La prospettiva dell'
Ontologia Applicata
Nicola Guarino
(con il contributo di tutti i membri del LOA!)
www.loa-cnr.it
Le nuove tecnologie della conoscenza:
sempre piu' invisibili (e trasparenti?...)
• ambient knowledge, ubiquitous knowledge:
• La conoscenza e' dappertutto, distribuita, invisibile...
• I programmi che usiamo quotidianamente fanno assunzioni
sul mondo per noi misteriose
• Semantic interoperability
• ...eppure questi programmi comunicano sempre di piu' tra
loro, i dati vengono messi in comune...
• Applicazioni eterogenee comunicano fra di loro grazie al
fatto che la conoscenza e' interpretabile automaticamente
• Cio' non significa che i contenuti, le assunzioni implicite, il
vocabolario utilizzato siano comprensibili agli utenti finali.
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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Ecl@ss
UNSPSC, UCEC
Paper Materials &
14
Products
Semi finished
materials
35
Paper materials 10
Comm. Techn.
Office
Raw materials
15
24
Paper Pulp
Office Supplies
11
Office Supplies
(other)
Paper products
05
Writing paper
11
Printing & writing
15
paper
34
Writing Paper
Paper, film
Operating/cleaning
30
equipment
14
Printer paper
01
Personal Paper
Products
11
17
3
Paper Towels 54
Cleaning material 02
0
House office sanit.
cleaner
03
Office Equipment
44
Office Supplies
12
Desk Supplies
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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3
Staples
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La sfida della trasparenza cognitiva
• Obiettivo: comunicare, reperire, organizzare, condividere,
negoziare contenuti distribuiti.
• Complessa rete di interazioni che in ultima analisi riguarda
persone!
• Trasparenza cognitiva chiave della fiducia:
• Riguardo alle modalita' di interazione col mondo
• Riguardo alle assunzioni sul mondo
• Gli ingredienti base della comunicazione devono essere
espliciti, accessibili e cognitivamente adeguati:
• Le primitive concettuali
• Il vocabolario utilizzato
• Questo e' difficile ma (in buona misura) possibile attraverso un
approccio interdisciplinare basato sull'analisi ontologica
• L'infrastruttura sintattica viene dopo!
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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The importance of subtle distinctions
“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 many
subtle distinctions in terminology and meaning”
Harvard Business Review, October 2001
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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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
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Standard vocabularies are not the solution
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Defining standard vocabularies is difficult and timeconsuming
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
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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 artifact expressing the intended meaning of a
vocabulary in terms of the nature and structure of the
entities it refers to
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Ontologies and intended meaning
State of
State of
affairs
affairs
Situations
Conceptualization C
(relevant invariants across
situations: D, )
Language L
Tarskian
interpretation I
Intended
models IK(L)
Ontological commitment K
Models MD(L)
Ontology
Ontology models IK(L)
Ontology Quality: Precision and Coverage
Good
High precision, max coverage
Less good
Low precision, max coverage
BAD
Max precision, limited coverage
WORSE
Low precision, limited coverage
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Why precision is important
MD(L)
Area
of false
agreement!
IB(L)
IA(L)
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Levels of Ontological Precision
tennis
football
game
field game
court game
athletic game
outdoor game
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)
game
athletic game
court game
tennis
outdoor game
field game
football
Taxonomy
Glossary
Catalog
game
NT athletic game
NT court game
RT court
NT tennis
RT double fault
Thesaurus
Axiomatic
theory
DB/OO
scheme
Ontological precision
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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)
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Why formal?
• Two meanings: rigorous and general
• Formal logic: connections between truths - neutral wrt truth
• Formal ontology: connections between things - neutral wrt reality
Basic theories
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• Theory of Essence and Identity
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Theory of Parts (Mereology)
Theory of Wholes
Theory of Dependence
Theory of Composition and Constitution
Theory of Properties and Qualities
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Identity, Unity, and Essence
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Identity: is this my dog?
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Essential properties of dogs
Essential properties of my dog
Unity: is the collar part of my
dog?
