Ontology-Driven Conceptual Modelling

Ontology-Driven Conceptual 

Modelling 

Summary 

Nicola Guarino 

Thanks to Giancarlo Guizzardi and the LOA people 

• Ontology and ontologies 

• What is an ontology 

• Ontologies and conceptual modelling 

• The role of formal ontology 

• Distinctions among properties 

• Ontology-driven design patterns 

• Taxonomy "cleaning" with OntoClean 

www.loa-cnr.it 

ADBIS 2005, Tallin, September 2005 2 

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 


1

Where subtle distinctions in meaning are 

important 

• Twin towers catastrophe: 

how many events? 

• US elections: how many holes? 

…only ontological analysis solves these problems!! 


Do we know what to REpresent? 

• First ontological analysis, 

• THEN conceptual modeling or knowledge 

representation… 

Unfortunately, this is not the current practice… 

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 


2

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 occurence of a specific situation 

• Different situations involving same objects, described by different 

vocabularies, may share the same conceptualization. 

L E 

L I 

Language L 

Tarskian 

interpretation I 

Intended 

models I K (L) 

apple 

mela 

same conceptualization 


Ontologies and intended meaning 

Conceptualization C 

(invariants across 

situations: D, ℜ) 

Ontological commitment K 

Models M D (L) 

Ontology 

Ontology models I K (L) 

Ontology Quality: Precision and Coverage 

Good 

High precision, max coverage 

BAD 

Max precision, limited coverage 

State of 

State of 

affairs Relevant 

affairs 

Situations 

Less good 

Low precision, max coverage 

WORSE 

Low precision, limited coverage 


3

Levels of Ontological Precision 

tennis 

football 

game 

field game 

court game 

athletic game 

outdoor game 

Catalog 

Glossary 

game 

athletic game 

court game 

tennis 

outdoor game 

field game 

football 

Taxonomy 

Ontological precision 

game 

NT athletic game 

NT court game 

RT court 

NT tennis 

RT double fault 

Thesaurus 

When precision is not enough 

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) 

DB/OO 

scheme 

Axiomatic 

theory 


Only one binary predicate in the language: on 

Only blocks in the domain: a, b, c, … 

Axioms (for all x,y,z): 

on(x,y) -> ¬on(y,x) 

on(x,y) -> ¬∃z (on(x,z) ∧ on(z,y)) 

Non-intended models are excluded, but the rules for 

the competent usage of on in different situations are 

not captured. 

a 

a 

c 

a 

b 

Excluded situations 

Precision vs. Accuracy 

c 

a 

c 

a 

Indistinguishable situations 

• In general, a single intended model may not discriminate 

among relevant alternative situations because of 

• Lack of primitives 

• Lack of entities 

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

ontology 

Precision: non-intended models are excluded 

Accuracy: non-intended situations are excluded 


c 

a 

4

Ontologies vs. Conceptual Schemas 

• Conceptual schemas 

• not accessible at run time 

• not always have a formal semantics 

• constraints focus on data integrity 

• attribute values taken out of the UoD 

• Ontologies 

• accessible at run time (at least in principle) 

• formal semantics 

• constraints focus on intended meaning 

• attribute values first-class citizens 


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 


Community-based Access vs. Global Knowledge 

Access 

different roles of ontologies 

• Community-based access 

• 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 

• 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) 


5

The Ontological Level 

(Guarino 94) 

Level Primitives Interpretation Main feature 

Logical Predicates, 

functions 

Epistemological Structuring 

relations 

Ontological Ontological 

relations 

Conceptual Conceptual 

relations 

Linguistic Linguistic 

terms 

Arbitrary Formalization 

Arbitrary Structure 

Constrained Meaning 

Subjective Conceptualization 

Subjective Language 

dependence 


The semantic web architecture [Tim Berners Lee 

2000] 

The problem of primitives 


• Representation primitives vs. ontological primitives 

(against arbitrary interpretations) 

• Formal ontology helps discovering general primitives, 

similarly to what happens in mathematics: set, 

relation, transitive, symmetric… 


6

Formal 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 

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 

An example: mereology 


• Primitive: proper part-of relation (PP) 

• asymmetric 

• transitive 

• Pxy = def PPxy ∨ x=y 

• Further axioms: 

supplementation: PPxy → ∃z ( PPzy ∧ ¬ z=x) 

principle of sum: ∃z ( PPxz ∧ PPyz ∧ ¬ ∃ w(PPwz ∧ ¬ (Pwx ∨ Pwy))) 

extensionality: x = y ↔ (Pwx ↔ Pwy) 

Excluded models: 

? 


