Ontologies for Reasoning, Action and Interaction in Space John Bateman University of Bremen SOCop...

Ontologies for Reasoning, Action and Interaction in Space

John BatemanUniversity of Bremen

SOCop Meeting: 12th November 2009

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Overview of talk

● Context of the work ● within our Collaborative Research Center: “Spatial

Cognition”...● ... and my work within that

● Representations of Space● Results and Conclusions● Proposals for Ontology Best Practice● Next targets and challenges

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● Areas: spatial reasoning, representation, action and communication

● Organisation:● Collaborative Research Center● Bremen / Freiburg● funded by: Deutsche Forschungsgemeinschaft

(DFG: German Research Council )● 3 Phases

○ 1st phase: 2003-2006: 12 projects○ 2nd phase: 2007-2010: 18 projects○ 3rd phase: being proposed

Spatial Cognition: SFB/TR8

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Spatial Assistance

● Mobility support

● Spatially-embedded tasks

● Descriptions of spatial situations● verbally● visually

● Exploration

● Navigation

● Dialogic interaction

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Qualitative Information “In front to the right is

the seminar room”

Quantitative information

Symbolic information[door_1 recognized]

Bremen Autonomous Wheelchair: Rolland

: Rolland

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Test-Bed: BAALLBremen Ambient Assisted Living Lab

● Environment● heating, lighting● safety● soft / hard /

middleware interaction

● Appliances● refrigerator● cooker● cupboards,● drawers● washing

machine,● microwave● TV, PC, …● mobile phone● doors

● Autonomous assistance devices● wheelchairs● walkers

● Health monitoring● Architecture

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Sensor data: ‘free-space’ maps

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Voronoi map From Voronoi map From SFB/TR8 project: SFB/TR8 project: A1-[RoboMap]A1-[RoboMap]

Voronoi calculation on a scanned floor plan

“where are you?”

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Unnatural / unhelpful descriptions

● 25.4 m NW of you

● GPS: “34° 15´ N / 3° 27´ E”

● “3.45m away from edge 98 (with 80% certainty)”

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Natural route descriptions

● Leave the room and turn right into the corridor.

● Go to the window and then turn left.

● Follow the corridor and I’m in the last room on the left.

Many problems of semantic interpretation involved here...

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Context-specific way-finding assistance

Kai

-Flo

rian

Ric

hter

, T

hom

as B

arko

wks

y et

al.

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"At the next junction go straight on, and then, turn right before a map. Keep following the river until a Telekom sign, and then, turn left after the Telekom sign. Go towards the Universum until a bus stop, and then, turn right after the bus stop."

schematization

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Sources of relevant knowledge

Location-based services

Geographic Information Systems

Commonsense objects and activities

Spatial awareness and understanding

Natural language capabilities

Robot perception

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Basic problem

● Getting these diverse areas of expertise to talk to each other is a serious issue● different communities● different interests● different representations

● The kinds of knowledge maintained by such systems are very different

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Consequences

● Component specifications are developed again and again (and again and again)

● Each community of practice defines them slightly differently (or not, it is difficult to tell)

● Each standardisation group has little time to look at parallel activities and must reflect the demands of its own community before considering others

● Lack of foundation leads to a proliferation of ‘standardisation’ efforts

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Research Foci: John Bateman

● Computational Linguistics● Multilingual natural language generation● Interfaces between language technology and

world/domain knowledge● Development of linguistically-motivated

ontologies

● Formal Ontology● General design principles for ontology● Relations between differently motivated

ontologies

● Spatial representation and language● Dialogic natural language interaction● Spatial language

1988

1992

2001

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Solution we are pursuing

● High degree of interoperability between diverse knowledge-rich systems is to be achieved by ontological engineering, taking in:

● knowledge of the human world (commonsense)● knowledge of the robot world (programmed, emergent)● geo-knowledge (GML, other standards)● spatial knowledge (spatial calculi, spatial ontologies)● knowledge of language (linguistics)

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ONTOLOGY 1 ONTOLOGY 2

Goals

● Achieving interaction between system modules using ONTOLOGIES

DOMAINS

ONTOLOGIES

inter-ontology mediation

HIGHLY STRUCTURED AND MOTIVATED SEMANTICS

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SPATIAL REPRESENTATIONS LINGUISTIC REPRESENTATIONS

Goals


DOMAINS

ONTOLOGIES


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SPATIAL REPRESENTATIONS GENERAL ONTOLOGY

Goals


DOMAINS

ONTOLOGIES


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ROUTE GRAPH R3: GVG ROUTE GRAPH A1: PATH

Goals


DOMAINS

ONTOLOGIES


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Ontologies...

