Twentyone Years of Applied Ontology 1993-2014

Nicola Guarino National Research Council, Institute for Cognitive Science and

Technologies (ISTC-CNR) Laboratory for Applied Ontology (LOA)

www.loa.istc.cnr.it !

Thanks to Giancarlo Guizzardi and all the LOA people!

Presented at International Workshop on Formal Ontology, March 1993, Padua, Italy – Organized by LADSEB-CNR (N. Guarino and R. Poli)

The most cited paper in applied ontology

Carving the reality at its joints: good ontologists

like good butchers [Plato]

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…but, despite reality resists, still many possibilities are open!

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Applied Ontology: an emerging interdisciplinary area

• Applied Ontology builds on philosophy, cognitive science, linguistics and logic with the purpose of understanding, clarifying, making explicit and communicating people's assumptions about the nature and structure of the world.!

• This orientation towards helping people understanding each other distinguishes applied ontology from philosophical ontology, and motivates its unavoidable interdisciplinary nature.

ontological analysis: study of !content (of these assumptions) as such !(independently of their representation)

Focusing on content

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Do we know what to REpresent?

• First analysis,!• THEN representation…!

Unfortunately, this is not the current practice…!

• Computer scientists have focused on the structure of representations and the nature of reasoning more than on the content of such representations!

Essential ontological promiscuity of AI: any agent creates its own ontology based on its usefulness for the task at hand (Genesereth and Nilsson 1987)

No representation without ontological analysis!

Logic is neutral about content

...but very useful to describe the formal structure (i.e., the invariances) of content

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Kinds of knowledge"(Carnap - Meaning and Necessity)

Fido is black!

either Fido is black or Fido is not black!

If Jack is a bachelor, then he is not married

syntheticlogical

analytic

terminological

(assertional)

Terminological knowledge is about relationships between terms and concepts

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The problem: subtle distinctions in meaning

!The e-commerce case:!!

“Trying to engage with too many partners too fast is one of the main reasons that so many online market makers have foundered”

The transactions they had viewed as simple and routine

actually involved manysubtle distinctions in terminology and meaning”!

!Harvard Business Review, October 2001

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Subtle distinctions in meaning...

• What is an application to a public administration?!• What is a service?!• What is a working place?!• What is an unemployed person?!• What is a customer?!• What is an organization?!• What is a contract?

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

Semantic Interoperability is considered to be the problem of this decade…[currently] costing productivity, lives and billions of dollars annually…the overall human and

financial cost to society from our failure to share and reuse information is many times the

cost of the systems’ operation and maintenance [OMG, SIMF]

When subtle distinctions are important:!fine prints

An ontology is like a contract's fine print, one of those things which require a very precise technical jargon, which you might ignore in many cases, but which can save your business in critical situations.

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Product Classification

• U.S. Product Classification:

• Dolls: Representing Only a Human-Being (12%)

• Toys: Anything that does not represent only a human being (6%)

What is an ontology

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Philosophical ontologies

• Ontology: the philosophical discipline!!• Study of what there is (being qua being...)!

...a liberal reinterpretation for computer science: !!content qua content, independently of the way it is represented!!

• Study of the nature and structure of “reality”!!

• A (philosophical) ontology: a structured system of entities assumed to exists, organized in categories and relations

Computational ontologies

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Specific (theoretical or computational) artifactsexpressing the intended meaning of a vocabulary

in terms of primitive categories and relations describing the nature and structure of a domain of discourse

Gruber: “Explicit and formal specifications of a conceptualization”

Computational ontologies, in the way they evolved, unavoidably mix together philosophical, cognitive, and linguistic aspects.!

Ignoring this intrinsic interdisciplinary nature makes them almost useless.

Ontology

Language L

Intended models for each IK(L)

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

Interpretations I

Ontology models

Models MD’(L)

Bad Ontology

~Good

relevant invariants within and across presentation

patterns:D, ℜ

Conceptualization

State of affairsState of

affairsPresentationpatterns

Perception Reality

Phenomena

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Ontology Quality: Precision and Correctness

Low precision, max correctness

Less good

Low precision, low correctness

WORSE

High precision, max correctness

Good

Max precision, low correctness

BAD

Why ontological precision is important

Database A: keeping track of fruit stock

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Variety Quantity

Granny Smith 12

Golden delicious 10

Stark delicious 15

Database B: keeping track of juice stock

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Variety Quantity

Granny Smith 12

Golden delicious 10

Stark delicious 15

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All interpretations

of “apple”

Why ontological precision is important

Area of false

agreement!

B - Juice producer’s intended

interpretationsA - Apple

producer’s intended

interepretations

Interpretations allowed by B’s

ontology

Interpretations allowed by A’s

ontology

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When is a precise (and accurate) ontology useful?