7

OntoClean: 

useful distinctions among properties 

Essential properties and rigidity 

• Certain entities must have some properties in order to exist; 

• John must have a brain 

• John must be a person. 

• Certain properties are essential to all their instances (compare being a 

person with having a brain). 

• These properties are rigid - Their extension is the same in all possible 

worlds. If an entity is ever an instance of a rigid property, it must 

necessarily be such. 

Formal Rigidity 

• φ is rigid (+R): ∀x (pos φ(x) → nec φ(x)) 

• e.g. Person, Apple 


• φ is non-rigid (-R): ∃ x (pos φ(x) ∧ ¬ nec φ(x)) 

• e.g. Red, Male 

• φ is anti-rigid (~R): ∀ x (pos φ(x) → ¬ nec φ(x)) e.g. Student, Agent 

Meta-properties 


8

Sortals and other properties 

• Sortals (horse, triangle, amount of matter, person, student...) 

• Carry (non-trivial) identity conditions 

• Usually correspond to nouns 

• High organizational utility 

• Non-sortals (red, big, old, decomposable, dependent...) 

• No identity 

• Usually correspond to adjectives 

• Span across different sortals 

• Limited organizational utility 

• Categories (object, entity...) 

• No identity 

• Useful generalizations for sortals 

• Characterized by a set of (only necessary) formal properties 

• Good organizational utility 

Identity criteria 

• Classic formulation: 

• Generalization: 


φ(x) ∧ φ(y) → (ρ(x,y) ↔ x = y) 

φ(x,t) ∧ φ(y,t’) → (Γ(x,y,t,t’) ↔ x = y) 

(φ carries the identity criterion ρ) 

(synchronic: t = t’; diachronic: t ≠ t’) 

• In most cases, Γ is based on the sameness of certain characteristic 

features: 

• Non-triviality condition: 

Γ(x,y,t,t’) = ∀z (χ(x,z,t) ∧ χ(y,z,t’)) 

• Γ( x,y, t, t’) must not contain an identity statement between x and y! 

Carrying vs. Supplying Identity 


• Supplying (global) identity (+O) 

• Carrying an IC (or essential property) that doesn’t hold for all directly 

subsuming properties 

• Carrying identity (+I) 

• Not supplying identity, while being subsumed by a property that does. 

• Common sortal principle: x=y -> there is a common sortal supplying their 

identity 

• Theorem: only rigid properties supply identity 


9

Heuristics for Identity 

• Finding necessary and sufficient ICs for a given property may be very 

hard. 

• Heuristic 1: at least a sufficient IC. 

• Heuristic 2: some essential parts or qualities 

• Heuristic 3: some essential (non-rigid) properties 

Carrying essential properties 


• A property P carries a (relevant) essential property Q (different 

from P) iff Q is essential to all instances of P, and still Q is not 

rigid: 

• Every person must have a brain. 

• Compare with: 

• Every person must be a mammal. 

Unity, Identity, and Essence 

• Unity: is the collar part of my 

dog? 

• Being a topological 

whole is an essential 

property of my dog 

• Identity: is this my dog? 

• Essential properties allow 

us to keep track of my dog 

across time 

• Individual essential 

properties of my dog 

• Generic essential 

properties of dogs 



10

Unity as an essential property 

• A tentative formulation: x is a whole under a unifying relation U iff U is 

an equivalence relation that binds together all the parts of x, such that, 

necessarily, 

but not 

P(y,x) → (P(z,x) ↔ U(y,z)) 

U(y,z) ↔ ∃x(P(y,x) ∧ P(z,x)) 

• P is the part-of relation 

• U can be seen as a generalized indirect connection 

Kinds of Whole 


• Depending on the nature of U, we can distinguish: 

• Topological wholes (a piece of coal, a lump 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 

U) 

* Being a whole of a certain kind is an essential property: things cannot 

change their own unity conditions 

Unity Disjointness Constraint 


Classes with incompatible UCs are disjoint 

Example: Object and Matter 


11

Identity Disjointness Constraint 

ICs impose constraints on sortals, making their ontological 

nature explicit: 

Properties with incompatible ICs are disjoint 

Examples: 

• persons and passengers 

• sets vs. ordered sets 

• amounts of matter vs. assemblies 

Taxonomic Constraints 

• +R ⊄ ~R 

• -I ⊄ +I 

• -U ⊄ +U 

• +U ⊄ ~U 

• -D ⊄ +D 

Example - Identity 

• Is time-interval a subclass of timeduration? 

