Some design patterns for domain ontology building and analysis

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Oct 22, 2013 (3 years and 5 months ago)

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Some design patterns for domain
ontology building and analysis

Aldo Gangemi

a.gangemi@istc.cnr.it

LOA
-
ISTC
-
CNR, Viale Marx 15, Roma, Italy



Manchester, 15/16 January 2004

2

What is LOA?


Laboratory_for_Applied_Ontology


-
partOf
-

Institute_of_Cognitive_Sciences_and_Technology


-
partOf
-

Italian_National_Research_Council


-
memberNumerosity
-

125 (70 staff)


-
location
-

{Roma, Trento, Padova}


-
head
-

Cristiano_Castelfranchi


-
memberNumerosity
-

13


-
location
-

{Roma, Trento}


-
head
-

Nicola_Guarino


-
researchTopic
-

{axiomatic_theories,
foundational_ontologies, domain_ontologies,
lexical_ontologies, ontology_development}

Manchester, 15/16 January 2004

3

Selected ongoing Projects


IKF

: Intelligent Knowledge Fusion (Eureka Project)



Ontology of banking transactions

(
with
ELSAG Banklab)



Ontology of Service
-
Level Agreement and IS monitoring

(
with
SELESTA)



Ontology of Insurance Services (with
Nomos SpA
)



WonderWeb

(FP5): Ontology Infrastructure for the Semantic Web (LOA: foundational ontologies for
the Semantic Web, ontology of information, ontology of services)



OntoWeb

(FP5
-

NoE): Ontology
-
based information exchange for knowledge management and
electronic commerce (LOA:
SIG on Content Standards
)



FOS

(with UN
-
FAO): Alignment of legacy fishery terminologies, ontology
-
based query expansion



Metokis

(FP6
-

Strep): Middleware between domain knowledge and user task
-
oriented applications
(LOA: Task modelling ontology for the communication of knowledge objects)



SEMANTIC MINING

(FP6
-

NoE): Semantic Interoperability and Data Mining in Biomedicine



TICCA

(PAT&CNR): Interaction and cooperation with artificial agents (LOA: ontology of social
interaction)


Manchester, 15/16 January 2004

4

Collaborations


U. of Trento, Padova, Roma, Torino,
Verona


ITC
-
IRST


ITTIG
-
CNR, ILC
-
CNR


History of Science Museum, Florence


IRIT
-
CNRS


IFOMIS


Columbia University


U. of Manchester, Leeds


U. of Amsterdam, VUA


Berlin
-
Brandenburgische Akademie der
Wissenshaften


U. of Leipzig, Bremen, Hamburg


European Media Lab, Heidelberg


U. of Salzburg


U. of Queensland


ICS
-
Forth, Heraklion


UPM



IBM Italia



Nomos Spa



Selesta Spa



Elsag Spa



Libero/Wind




UN
-
FAO




Boeing Inc



IBM Watson Research Centre



Ontology Works



Language & Computing


Manchester, 15/16 January 2004

5

Research topics


Logical tools

for ontological analysis and development


Domain ontologies


Physical objects and artifacts


Information and information processing


Social interaction


Legal and financial entities


Biomedical entities


Services and planning


Fishery and agriculture


Cultural heritage


Ontology in
language and cognition


Lexical ontologies


Ontology
-
driven
information systems


Conceptual modeling


Information access


Information integration

Manchester, 15/16 January 2004

6

Levels of Ontological Precision

Ontological precision


Axiomatized
theory

Glossary

Thesaurus

Taxonomy

DB/OO
scheme

tennis

football

game

field game

court game

athletic game

outdoor game

Catalog

game


athletic game


court game


tennis


outdoor game


field game


football

game

NT athletic game


NT court game


RT court


NT tennis


RT 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)

Manchester, 15/16 January 2004

7

Ontological layers

A layering example in molecular biology

Manchester, 15/16 January 2004

8

DOLCE foundational

ontology

OntoWordNet

fragments

Fishery core

ontology

Fishery legacy

“light” ontologies

Use of layers in ontology integration

An example in fishery

Manchester, 15/16 January 2004

9

WW Foundational Ontologies Library (WFOL)


Reflects different commitments and purposes, rather than a
single monolithic view.


