systems

• Limited number of geometry types

• W3C Basic Geo data can easily be converted to wktLiteral

BBN Parliament

An example query of GeoSPARQL(1)

• Within

SELECT DISTINCT ?POO ?POO_wktWHERE { ?POO a eoe:PointOfObservation; geo:hasGeometry ?POO_geo. ?POO_geo geo:asWKT ?POO_wkt.

FILTER (geof:sfWithin(?POO_wkt, "Polygon((121 22, 121 23, 122 23, 122 22, 121 22))"^^sf:wktLiteral))

Query results (1)

An example query of GeoSPARQ(2)

• buffer and within

SELECT DISTINCT ?p_wkt?POO_wkt ?distanceWHERE {

?POO a eoe:PointOfObservation; geo:hasGeometry ?POO_geo. ?POO_geo geo:asWKT ?POO_wkt. geo:point_238918712815615_439043552803129 geo:asWKT ?p_wkt;

LET (?buff := geof:buffer(?p_wkt, 3000, units:metre)) . FILTER (geof:sfWithin(?POO_wkt, ?buff)) . LET (?distance := geof:distance(?POO_wkt, ?p_wkt, units:metre))}

Query results (2)

20130905_feng_chia_gis_center_geospatial_ontology

generic domain

domain d

separate domain knowledge

reuse of domain knowledge

domain assumptions explicit

domain general axioms

symbols semantics

task ontologies

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