• Initial answer: yes 

• IC for time-duration 

• Same-length 

• IC for time-interval 

• Same start & end 


• Incompatible IC’s are disjoint 

• Incompatible UC’s are 

disjoint 


occurrent 

time-interval 

time-duration 


12

Examples of IS-A overloading 

1. A physical object is an amount of matter (Pangloss) 

2 An amount of matter is a physical object (WordNet) 

3. An association is a group (WordNet) 

4. A place is a physical object (µKosmos, WordNet) 

5. A country is a geographical region (WordNet) 

6. A window is both an artifact and a place (µKosmos) 

7. A person is both a physical object and a living thing (Pangloss) 

How ontological levels 

simplify taxonomies 

social-event 

mental-event 

physical-event 

social-event 

mental-event 

physical-event 

Sortal specialization 


communication-event 

perceptual-event 

communication-event 

perceptual-event 


• Type specialization (e.g. Living being → Person) 

• New features (especially essential properties) affect identity 

• Both necessary and sufficient ICs can be added while specializing types 

• Polygon: same edges, same angles 

• Triangle: two edges, one angle 

• Living being: same DNA, etc… 

• Zebra: same stripes... 

• Role specialization (e.g. Person → Student) 

• New features don’t affect identity 

• Types are rigid, roles are anti-rigid 


13

Roles are ‘dynamic’ and ‘antirigid’ 

Basic Idea (Steimann 2000): Roles have temporal/modal relations with 

their players 

• An entity can play different roles simultaneously 

• In 2003, B. was the Italian Prime Minister, the President of the 

European Union, the president of the Forza Italia party, the owner of 

the Mediaset company, an Italian citizen, a defendant at a legal trial. 

• An entity can cease playing a role (antirigidity) 

• In 1960, B. was a piano bar singer, now he is the IPM. 

• An entity can play the same role several times, simultaneously 

• In 2003, B. had two presidencies / was president twice. 

• A role can be played by different entities, simultaneously or at 

different times 

• Today, there are 4319 Italian National Research Council 

researchers. 

• In 2000, the Italian Prime Minister was D., now it is B. 

Roles have a relational nature 


• Basic Idea (Sowa, Guarino&Welty) 

Roles imply patterns of relationships, i.e., they depend—via 

these patterns—on additional ‘external’ properties 

• Which kind of dependence? 

• “Definitional” dependence (Fine 1995) avoids these 

problems: 

“to say that an object x depends upon an F is to say that an 

F will be ineliminably involved in any definition of x.” 

• with a non-internality condition added 


The dual nature of roles [Masolo et al 2004] 

• Basic Idea (Sowa 2000) 

Roles can be ‘predicated’ of different entities, i.e., 

different entities can play the same role 

• Standard representation 

Roles as properties 

• Social (and dynamic) aspects of roles not accounted 

for 

• Roles are created and disappear; are defined by 

conventions; are adopted and accepted by communities of 

agents 

• Roles need to be considered both as properties and 

“first-class citizens” 


14

What's the right model? [Steimann 2000] 

Customer 

Person Organization 

Person Organization Customer 

a 

The solution [Guizzardi 2005] 

«kind» 

Person 

«role» 

PrivateCustomer 


«roleMixin» 

Customer 

«kind» 

Social Being 

Organization 

«role» 

CorporateCustomer 


Another example solved with the same 

Ontology-Driven Design Pattern 

«kind» 

Person 

«roleMixin» 

Participant 

«kind» 

Social Being 

SIG 

«role» 

«role» 

IndividualParticipant CollectiveParticipant 


b 

15

Location 

Country 

Location 

+O-U-D+R 

Country 

+L+U-D~R 

Fruit 

A taxonomy cleaning example 

Physical object 

Apple 

Amount of matter 

Red apple 


+O+U-D+R 

Fruit 

+O+U-D+R 

Food 

Entity 

Living being 

Caterpillar 

Animal 

Entity -I-U-D+R 

Red 

Agent 

Legal agent 

Vertebrate 

Butterfly 

assign meta-properties 

Group 

Group of people 

Social entity 

Organization 

Person 

Remove non-rigid properties 


+O~U-D+R 

Red 

-I-U-D-R 

Agent 

-I-U+D~R 

Group 

+O~U-D+R 

Apple 

+O+U-D+R 

Red apple 

+I-O+U-D~R 

Food 

+I-O~U+D~R 

Living being 

+O+U-D+R 

Caterpillar 

+L+U-D~R 

Animal 

+O+U-D+R 

Butterfly 

+L+U-D~R 

Legal agent 

+L-U+D~R 

Vertebrate 

+I-O+U-D+R 


+I-O~U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 

16

Location 

+O-U-D+R 

Location 

+O-U-D+R 

Location 

+O-U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 



+O~U-D+R • ~U can’t subsume +U Group 

• Living being can change +O~U-D+R parts and 

remain the same, but amounts of 

Living being 

+O+U-D+R • 

matter can not (incompatible ICs) 

