1. Ontologies and Classifications
Nicola Guarino
Laboratory for Applied Ontology (LOA)
Institute for Cognitive Sciences and Technologies (ISTC-CNR)
Trento, Italy

2. Summary Ontologies and classifications play complementary roles
Classifications have a central role within information architecture
Proper use of classifications requires understanding their terms
Especially in presence of multiple, heterogeneous classifications
Main role of [computational] ontologies is to clarify the meaning of terms
Therefore, “ontology” is not just a trendy name for “classification”
Ontologies and classifications
play complementary roles
in information architecture

3. Functions of classifications in information architecture
The problem: understanding, sharing, integrating meaning
What are ontologies
Foundational vs. lightweight ontologies
The role of foundational ontologies
Ontologies as complementary to classifications

4. Functions of classifications
Support information retrieval and analysis.
partition the search space on the base of pre-determined criteria (encoded by syntactic keys)
Provide triggers for action.

5. A simple classification
Pictures
Home
Work
Vacations
Italy
Europe
What’s the meaning of these terms?
What’s the meaning of arcs?
…they do not represent analytic relationships!

6. The source of all problems: different languages, different conceptualizations

7. A first solution: glossaries and thesauri
Glossaries: link terms to concepts, described informally by glosses
Thesauri: add structural relationships (generalization, part, dependence, causation…) among terms (and concepts).
Multilingual glossaries and thesauri are available for many domains.
General thesauri (e.g., WordNet) are available for many languages

8. Standard glossaries and thesauri 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
Accessing and integrating heterogeneous glossaries and thesauri becomes a nightmare

9. The need to focus on 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 (focus is usually on representation and reasoning)
A strong interdisciplinary approach is needed
non c'e' niente in comune col mondo della magia, tranne forse il fumo - a volte denso - che spesso aleggia intorno a questo termine, e che a volte viene venduto per mascherare soluzioni superficiali e fragili di problemi seri e ricorrenti, o peggio ancora specchietti per le allodole che di fatto rimuovono i problemi stessi.
Le ontologie possono effettivamente risolvere molti problemi legati al contenuto, se sono ben fatte. Questa sara' una delle conclusioni che cerchero' di argomentare.

10. What is an ontology

11. 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.

12. Ontology and Ontologies
Ontology: the philosophical discipline
Study of the nature and structure of being qua being
(content qua content)
ontologies:
Specific (theoretical or computational) artifacts expressing the intended meaning of a vocabulary in terms of primitive categories and relations describing the nature and structure of a domain of discourse
This talk will give an introduction to ontology in computer science, presenting the philosophical background, the theoretical or computational objects named ontologies and what they are useful for, as well as the methods of formal ontology that are sometimes used to design them.
Gruber: “Explicit and formal specifications of a conceptualization”

13. What is a conceptualization
The implicit rules used to structure reality as perceived and organized by an agent, independently of:
the vocabulary used
the actual occurence of a specific situation
Different situations involving same objects, described by different vocabularies, may share the same conceptualization.
apple
mela
same conceptualization LI LE

14. An example: the concept of red
a b
{a}
{b}
{a,b} {}

15. 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 (driven by actual needs)
(Language)
A set of atomic stimuli (input pattern) is received when the attention is focused on a phenomenon in a certain minimal region of spacetime (a single presentation)
Synchronic level: topological/morphological invariants within a single presentation
Unity properties are ascribed to input patterns: topological and morphological wholes (percepts) emerge
Diachronic level: temporal invariants across multiple presentations
Objects: equivalence relationships among percepts belonging to different presentations
Events: unity properties are ascribed to percept sequences belonging to different presentations

16. Intended models for each IK(L)
relevant invariants across situations: D, 
Conceptualization
State of affairs
Perceived situations
Perception
Reality
Phenomena
Bad
Ontology
Ontological commitment K (selects D’D and ’)
Language L
Models MD’(L)
Interpretations I
Mention Leo's talk
Ontology
~Good
Intended models for each IK(L)
Ontology models

17. Ontology Quality: Precision and Coverage
Good
Less good
High precision, max coverage
Low precision, max coverage
BAD
WORSE
Max precision, limited coverage
Low precision, limited coverage

18. Why precision is important Area of false agreement!
Possible interpretations of “apple”
Farmer’s ontology
Company’s ontology
What “apple” means for the farmer
What “apple” means for the juice company
Area of false agreement!

19. Ontologies and...

20. Levels of Ontological Precision
game
athletic game
court game
tennis
outdoor game
field game
football
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)
tennis
football
game
field game
court game
athletic game
outdoor game
Axiomatic theory
Taxonomy
game
NT athletic game
NT court game
RT court
NT tennis
RT double fault
Glossary
DB/OO scheme
Catalog
Thesaurus
Ontological precision

21. Ontologies and taxonomies
analytic relationships among terms!

22. 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

23. Ontologies vs. Database Schemas
Constraints focus on data integrity
Relationships and attribute values out of the DoD
Typically non-executable
Ontologies:
Constraints focus on intended meaning
Relationships and attribute values first class citizens
Typically executable

24. 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 a general enough basic categories and relations (primitives).
If basic assumptions are not made explicit, any imposed, common ontology risks to be
seriously mis-used or misunderstood
opaque with respect to other ontologies

25. 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
Idea of Chris Welty, IBM Watson Research Centre, while visiting our lab in 2000
The basis for a common ontology vocabulary

26. The semantic web architecture [Tim Berners Lee 2000]

27. 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

28. When is a precise (and well-founded) ontology useful?
When subtle distinctions are important
When recognizing disagreement is important
When careful explanation and justification of ontological commitment is important
When mutual understanding is more important than interoperability.

29. Role of ontologies in information architecture
Role of ontologies in information architecture (thanks to Dagobert Soergel)
Relate concepts to terms. Clarify their meaning by providing a system of definitions.
Provide a semantic road map and common conceptual reference tool across different disciplines, languages, and cultures
Make medical concepts clear to social science researchers and vice versa…
Improve communication. Support learning by helping the learner ask the right questions
Support information retrieval and analysis
Support the compilation and use of statistics
Support meaningful, well-structured display of information.
Support multilinguality and automated language processing
Support reasoning.

30. Conclusions In general, classifications are not ontologies
Some classifications are ontologies
Ontologies are needed to understand, integrate, reason on classifications
Every ontology induces a classification
Both ontologies and classifications are a fundamental tool for information architecture

31. A new journal: Applied Ontology
Editors in chief:
Nicola Guarino
ISTC-CNR
Mark Musen
Stanford University
IOS Press
Amsterdam, Berlin, Washington, Tokyo, Beijing