1. When subtle distinctions are important!

2. When recognizing disagreement is important!

3. When careful explanation and justification of ontological commitment

is important!

4. When mutual understanding is more important than interoperability.

Two classic KR problems solved by formal ontology

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Problem 1 - Terminological competence

rock

igneous rock sedimentary rock metamorphic rock

large rock grey rock

large grey igneous rock

grey sedimentary

rock

pet metamorphic rock

[From Brachman, R ., R. F ikes, et al. 1983. “Krypton: A Functional Approach to Knowledge Representation”, IEEE Computer]

How many rock kinds are there?

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The answer

• According to Brachman & Fikes 83: • It’s a dangerous question, only “safe” queries about analytical

relationships between terms should be asked • In a previous paper by Brachman and Levesque on terminological

competence in knowledge representation [AAAI 82]: • “an enhancement mode transistor (which is a kind of

transistor) should be understood as different from a pass transistor (which is a role a transistor plays in a larger circuit)”

• These issues have been simply given up while striving for logical simplification and computational tractability

• The OntoClean methodology, based on formal ontological analysis, allows us to conclude: there are 3 kinds of rocks

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Problem 2 - What’s in a link?

• Woods’ “What’s in a link?” (1975):

JOHN HEIGHT: 6 FEET KISSED: MARY !

• "no longer do the link names stand for attributes of a node, but rather arbitrary relations between the node and other nodes”

• different notations should be used

Structured concepts: a broader picture

JOHN HEIGHT: 6 FEET RIGHT-LEG: BROKEN MOTHER: JANE KISSED: MARY JOB: RESEARCHER

intrinsic quality

part

role

external relation

relational quality

We need different primitives to express different structuring relationships among concepts

We need to represent non-structuring relationships separately

Current description logics tend to collapse EVERYTHING!

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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 postulate s )

Meaning

Conceptual Conceptual relations

Subjective Conceptualization

Linguistic Linguistic terms

Subjective Language dependence

• Guarino N. 1994. The Ontological Level. In R. Casati, B. Smith and G. White (eds.), Philosophy and the Cognitive Sciences (by 16th International Wittgenstein Symposium, Kirchberg am Wechsel, Austria, 1993). Vienna, Hölder-Pichler-Tempsky 1994!

• Guarino, N. 2009. The Ontological Level: Revisiting 30 Years of Knowledge Representation. In Alex Borgida, Vinay Chaudhri, Paolo Giorgini, Eric Yu (eds.), Conceptual Modelling: Foundations and Applications. Essays in Honor of John Mylopoulos, Springer Verlag 2009

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The formal tools of ontological analysis

• Theory of Parts (Mereology) !• Theory of Unity and Plurality!• Theory of Essence and Identity!• 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

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The semantic web architecture [Tim Berners Lee 2000]

The Semantic Web Architecture (revised)

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Formal Ontology

• Theory of formal distinctions and connections within:!• entities of the world, as we perceive it (particulars)!• categories we use to talk about such entities (universals)!

• Why formal?!• Two meanings: rigorous and general!• Formal logic: connections between truths - neutral wrt truth!• Formal ontology: connections between things - neutral wrt reality!

• NOTE: “represented in a formal language” is not enough for being formal in the above sense!!

• Analytic ontology may be a better term to avoid this confusion

• Ontological analysis: systematic way to understand and make explicit the world assumptions behind a certain description:!• How do we believe the world is, when we say !

• This rose is red!• John is married with Mary!• John is a student!• My name is Nicola

• Data models encode knowledge about the world in order to easily and efficiently access it!

• Conceptual models describe some aspects of the world for the purpose of understanding and communication!

• Knowledge representations encode knowledge about the world in order to easily and efficiently access it and use it to generate new knowledge!

• Computational ontologies characterize the language used to talk about the world in order to reduce ambiguities and misunderstandings

Knowledge representation, conceptual modeling, and ontological analysis

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different role of axioms

possible expansions of domain !and vocabulary

Ontological analysis as a detective lens

• Most of our true statements about the world are approximate!

• What makes them true?!• Where…?!• When…?!• Who…?!

• Why…?!

• Ontological analysis as a search for Truth-makers

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A bit of history - Community building initiatives• 1993: 1st Int. workshop on Formal Ontology & Information Systems!• 1998: 1st FOIS conference!• 2002: Ontolog forum!• 2005: Applied Ontology (IOS Press)!• 2005: ECOR, NCOR, JCOR...!• 2006: First public discussion on an ontology association at FOIS !• 2008: Public assembly at FOIS (Saarbrucken)!• 2011: Applied Ontology gets official ISI recognition!• 2009-2012: Several focused conferences (FOMI, WOMO...)!• 2012: IAOA permanent co-organizer of Ontology Summit!• 2013: !

• IJCAI invites authors of best FOIS papers; !• Philosophical community (J. Lowe) organizes a conference on applied

ontology!!