Living being is constituted Group of of matter people 

+I-O~U-D+R 

Apple 

+O+U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Animal 

+O+U-D+R 


Animal 

+O+U-D+R 

Analyze taxonomic links 

Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 



+O~U-D+R 

• 

• 

~U can’t subsume +U 

Group 

Living being can change parts and 

+O~U-D+R 

remain the same, but amounts of 

Living being 

+O+U-D+R • 

matter can not (incompatible ICs) 

Living being is constituted Group of of matter people 

+I-O~U-D+R 

Apple 

+O+U-D+R 


Animal 

+O+U-D+R 

Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 




• Physical objects can change +O~U-D+R parts 


+O+U-D+R 

Living being 

+O+U-D+R 

• 

and remain the same, but 

amounts of matter can not 

(incompatible ICs) Group of people 

Physical object is constituted +I-O~U-D+R of 

matter 

Social entity 

Fruit 

+O+U-D+R 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 

17

Location 

+O-U-D+R 

Location 

+O-U-D+R 

Location 

+O-U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 




• Physical objects can change +O~U-D+R parts 

and remain the same, but amounts 

Living being 

+O+U-D+R • 

of matter can not (incompatible ICs) 

Physical object is constituted Group of ofpeople 

matter 

+I-O~U-D+R 

Apple 

+O+U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Animal 

+O+U-D+R 


Animal 

+O+U-D+R 


Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 



+O~U-D+R • Meta-properties fineGroup 

• Identity-check fails: +O~U-D+R being alive 

is a contingent property for 

Living being 

+O+U-D+R 

• 

physical objects, and an 

essential property Group for animals of people 

+I-O~U-D+R 

Constitution again 

Apple 

+O+U-D+R 


Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 


+O~U-D+R Group 

+O~U-D+R 

Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Vertebrate 

+I-O+U-D+R 


+I-O~U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 

18

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 


Location 

+O-U-D+R • 


~U can’t subsume +O~U-D+R +U 

Group 

• A group can’t change parts - it 

+O~U-D+R 

becomes a different group 

Physical • A social object entity can change Living parts being - it’s 

+O+U-D+R 

more than just a group +O+U-D+R (incompatible 

IC) 


+I-O~U-D+R 

• Constitution again 

Location 

+O-U-D+R 

Location 

+O-U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Animal 

+O+U-D+R 



Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 


+O~U-D+R Group 

+O~U-D+R 


+O~U-D+R 

• ~R can’t subsume +R 

• Really want a type restriction: all 

agents are animals or social 

entities. 

• Subsumption is not disjunction! 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Vertebrate 

+I-O+U-D+R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Person 

+O+U-D+R 


+I-O~U-D+R 

Social entity 

-I+U-D+R 

Organization 

+O+U-D+R 

Person 

+O+U-D+R 

Analyze non-rigid properties 

Agent 

-I-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Organization 

+O+U-D+R 

19

Location 

+O-U-D+R 

Location 

+O-U-D+R 

Location 

+O-U-D+R 


+O~U-D+R 


• Another disjunction: all legal agents are 

persons or organizations 

Apple 

+O+U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 


+O~U-D+R 


• Another disjunction: all legal agents are 

persons or organizations 

Food 

+I-O~U+D~R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Caterpillar 

+L+U-D~R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Agent 

-I-U+D~R 

Person 

+O+U-D+R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Person 

+O+U-D+R 

Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Organization 

+O+U-D+R 


Agent 

-I-U+D~R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 

Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Organization 

+O+U-D+R 


Agent 

-I-U+D~R 


Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 

• Apple is not necessarily food. A poisonapple, 

e.g., is still an apple. 

• ~U can’t subsume +U 

• Caterpillars are wholes, food is stuff. 


+I-O~U-D+R 

Organization 

+O+U-D+R 

20

Location 

+O-U-D+R 

Location 

+O-U-D+R 

Food 

+I-O~U+D~R 


+O~U-D+R 

Apple 

+O+U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Caterpillar 

+L+U-D~R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Country 

+L+U-D~R Caterpillar 

+L+U-D~R 

Location 

+O-U-D+R 

Food 

+I-O~U+D~R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 


Agent 

-I-U+D~R 


Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 

• Apple is not necessarily food. A poisonapple, 

e.g., is still an apple. 