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... but where to start?

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Fundamental issue

● The ontologies present are diverse:

● different methodologies● different motivations● different domains of application● different worlds● different purposes● different communities

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Representations of Space

● Ontology and Space

● Qualitative Spatial Representation and Reasoning

● Language

● GIS

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physicalmathematical

Geometry

ontology

Foundational Ontologies

QualitativeSpatial

Reasoning + Representation

Linguistics

R3

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Ontology + QSR: Varying primitives

25Bateman/Farrar (2006) Spatial Ontology Baseline

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Spatial Representations

● Ontology

● Qualitative Spatial Reasoning and Representation

● Language

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Ontologies: SUMO

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Ontologies: SUMO

● Shape: internal attribute (inheres in some entity)

● Position: relational attribute

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Ontologies: SUMO

● Spatial Relations

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Ontologies: Cyc

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Ontologies: Cyc

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Ontologies: Cyc

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Ontologies: Cyc: Paths

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Navigation: route graphs

GraphRoute

MZH 3rd Floor

kitc

he

nM

ZH

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00

MZ

H 3

11

0

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Ontologies: DOLCE basic categories

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DOLCE basic categories

Rooms, offices, buildings,tables, chairs, ...

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Events, happenings,movements, changes

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Agents, states of belief,plans, goals

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DOLCE inter-entity relationships

Feature(F)

Non-Agentive Physical Object

(NAPO)

Amount of Matter(M)

Physical Endurant (PED)

Physical Quality(PQ)

OGD

GK

MSDSMutual specific

spatial dependence

One-sided generic constant dependence

Generic constant constitution

Quality (Q)

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corner of a tablecurve of a bay

tablecoast

woodrocks, sand, water

heavypebbly

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● Ontology


● Language

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QSR: Region-Connection Calculus with 8 base relations

Randell, Cohn, Cui 1992: RCC8

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QSR: Region-Connection Spaces: RCC-5, RCC-8, 9+, etc.

Randell, Cohn, Cui 1992 etc. / Egenhofer

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QSR: Reasoning by Composition

43Composition table for RCC-8

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QSR: Double cross calculus: Freksa / Zimmermann (1996)

Qualitative description of position relative to a directed line segment

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QSR: Reasoning by Composition

Composition with additional relations

Homing, Shortcut, Inverse, Homing-Inverse,Shortcut-inverse

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QSR: Star Calculus

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Renz/Mitra 2004

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QSR: Dipole

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Moratz et al. 2000

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QSR: OPRA

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Moratz et al. 2005

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QSR: QTC

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Van de Weghe et al.

Qualitative Trajectory Calculus

single object moving

two objects moving

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● Ontology


● Language

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Linguistic usage evidence…

Herskovits (1986)

what does ‘on’ mean?

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And more usage evidence…

Herskovits (1986)

what does ‘in’ mean?

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54Herskovits (1986:125) “The cat is in the table”



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55Herskovits (1986)

The potato is in the bowl



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Relating calculi and language

● Egenhofer and colleagues 56

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Spatial Language

•extremely flexible

•sensitive to function and purpose

Coventry, Garrod and others

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Many types of spatial information

● Ontology● Qualitative calculi:

● RCC-n, Dipoles, Doublecross, etc.

● Way-finding abstractions: choremes● Free-space representations (Voronoi)● Natural language descriptions● Metric maps

● With different reasoning methods, different coverage, different strengths and weaknesses

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physicalmathematical

Geometry

ontology

Foundational Ontologies

QualitativeSpatial

Reasoning + Representation

Linguistics

BFO DOLCE GFO RCC DC OPRA 9+ GUM-Space

‘alignment’? ? ? ?

