Ontological Analysis for Conceptual Modeling:

Foundational Ontologies

Roberta Ferrario Laboratorio di Ontologia Applicata (LOA)

Istituto di Scienze e Tecnologie della Cognizione (ISTC-CNR) Trento, Italy

www.loa-cnr.it

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Summary

•  The semantic dimension : from form to content •  The role of ontological analysis: what are ontologies and what

are they for •  Formal ontology and the bases for ontological analysis •  Ontology-driven information systems •  An application and an approach: services

The focus of ontological analysis: from form to CONTENT

§  The key problems content-based information access (semantic matching) content-based information integration (semantic integration)

To approach them, content must be studied, understood, analyzed as such,

independently of the way it is represented. Computer technologies are not really good for that... …and users of computer systems are often confused by technology

Ontologies: a magic solution?!

No ontology without ontological analysis!

Do we know what to REpresent?

First ontological analysis, THEN knowledge representation…

Unfortunately, this is not the current practice…

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So… Nothing new?!

•  Investing on analysis always pays off (most of all in a re-use perspective)

•  To use instruments of ontological analysis and of semantic technologies offers further advantages:

•  The analysis is more robust, well-founded, re-usable •  Semantic technologies offer advantages (as automatic reasoning)

both at design time and at run time •  Analysis (and ontology) can “automatically” guide nearly everything

in the system

A common alphabet is not enough…

“XML is only the first step to ensuring that computers can communicate freely. XML is an alphabet for computers and as everyone who travels in Europe knows, knowing the alphabet doesn’t mean you can speak Italian or French”

Business Week, March 18, 2002

Standard glossaries can help, but...

•  Defining standard vocabularies is difficult and time-consuming •  Once defined, standards don’t adapt well •  Heterogeneous domains need a broad-coverage vocabulary •  People don’t implement standards correctly anyway •  Vocabulary definitions are often ambiguous or circular

Ontology, lexicon, semantics

Distinctions among contents: Ontology (capital “o”) Reference to content: Lexicon, via Semantics Every organization, every computer system

Makes (implicit) ontologic assumptions Adopt a certain lexicon, to which an intended semantics is

ascribed.

Ontology and ontologies

Ontology: the philosophical discipline Study of what there (possibly) is Study of the nature and structure of reality

Domain of entities Categories and relations Characterizing properties

An ontology: a theoretical or computational artifact “An explicit and formal specification of a conceptualization” (Gruber) A specific artefact expressing the intended meaning of a vocabulary in terms

of the nature and structure of the entities it refers to

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The importance of philosophy for ontologies

•  In order to build a model that is implementable in an information system

one needs to understand what are the objects that populate the domain the system applies to and this is an important exercise of philosophy

•  The disciplines that deal directly with those objects usually don’t ask

questions on the foundations of the domain, taking them for granted

•  Example: organization theory or sociology don’t try to answer questions like those inherent to the materiality of organizations or to the nature of individuals possessing intentions

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The importance of ontologies for philosophy

•  On the other hand, facing the concrete modeling activity allows

philosophers to see old problems under a new light, thus showing new perspectives that wouldn’t otherwise have emerged

•  When one builds a model (especially a formal one) on the basis of a certain theory, such theory in some sense undergoes a validation

•  A model abstracts from what is not relevant, thus highlighting what is relevant; this allows to grasp more easily imprecisions and theoretical inconsistencies

What is a conceptualization?

Formal structure of (a piece of) reality as perceived and organized by an agent, independently of:

the vocabulary used the actual occurrence of a specific situation

Different situations involving same objects, described by different vocabularies,

may share the same conceptualization.

apple

mela same conceptualization

LI

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What is a conceptualization? A cognitive approach

Humans isolate relevant invariances from physical reality (quality distributions) on the basis of:

Perception (as resulting from evolution) Cognition and cultural experience Language

A set of atomic stimuli (input pattern) is associated to each situation Synchronic level: spatial invariants

Unity properties are ascribed to input patterns: topological and morphological wholes (percepts) emerge

Diachronic level: temporal invariants

Objects: equivalence relationships among input patterns belonging to different situations

Events: unity properties are ascribed to percepts patterns belonging to different situations

Ontology

Ontologies and intended meaning

Language L

Conceptualization C (relevant invariants across

situations: D, ℜ)

Intended models IK(L)

State of affairs State of

affairs Situations

Ontological commitment K (selects D’⊂D and ℜ’⊂ℜ)

Interpretation I

Ontology models IK(L)

Models MD’(L)

Bad Ontology

~Good

Ontology quality: precision and coverage

Low precision, max coverage

Less good

Low precision, limited coverage

WORSE

High precision, max coverage

Good

Max precision, limited coverage

BAD

Levels of ontological precision

Ontological precision

Axiomatic theory"

Glossary"

Thesaurus

Taxonomy

DB/OO scheme Catalog"

IA(L)

MD(L)

IB(L)

Why precision is important

Area of false agreement!