• In parallel: various consortia focusing mainly on Semantic Web40

A new discipline is emerging

A hint from the past: The emergence of psychology as a science

• 1874: Franz Brentano publishes Psychology from an Empirical Standpoint!

• 1879: Wilhelm Wundt establishes the world’s first psychological laboratory at the University of Leipzig!

• 1883: First psychology lab in America established at Johns Hopkins!• University authorities give Wundt's Leipzig laboratory formal recognition!

• 1889: First international congress of Psychology!• Alexius Meinong founds Laboratory of Psychology in University of Graz!• First Chinese translation of a Western psychology book!

• 1892: American Psycgological Association founded (42 members)!• 1894: Stumpf called to serve as professor of philosophy in Berlin with

the explicit task of establishing there an institute of psychology

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Typical reactions to the founding of a new discipline

If one is interested in the relations between fields which, according to customary academic divisions, belong to different departments, then he will not be welcomed as a builder of bridges, as he might have expected, but will rather be regarded by both sides as an outsider and troublesome intruder.! R. Carnap, "My Work in Philosophy Begins".

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From metaphysics to ontology as a science

Metaphysics (phil.)!

! The science of being!

Ontology (phil.) !

! A theory of the types of entities existing in reality, and of the relations between these types!

Ontologies (tech.)!

! Standardized classification systems which enable data from different sources to be combined!

Ontology (science)!

! The science which develops theories of the types of entities existing in (people’s assumptions about) given domains of reality, and of the relations between these types including: ways of testing such theories, ways of using such theories, e.g. in supporting reasoning about empirical data collected by other sciences

The Association is addressed to:

• Philosophers who have an interest in applying their analytical tools to

technology advancement; • cognitive scientists, linguists and terminologists aware of the subtle

interplays among ontology, language, and cognition; • computer scientists and IT professionals aware of the desperate need of

a sound interdisciplinary approach for building future generation socio-technical systems.

From the Statute

“The Association is a non-profit organization the purpose of which is to

promote interdisciplinary research and international collaboration at

the intersection of philosophical ontology, linguistics, logic,

cognitive science, and computer science, as well as in the

applications of ontological analysis to conceptual modeling,

knowledge engineering, knowledge management, information-

systems development, library and information science, scientific

research, and semantic technologies in general.”

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IAOA: a unique combination of key aspects

1. Interdisciplinarity!

2. Cooperation between academy, industry, and communities of practice (with an eye on education)!

3. Scientific authoritativeness!

4. Openness!

5. Legal status!

6. Transparent governance

The IAOA flagship journal: Applied Ontology

Editors in chief: Nicola Guarino ISTC-CNR

Mark Musen Stanford University

!!IOS Press Amsterdam, Berlin, Washington, Tokyo, Beijing

www.applied-ontology.org

Now indexed by ISI and Scopus. Impact Factor: 1.105

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Is applied ontology successful?

“The  fast-­‐growing  science  of    ontology  could  exert  a  greater    impact  on  humanity  than  the    rise  of  the  Internet…ontologies    

allow  for  data  to  interoperate  and  for  machines  to  make  inferences.  The  report  calls  for  more  education  and  training  opportunities  for  ontologists,  and  for  better  means  of  connecting  ontologists  with  organizations  that  need  them.

In 2014, the Financial Research Advisory Committee (FRAC) of the US Treasury’s Office of

Financial Research (OFR) unanimously recommended the adoption of ontology as a

significant part of the OFR’s initiatives to meet the requirements put forth by the Dodd-Frank Act

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Ontologies and (big) data

A new discipline (or science) is emerging?

Maybe.!

See the history of Psychology, Systems Engineering...!

See recent proposals for Web Science, Services Science, Data Science??…!

For sure, a humble, truly interdisciplinary approach is needed, focusing on letting new ideas, approaches, methodologies emerge

from the mutual cross-fertilization of different disciplines.

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MethodologyCurrent Research topics

Ontology of socio-technical systems!• Multi-agent systems, social interaction, and collective intentionality!• Ontology of organizations and social roles!• Ontology of functions, artefacts, and engineering design!• Integrated modelling of organizations, processes, and services!• Ontological foundations of service science and value-cocreation!• Visual recognition of crisis situations; role of emotions in crisis situations!• Role of crises and contradiction in social interaction!

Ontology, language, cognition!• Ontology, cognition, and natural language semantics!• Ontology and lexical resources!• Formal semantics of discourse and dialogue relations!• Ontology and epistemology of measurement!• Perception of visual objects!• Perception, social conventions, and ontological constructivism!

Principles and methodologies for ontological analysis, conceptual modeling, knowledge representation, and software engineering!

• Formal ontological analysis: theories of properties, qualities, parts, unity, identity, dependence...!

• Ontology-driven conceptual modelling