A starting point for building new foundational or domain
ontologies.


A reference point for easy and rigorous comparison among
different ontological approaches.


A common framework for analyzing, harmonizing and
integrating existing ontologies and metadata standards.


Manchester, 15/16 January 2004

10

The structure of the WFOL


Modules are organized along two dimensions:


visions
, corresponding to basic ontological choices made


specificity
, corresponding to the levels of generality/specific domains

Choose Vision

Choose

Specificity

Top

Bank

Law

4D

3D

Single Vision

Single Module

Formal Links

Between Visions

and Modules

Mappings between

Visions/Modules

and Lexicons

Manchester, 15/16 January 2004

11

Current “implementation” of the WFOL


Axiomatic (FOL) characterization of three visions (DOLCE,
OCHRE, and BFO)


KIF encoding of DOLCE and OCHRE


OWL encoding of (a part of) DOLCE (DOLCE
-
Lite)


OWL/KIF encoding of (a part of) DOLCE+D&S (DOLCE
-
Lite+)


OWL/KIF encoding of the web services “ontology”


Formal mapping of OCHRE into DOLCE


WordNet
-
DOLCE alignment (in KIF)



core ontologies extending DOLCE
-
Lite+

in specificity (time,
plans, services, legal, finance, …)


… forthcoming
OCML version of DOLCE
-
Lite+

Manchester, 15/16 January 2004

12

Basic Assumptions of DOLCE


DOLCE:
a Descriptive Ontology for Linguistic and Cognitive
Engineering



Strong Cognitive/Linguistic bias


Categories mirror cognition, common sense, and the lexical
structure of natural language.


Categories as

conceptual containers
:

no “deep” metaphysical
implications wrt “true” reality.


No deep commitment on “intellectual economy” of the primitives
notions adopted: focus on the simplicity of the representation
primitives.

Manchester, 15/16 January 2004

13

Basic Ontological Choices in DOLCE


Objects/Substances

and
Events/Processes
are distinct categories
linked by the relation of
participation
.


Qualities

inhere in

Objects (Physical Qualities) or in Events (Temporal
Qualities) and they corresponds to “individualized properties”, i.e. they
inhere

only

in a specific entity, e.g. “the color of this court”, “the velocity
of this serve”, etc.


Each kind of Quality is associated to a
Quality Space

representing the
space of the values that qualities can assume


Quality Spaces are neither in time nor in space


Different quality spaces associated to the same kind of Quality are
admitted.


Space

and
Time

are specific quality spaces


Different kinds of space and time are admitted.


Different Objects or Events can be spatio
-
temporally co
-
localized: the
relation of
constitution
is considered


Rich axiomatization of classes and relations

Manchester, 15/16 January 2004

14

Going practical: Generic Use Cases and
Ontology Design Patterns


Foundational ontologies are
applied


Sample Generic Use Cases:


who does what, when and where?


what are the parts of sth?


what is it made of?


what’s the place of sth?


what’s the time frame of sth?


how can you do what you do?


does my behaviour conform to that rule?


what’s the function of that artifact?


how is it built?


how did that phenomenon happen?


what’s your role in that affair?


is my scheduling compatible with yours?

Manchester, 15/16 January 2004

15

DOLCE
-
Lite+ library

Top

DOLCE
-
Lite

Descriptions

Extrinsic

Modalities

Communication

Time m.topology

Funct. participation

Places

Plans

WN alignment

Biomedical Domain #2

Legal Domain #1

Banking Domain #3

Services

WordNet

link to
built
-
in

representation ontologies

Manchester, 15/16 January 2004

16

From foundational ontologies to ODPs

Manchester, 15/16 January 2004

17

Related work on design patterns


Theoretical architecture
: C. Alexander, The Timeless way of
building, 1979


Software engineering
: E. Gamma et al., Elements of reusable
OO software, 1994


D. Maplesden et al., Design Pattern Modelling Language


N. Baker et al., Meta
-
modelling patterns (
-
> “descriptive models”)


Ontology engineering
(very recent interest):


G. Guizzardi et al., LINGO: foundation for meta
-
environments,
domain engineering in requirement analysis (bridging OE and OO)