Precision vs. accuracy

In general, a single intended model may not discriminate among relevant alternative situations because of Lack of entities

Lack of primitives

Capturing all intended models is not sufficient for a “perfect” ontology

Precision: non-intended models are excluded Accuracy: non-intended situations are excluded

When is a precise (and well-founded) ontology useful?

1.  When subtle distinctions are important

2.  When recognizing disagreement is important

3.  When general abstractions are important

4.  When careful explanation and justification of ontological commitment is

important

5.  When mutual understanding is more important than interoperability

Ontologies and taxonomies

Ontologies vs. classifications

Classifications focus on: access, based on pre-determined criteria

(encoded by syntactic keys)

Ontologies focus on:

Meaning of terms Nature and structure of a domain

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Applied ontology •  Differently from other computer science approaches, applied

ontology has as a goal to produce conceptual models that are independent form applications and from ways of presenting data

•  Ontologies as axiomatic theories that have the purpose of describing explicitly the fundamental entities of a certain field of enquiry underlying their relevant properties and the relations among them

•  The methodology consists in preliminarily using the analytical tools taken from different disciplines (cognitive sciences, linguistics…) among which philosophy plays a dominant role

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Different kinds of ontologies

•  Foundational ontologies and domain ontologies

•  Foundational (top level) ontologies can be reused and specialized in domain ontologies or in task ontologies

•  Domain and task ontologies have the purpose of characterizing a precise domain of analysis, singling out the theoretical primitives that can better deal with the problems they are built to solve

•  Ideally, domain and task ontologies should rely on a foundational ontology that shows and drives modeling choices

•  Only at the end of such specialization process one can build application ontologies that are really functional

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The modular approach

•  As it is well known, within each discipline very heterogeneous

positions – often irreducible one to the other - may co-exist; for such reason assuming a modular approach is particularly helpful

•  Instead of relying on a unique monolithic ontological system, a

library of ontologies linked by formal relations can be built, in which each module, i.e. each ontology, expresses a particular position

A single, imperialistic ontology?

An ontology is first of all for understanding each other ...among people, first of all! not necessarily for thinking in the same way

A single ontology for multiple applications is not necessary Different applications using different ontologies can co-exist and co-

operate (not necessarily inter-operate) ...if linked (and compared) together by means of general enough basic

categories and relations (primitives).

If basic assumptions are not made explicit, any imposed, common ontology risks to be seriously misused or misunderstood opaque with respect to other ontologies

Which primitives? The role of ontological analysis

Theory of Essence and Identity Theory of Parts (Mereology) Theory of Wholes Theory of Dependence Theory of Composition and Constitution Theory of Properties and Qualities

The basis for a common ontology vocabulary

Idea of Chris Welty, IBM Watson Research Centre, while visiting our lab in 2000

The problem of primitives

Representation primitives vs. ontological primitives (against arbitrary interpretations)

Let's aim at general primitives, similarly to what happens in

mathematics: set, relation, transitive, symmetric…

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The ontological level

Level Primitives Interpretation Main feature

Logical Predicates, functions

Arbitrary Formalization

Epistemological Structuring relations

Arbitrary Structure

Ontological Ontological relations

Constrained (meaning postulates)

Meaning

Conceptual Conceptual relations

Subjective Conceptualization

Linguistic Linguistic terms

Subjective Language dependence

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Towards a methodology

•  Linguistic analysis: •  To simplify composite terms

•  hasMunicipalityJob, hasMunicipalityDateofBirth... •  hasStateVerificationDueContribution...

•  Analysis of dependences: •  relational/non relational terms

•  To associate data with the entities that have generated them (and the attributes to the entities they depend from)

•  To make explicit temporal entities: events, stories, situations... •  …and their participants •  Ex.: work relation (with its participants)

•  To analyze the effects of possible changes •  Address/geographical place...

