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

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

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

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.

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!

The source of all problems: different languages, different conceptualizations

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

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

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.

What is an ontology

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 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”

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

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

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

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

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

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!

Ontologies and...

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

Ontologies and taxonomies analytic relationships among terms!

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

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

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

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

The semantic web architecture [Tim Berners Lee 2000]

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

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.

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.

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

A new 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