J.R. Reich, patterns of ontology constructs, applied to Mbiology


M. Klein: ontology change/versioning patterns


G. Schreiber: started committee on DPs in OE


ODPs here: focus on the architecture of the content, rather than on
the architecture of the logical form that represents that content

Manchester, 15/16 January 2004

18

This talk: using UML class diagrams


Non
-
standard use of UML to visualize ODPs:


generalisation
-
> subsumption (“subClassOf”)


association
-
> two
-
way conceptual relation (“property”)


attribute
-
> one
-
way conceptual relation (“property”)


assuming reasoning capabilities with classification and role
chaining


association with no cardinality: 0..*

Manchester, 15/16 January 2004

19

Basic DOLCE pattern

(participant match#1 {Enrico, Aldo})

(located {Enrico, Aldo} Milton_Keynes)

(located match#1 2004_Jan18_1:00
\
2:00GMT)

(part match#1 ace#12)

Manchester, 15/16 January 2004

20

Time intervals pattern

MTA(x,y) (MereoTopological Association) =df


weekly connected(x,y)



strongly connected(x,y)



part(x,y)



overlaps(x,y)



successor(x,y))

[(located match#1 2004_Jan18_12:00
\
13:00GMT)

(located match#2 2004_Jan23_12:00
\
13:00CET)

(successor 2004_Jan18_12:00
\
13:00GMT 2004_Jan23_12:00
\
13:00CET)]



(precedes match#1 match#2)

deducible from

sufficient conditions

Manchester, 15/16 January 2004

21

Places pattern

(place ball#1 racquet#2)



[
(located ball#1 ball#1_space)

(located racquet#2 racquet#2_space)

(weakly_connected ball#1_space racquet#2_space)]

not deducible from

necessary conditions

Manchester, 15/16 January 2004

22

Extensions of DOLCE (1)

Descriptions and Situation


It’s an ontology of
rationality
and
epistemology
(about “knowledge” objects)


Pluggable in any existing “ground” ontology


Reified theories, concepts, and states of affairs


Reified theories are called
s
-
descriptions

(or
contexts
)


Reified concepts are called
c
-
descriptions

(or
roles
)


Reified states of affairs are called
situations
(or
configurations
)


An s
-
description can be
satisfied by

a situation


An s
-
description is
composed by

c
-
descriptions


A situation is
constituted by

entities in the ground ontology


A c
-
description has systematic relations with sibling c
-
descriptions, and with
entities in the ground ontology


There results a typical design pattern to develop “core” domain ontologies


D&S is able to explicit:


the commited entities in a domain


the roles and contexts in which those entities are used, and


the expected or desired configurations that appear in those roles/contexts


Manchester, 15/16 January 2004

23

Situations


States of affairs

can be extracted from the world in many ways


Situations

reify states of affairs under a certain
descriptive Unity Criterion


A situation must satisfy at least one
s
-
description


This means that no state of affairs is reified in D&S unless it has an explicit s
-
description (
constructivist stance
)


only what we are dealing with …


uselessness of providing combinatorial precomputation of SOAs


Many uses of D&S involve matching an independently introduced situation to
existing s
-
descriptions (e.g. legal cases vs. jurisprudence, executions of plans
vs. plans, clinical conditions vs. diagnoses, etc.)


some D&S apps do not involve matching, e.g. narrative descriptions


A situation can then be matched either against its generating description (e.g. in
plan execution assessment), or against a new one (e.g. in legal cases or in
clinical diagnoses)


the second case can be called
redescription


these mechanisms are inspired by cognitive processes like Gestalt psychology
figure
-
ground
, and development as
re
-
presentation

(cf. Koehler, Karmiloff
-
Smith)

Manchester, 15/16 January 2004

24

some D&S axioms

Manchester, 15/16 January 2004

25

Minimal D&S pattern (pluggable into any FO)

[(s
-
description
traffic_norm#232
)


(c
-
description {
driving_task, driver, vehicle, speed_limit
)


(selects driving_task
driving#3283376400
)


(selects driver
Enrico
)


(selects vehicle
Lotus_Elise#M186YER
)


(selects speed_limit
60mph
) (speed_location
driving#3283376400

130mph
)]


[@
(situation
driving_sit#666
)