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Towards a methodology (II) •  First steps of a formalization

•  Choice of the domain of discourse •  Choice of the relevant concepts and relations for the given domain •  Choice of the primitive concepts and relations (son vs. relative o ancestor)

1.  Alignment with a reference ontology (DOLCE?)

1.  Objects 2.  Events 3.  Qualities 4.  Facts 5.  Descriptions 6.  ...

•  Systematic ontological analysis in terms of formal properties and relations...

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Ontology-driven information systems

•  Each IS has its own (implicit or explicit) ontology •  The ODIS perspective: explicit ontologies play a central role, driving

all aspects and components of an IS •  Two (main) dimensions to claim the role of an explicit ontology :

•  Temporal dimension: development time vs. run time •  Structural dimension : impact on the various components of an IS:

•  Database component •  Application program •  User interface

An application: services!

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Services are everywhere..."Services do not operate in isolation, they interact with other

services, thus they are part of a service system!Service systems are themselves part of wider contexts, i.e. socio-

technical systems, that are composed by services, various technological artefacts, various other resources and social agents"

Different disciplines are interested in the study of services, but they lack a common understading of what services are"

"Need of a Services Science!"Chesbrough & Spohrer, A Research Manifesto for Services Science. Communications of the ACM, 2006"

""

Some terminological issues!

What is a service?"An action"A generic type of action"The capability to perform some action"A computational procedure capable to perform some action"An agent in charge of performing an action"An agent ready to perform an action"The result of an action"The (subjective) value of an action"..."

What is a service provider?"The authority which guarantees the presence of a service"The actual agent who executes the service actions (possibly on behalf

of somebody else) "…""

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From the black box to the glass box view!Current web services models (black box view): transfer function from an

input state to an output state Yet, business applications need to specify

how the service is performed at the business level, referring to internal details whose nature varies a lot from service to service

when the various processes involved in a service occur Business applications need to monitor and evaluate services quality with

respect to their actual impact on the whole service system, which includes external events, objects, people, organizations... (context-aware services)

Service Level Agreements need to refer both to internal and contextual details

Well-known gap between business services and IT Need to look inside the box and out of the box...

Looking outside the box !

"Taking people and society into account "

Putting people in the loop: from users to actors !Putting social interactions in the loop "Putting social institutions in the loop """

Taking external environment into account "External natural environment "Internal aspects of artifacts !Interfaces (sensors) "

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Looking inside the box!

"Cognitive transparency, to support: "

"At design time "

"participatory, concurrent, agile design "

""At run time "

"governance "control "

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Services as events: the basic idea!

""A service is an agent’s availability to guarantee some action useful for

somebody, upon prior agreement, in correspondence of certain events """

•  How can you tell that a service is present, here and now?"•  What do you pay for, when you invest in a service?"

A service is essentially a promise [O’Sullivan 2006]

The general components of a service system

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Service and service system as layered structures of events

The main actors!

Service Provider is the person or authority who commits to have the service executed"

Service Producer is the person or organization that actually performs the actions constituting the delivery of the service "Provider and producer may coincide, but this is not always the case. "

"Service Customer is the one that requests the service and then

negotiates for its customized delivery" Service Consumer is the direct beneficiary of the service "Customer

and consumer may coincide, but this is not necessarily so"Consumer and producer may also coincide, in very particular situations""

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The DOLCE taxonomy!

Examples of elementary axioms in DOLCE

Parthood: “x is part of y”P(x, y) ! (AB(x) " PD(x)) # (AB(y) " PD(y))

Temporary Parthood: “x is part of y during t”P(x, y, t) ! (ED(x) # ED(y) # T(t))

Constitution: “x constitutes y during t”K(x, y, t) ! ((ED(x) " PD(x)) # (ED(y) " PD(y)) # T(t))

Participation: “x participates in y during t”PC(x, y, t) ! (ED(x) # PD(y) # T(t))

Quality: “x is a quality of y”qt(x, y) ! (Q(x) # (Q(y) " ED(y) " PD(y)))

Quale: “x is the quale of y (during t)”ql(x, y) ! (TR(x) # TQ(y))ql(x, y, t) ! ((PR(x) " AR(x)) # (PQ(y) " AQ(y)) # T(t))

The anchoring to a foundational ontology(DOLCE)!

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A general model of services

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…But all this is DIFFICULT?!

Why on earth should it be simple?