R3

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Methodological conclusion and starting point

● There is no sense in which a simple ‘merging’ of all of the above is a sensible strategy to follow

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Distinct facets or ‘theories’ rather than inheritance

lake

geographical region

obstacle

recreational area

source of pure water

link in transit system (ferry)

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Many perspectives on ‘reality’: many ontologies

event

time

space-1

space-2

event

Ontologically diverse

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Ontological diversity inter-ontology mappings

Way description

time

landmarks

choremes

event types

CASL

CASLCASL

route graphs

CASL

CASL

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Mapping between modules

problem area

time

points of interest

directions

road conditions

health status

“Hyperontology”

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Essential properties we are currently developing

● Perspectivalism● Objects● Activities● Artifacts: spatial artifacts● Language

● Granular partitions

● Plug-and-play spatial theories

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Essential ingredients we are drawing on

● Existing ontologies

● Existing formal tools

● Extensions for the specific problem of combining information flexibly

● Combining distinct reasoning possibilities

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● Existing ontologies

● DOLCE (for cross-category binding and axiomatization)

● BFO (for sites, niches and places and for SNAP/SPAN)

● GUM (generalized upper model for linguistic semantics)

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Defining Qualities

Quality Space

Gärdenfors: Geometric

Fauconnier: Logical

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Defining Qualities

Quality Space

Gärdenfors: Geometric

Fauconnier: Logical

Goguen: algebraic theoryTheory

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GREY GREEN

YELLOWORANGE

RED

VIOLET

HUE

CHROMATICNESS

From: Gärdenfors (2000, p10)

Color Space (1): Color wheel

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RED

YELLOWGREEN

BLUE

BLACK

WHITE

From: Gärdenfors (2000, p11)

CHROMATICNESS

Color Space (2)

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RED

YELLOWGREEN

BLUE

BLACK

WHITE

Defining Qualities

Quality Space

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Dolce treatment of qualities

Qualia: the position of an individual quality within a quality space

), t)

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DOLCE: spatial information

For DOLCE, space is also a quality...

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DOLCE: relevant for space

Physical ObjectsPhysical Endurants (PED) Spatial Location

Space Region

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DOLCE: relevant for space

Physical ObjectsPhysical Endurants (PED) Spatial Location

Space Region

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), t)

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Space Region

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Valuable for `swappable’ treatments of space

PED PQ

qt

ql

Physical Endurant Physical Quality Quality Space: quale

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`Swappable’ treatments of space

PED PQ

qtql

RCC-5,7,8,10,15,23Dipoles: D14 , DRA14 DRAfp

Cardinal directionsDouble Cross

Formalized modules

Should be possible to select formalization for the reasoning task at hand

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● Formal and computational tools

● CASLCommon Algebraic Specification Language (for specification, structuring and relating)

● HETS Heterogeneous Tool Set(for connecting to a range of reasoners)

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• Standardised first-order specification language

• designed by CoFI “Common Framework Initiative for algebraic specification and development” since 1995

• de facto standard approved by IFIP WG 1.3 “Foundations of Systems Specifications” (1998), extensive documentation (LNCS 2900, 2960)

• extensive User Manual and Reference Manual now available from Springer (LNCS 2900, LNCS 2960)

• supports structured specifications including imports, hiding, renaming, union, extensions, etc.

Formalization choice: CASL Common Algebraic Specification Language

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The Tool HeTSInstitution T

heory

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Formalization choice: CASL Common Algebraic Specification Language

Extensions:

● we have now added OWL-DL to the family of logics supported

● we are exploring combining the structuring principles of CASL and description logics

● we are progressively formalizing the entire family of qualitative spatial calculi

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Lüttich & Mossakowski (FOIS 2004)

Axiomatized Ontology in CASL

GenParthood

Primitives

DOLCE

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GenMereology

GenParthood

DOLCE

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spec MEREOLOGY =PRIMITIVES

then%%Ad7, Ad8, Ad9 and Ad10 are generated by %% instantiation of GenMereology

GENMEREOLOGY [sort T]then

GENMEREOLOGY [sort S]then

GENMEREOLOGY [sort PD]end


GenMereology

GenParthoodPrimitives

Mereology

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The DOLCE ontology in CASL

spec PreDolce =

Mereology_and_TemporalPart

and Temporary_Mereology

and Participation

and Constitution

and Dependence

and Direct_Quality

and Temporary_Quale

and Immediate_Quale

end

spec Dolce = PreDolceand Taxonomyend

work continuing...