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Being a whole (of a certain kind)
is also an essential property
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Kinds of Whole
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Depending on the nature of the unifying relation, we can distinguish:
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Topological wholes (a piece of coal, a heap of coal)
Morphological wholes (a constellation)
Functional wholes (a hammer, a bikini)
Social wholes (a population)
a whole can have parts that are themselves wholes (with a different
unifying relation)
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The rich ontology of Natural Language
Multiple co-located objects
• I am talking here
• *This bunch of molecules is talking
• *What’s here now is talking
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This statue is looking at me
*This piece of marble is looking at me
This statue has a strange nose
*This piece of marble has a strange nose
Multiple co-located events
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John sings while taking a shower
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Ontology: an overloaded term
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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Ontologies vs. Knowledge Bases
• Knowledge base
• Assertional component
• reflects specific (epistemic) states of affairs
• designed for problem-solving
• Terminological component (ontology)
• independent of particular states of affairs
• Designed to support terminological services
Ontological formulas are (assumed to be)
necessarily true
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Ontology and semantics
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Strictly intertwined: ontology is about what there is, semantics is about
referring to what there is...
Structural semantics vs. referential semantics
Different aspects of language, different roles of ontology
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Complex sentences (conjunctions, conditionals...)
Primitive sentences (predication)
Quantifiers and modifiers
Prepositions
Nouns and verbs
Discourse structure
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Cosa facciamo...
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Foundational issues
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Ontology and natural-language semantics
Formal semantics of discourse and dialogue relations
Ontology and lexical resources
Ontology learning techniques and their evaluation
Conceptual schemas, perceptual invariances, categorization
Ontology-driven information systems
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Basic ontological categories and relations
Formal comparison and evaluation of ontologies
Ontology, epistemology, and semiotics
Ontology, language, cognition
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Come lo facciamo
Methodologies for ontology development
Ontology-driven conceptual modeling
Best practice examples and case studies
Ontology-driven information integration & (multimedia) access
Semantic Web
Application domains
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Biomedicine
Agents and actions
Organizations, social reality, law
Space and geography
Industrial artifacts and manufacturing
Business and e-government
Food and agriculture
Cultural heritage
www.loa-cnr.it
Conclusions
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First ontological analysis,THEN conceptual modeling or knowledge
representation…
Subtle meaning distinctions do matter
General ontological primitives help making intended meaning explicit
Realizing reasons of disagreement may be more important than forcing
agreement
A humble interdisciplinary approach is essential
…Is this hard?!
Of course yes! (Why should it be easy??)
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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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
Ontologie umanistiche, Firenze, 27 Gennaio 2006
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Applications of DOLCE
Core Ontologies
based on DOLCE, D&S, and OntoWordNet
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Core ontology of plans and guidelines
Core ontology of (Web) services
Core ontology of service-level agreements
Core ontology of (bank) transactions (anti-money-laundering)
Core ontology for the Italian legal lexicon
Core ontology of regulatory compliance
Core ontology of fishery (FAO's Agriculture Ontology Service)
Core ontology of biomedical terminologies (UMLS)
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A Selection of Most Relevant Projects (2003-2006)
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WonderWeb (FP5): Ontology Infrastructure for the Semantic Web (LOA: foundational ontologies for the
Semantic Web)
OntoWeb (FP5 - NoE): Ontology-based information exchange for knowledge management and electronic
commerce (LOA: SIG on Content Standards)
METOKIS (FP6): Methodologies and tools infrastructure for the development of multimedia knowledge
units
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SEMANTIC MINING (FP6 - NoE): Semantic Interoperability and Data Mining in Biomedicine
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TICCA (PAT&CNR): Tecnologie cognitive per l'interazione e la cooperazione con agenti artificiali
(LOA: ontology of social interaction)
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MOSTRO (PAT); Modelling Security and Trust Relationships in Organizations
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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)
FOS (UN/FAO): Alignment of legacy fishery ontologies
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NEON (FP6) - Networked Ontologies
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ONTOGEO (FP6) - Geo-spatial Semantic Web
La varieta' delle applicazioni
dimostra la generalita' del metodo
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The semantic web architecture [Tim Berners Lee
2000]
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
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Community-based Access vs. Global
Knowledge Access
different roles of ontologies
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Community-based access
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Intended meaning of terms known in advance
Taxonomic reasoning is the main ontology service
Limited expressivity
On-line reasoning (stringent computational requirements)
Global knowledge access
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Negotiate meaning across different communities
Establish consensus about meaning of a new term within a community
Explain meaning of a term to somebody new to community
Higher expressivity required to express intended meaning
Off-line reasoning (only needed once, before cooperation process starts)
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Ontologies vs. Conceptual Schemas
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Conceptual schemas
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not accessible at run time
not always have a formal semantics
constraints focus on data integrity
attribute values taken out of the UoD
Ontologies
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accessible at run time (at least in principle)
formal semantics
constraints focus on intended meaning
attribute values first-class citizens
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