(setting
-
for driving_sit#666



{driving#3283376400, Enrico, Lotus_Elise#M186YER, 130mph})]

@(

)

means that the situation

is generated through a “door”

s
-
constituent on the basis of

production rules

Manchester, 15/16 January 2004

26

DOLCE+D&S pattern

Ground entities

Descriptive entities

Manchester, 15/16 January 2004

27

D&S specialization for norms

[(legal_description
traffic_norm#232
)


(legal_course
driving_task
)


(legal_role
driver
) (legal_role
vehicle
)


(legal_parameter
speed_limit
)


(sequences driving_task
driving#3283376400
)


(played_by driver
Enrico
)


(played_by vehicle
Lotus_Elise#M186YER
)


(valued_by speed_limit
60mph
)


(speed_location
driving#3283376400

130m
)]



[@
(case
driving_sit#666
)


(setting_for driving_sit#666


{driving#3283376400, Enrico, Lotus_Elise#M186YER, 130m})]

Manchester, 15/16 January 2004

28

Extensions of DOLCE (2)

Plans and task models


Using D&S, some other extensions are being developed


A preliminary plan ontology has been defined by starting from the
harmonizing of existing clinical guidelines standards


Basic distinction between plans as contexts (
methods
), and plan
execution as configuration


Typical attributes of plans are different from those of an execution (e.g.
“approved” vs. “started”)


A plan is composed by
tasks
,
roles
, and
parameters


Tasks
sequence

actions or processes


Succession relations applicable that mirrors temporal relations


Task≠Action (cf. “alternative” vs. “running”)


Distinction btw action tasks and rational tasks (branching, joining)


Roles are
played by

objects or substances


Parameters
select

regions within quality spaces


Plan representation is also addressed by using an ontology of
communication


Manchester, 15/16 January 2004

29

D&S specialization for plans

Manchester, 15/16 January 2004

30

D&S specialization for designs

Manchester, 15/16 January 2004

31

Information and symbols pattern

Manchester, 15/16 January 2004

32

D&S specialization for inflammations

Manchester, 15/16 January 2004

33

D&S specialization for fishery

Manchester, 15/16 January 2004

34

Features of ontology design patterns


Any ontology is a potential domain design pattern, since it can instantiate a set
of states of affairs.


An ODP focuses on specialization, rather than instantiation


An ODP is similar to top
-
level or foundational ontologies, but it has certain
additional properties:


1.
An ODP is a template for solving a domain modelling problem

2.
An ODP "extracts" a fragment of a TLO or FO, which is its "background”

3.
An ODP is axiomatized according to the fragment it extracts

4.
An ODP can be represented in any ontology representation language, although its
intuitive and compact visualization seems an essential requirement

5.
An ODP can be an element in a partial order, where the ordering relation requires that
at least one of the classes or relations in the ODP are specialized

6.
An ODP can be intuitively exemplified and catches relevant "core" notions of domains

7.
An ODP can be often built from informal or simplified schemes used by domain
experts, together with the support of a foundational ontology and a methodology for
domain ontology analysis, or by specializing existing ODPs

8.
An ODP can/should be used to describe a "best practice" of modelling

9.
An ODP is similar to a DB schema, but an ODP is defined wrt a foundational ontology
and should have a general character, independently from local design details

Manchester, 15/16 January 2004

35

Application of DOLCE (3)

WordNet alignment and OntoWordNet


OntoWordNet research program jointly with other institutions


809 synsets from WordNet1.6 directly subsumed by a
DOLCE+D&S class


Whole WordNet linked to DOLCE+D&S


Lower taxonomy levels in WordNet still need revision


Glosses being transformed into DOLCE+ axioms


Machine learning applied jointly with foundational ontology


WordNet “domains” being used to create a modular, general
purpose domain ontology


Manchester, 15/16 January 2004

36

Considerations on domain ontology building


Developing precise domain ontologies is time
-
consuming, and
requires high competences


Not always is deep granularity required


Not always is full expressivity required


Our position:


“lightweight” is ok, but if we a have a level for sharing intuitions and
to establish negotiation, it is much better


“local” precise ontologies are ok, but if we have a level to align and
merge different locals, it is much better


precision is “heavyweight”, but scalability is reachable by using
good patterns and interfaces