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Development Graph

showing dependencies between specificationsand proof obligations

Links: theory morphisms

• imports of theories• relative interpretations of

theories• open• proved

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Reasoning

● First-Order Reasoning with CASL/HETS reasoners

● Description logic reasoning with DL reasoners

● Spatial Reasoning with specialized spatial reasoners: SparQ, GQR

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Reasoning: SparQ

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Frank Dylla, Lutz Frommberger, Jan Oliver Wallgrün, and Diedrich Wolter

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Lessons drawn

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● Idea: Providing channels to ontologies provides access to detailed contextual ‘world-knowledge’ that does not then have to be worked out again…

Application

Ontology

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Sharing knowledge and achieving interoperability

● Many projects, many products, many information providers now constructing ontologies

● BUT: ● proliferation of unrelated designs, ● impoverished or application-specific semantics, ● ‘roll your own’ ignoring previous attempts● lack of interoperability

... which was precisely whatontologies were meant to provide!

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Metamodels:commonly restricted to ensuring translatability across formal languages not content

Horiuchi

modelling language

dependence

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Manchester, 15/16 January 2004 6

Levels of Ontological Precision

Ontological precision

Axiomatized theory

Glossary

Thesaurus

Taxonomy

DB/OO scheme

tennisfootballgamefield gamecourt gameathletic gameoutdoor game

Catalog

gameathletic gamecourt gametennis

outdoor gamefield gamefootball

gameNT athletic gameNT court gameRT courtNT tennisRT double fault

game(x) activity (x)athletic game(x) game(x)court game(x) athletic game(x) y . played_in(x,y) court(y )tennis(x) court game(x)double fault(x) fault(x) y . part_of(x,y ) tennis(y )

precision: the ability to catch all and only the intended meaning(for a logical theory, to be satisfied by intended models)

LOA, Dolce group: EU WonderWeb Project

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Problems...

● Looseness of definition

● Sparseness of definition

does not give much to ‘get hold of’ for relating distinct accounts/levels of abstraction

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Conclusions: Ontology Best Practice

● ‘Light’ ontologies: semantic web ...

● ‘Heavy’ ontologies:● Rich axiomatization● Formal principles ● Well-defined design criteria

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Lessons drawn

● Ontological best design principles

● axiomatization● modularity● heterogeneity● perspectivalism

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Ontology construction

● Axioms are grouped into logically appropriate theories● Theories may be extended via parameterization to

achieve semantic re-use● Theories may be created and related by views: theory

morphisms

Only with this availability of working with meaningful interrelationships can the complexity of distinct axiomatized ontologies really be harnessed.

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Where next?

● Geospatial Information set to become the next major area of ontological development?

● However, just converting existing schema to OWL is probably not going to be adequate

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Questions: modularity?

103OpenGIS® City Geography Markup Language (CityGML) Encoding Standard (2008)

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Questions: modularity?

104Geometry to BDM to IFC

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Selected Application Scenarios

● assisted ambient living (AAL)

● ADL, spatial activities, ...

● geographic information science (GIS)

● OpenGIS, OGC, CityML, OpenStreetMap, ...

● assisted architectural design (AAD)

● IFC, BIM, ...

In each application area, we want to interact directly with the appropriate national and international standards

Our Next Steps

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Geographic Information Systems Ontologies

Our Next Steps

• framework for connecting distinct geographic layers

• modular breakdown of relevant knowledge improving re-use

• relation to non-geographic modeling

• relation to qualitative representations

• relation to existing standards

• support for verbalisation and visualisation

OpenStreetMap106

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and we can only do that in cooperation with those with the detailed expert knowledge!

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Acknowledgements

● The entire SFB/TR8 team!

● http://www.sfbtr8.uni-bremen.de

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