• ~U can’t subsume +U 

• Caterpillars are wholes, food is stuff. 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 


+I-O~U-D+R 

Organization 

+O+U-D+R 


• Identity check: a location can’t change parts… 

• 2 senses of country: geographical region and political entity. 

• Split the two senses into two concepts, both rigid, both types. 


+O~U-D+R 


There is Physical a relationship object between the 

two, but +O+U-D+R not subsumption. Living being 

Food 

+O+U-D+R 

+I-O~U+D~R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Geographical 

Country Region 

+L+U-D~R +O-U-D+R Caterpillar 

+L+U-D~R 

Animal 

+O+U-D+R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Organization 

+O+U-D+R 


Agent 

-I-U+D~R 

Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

21

• Caterpillars and butterflies cannot be 

vertebrate 

• There must a rigid property that 

subsumes the two, supplying identity 

across temporary phases 

Location 

+O-U-D+R 

Food 

+I-O~U+D~R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Geographical 

Region 

+O-U-D+R Caterpillar 

+L+U-D~R 

Location 

+O-U-D+R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Geographical 

Region 

+O-U-D+R Caterpillar 

+L+U-D~R 

Location 

+O-U-D+R 

Food 

+I-O~U+D~R 

Geographical 

Region 

+O-U-D+R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Lepidopteran 

+O+U-D+R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Lepidopteran 

+O+U-D+R 

Look for missing types 

Agent 

-I-U+D~R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Lepidopteran 

+O+U-D+R 

Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

Look for missing types 

Agent 

-I-U+D~R 

Social entity 

-I+U-D+R 

Person 

+O+U-D+R 

Legal agent 

+L-U+D~R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

The backbone taxonomy 

Vertebrate 

+I-O+U-D+R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

22

Location 

+O-U-D+R 

Food 

+I-O~U+D~R 

Geographical 

Region 

+O-U-D+R 

Location 

Country 

Location 

+O-U-D+R 


+O~U-D+R 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Red apple 

+I-O+U-D~R 

Physical 

object 

Fruit 

Caterpillar 

+L+U-D~R 


Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Lepidopteran 

+O+U-D+R 


Apple 

Food 

+I-O~U+D~R 

Geographical 

Region 

+O-U-D+R 

Red apple 

Food 


+O~U-D+R 

Agent 

-I-U+D~R 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 

Entity 

Living being 

Caterpillar 


+O+U-D+R 

Fruit 

+O+U-D+R 

Apple 

+O+U-D+R 

Red apple 

+I-O+U-D~R 

Red 

-I-U-D-R 

Caterpillar 

+L+U-D~R 

Red 

Animal Legal agent 


Vertebrate 

Butterfly 

Living being 

+O+U-D+R 

Animal 

+O+U-D+R 

Lepidopteran 

+O+U-D+R 

Legal agent 

+L-U+D~R 

Agent 

Social entity 

-I+U-D+R 

Vertebrate 

+I-O+U-D+R 

Agent 

-I-U+D~R 

Butterfly 

+L+U-D~R 

Person 

+O+U-D+R 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

Before 

Group 


Social entity 

Organization 

Person 

Legal agent 

+L-U+D~R 

After 

Group 

+O~U-D+R 


+I-O~U-D+R 

Country 

+O+U-D+R 

Organization 

+O+U-D+R 

23

An Interdisciplinary Approach 

• Towards a unified Ontology-driven Modelling Methodology for databases, 

knowledge bases and OO-systems 

• Grounded in reality 

• Transparent to people 

• Rigorous 

• General 

• Based on 

• Logic 

• Philosophy 

• Linguistics 

- Cognitive science 

Conclusions 


• Subtle meaning distinctions do matter 

• Properties and relations are not all the same 

• Formal ontological analysis helps introducing distinctions that make modeling 

assumptions clear 

• Helps resolving known conflicts 

• Helps recognizing unkown conflicts 

• Imposes constraints on standard modeling primitives (generalization, aggregation, 

association) 

• Elicits natural distinctions 

• …results in more reusable ontologies 

• A humble interdisciplinary approach is essential 

…Is this hard?! 

Of course yes! (Why should it be easy??) 


24

Applications of DOLCE (2) 

Core Ontologies 

based on DOLCE, D&S, and OntoWordNet 

• 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) 

Dependence 


• Between particulars 

• Existential dependence (specific/generic) 

• Hole/host, person/brain, person/heart 

• Historical dependence 

• Person/parent 

• Causal dependence 

• Heat/fire 

• Between universals 

• Definitional dependence 

• P depends on Q iff Q is involved in the definition of P. 

• Metaproperties: +D/-D 

A formal ontology of properties 

Property 

Sortal 

+I 

Non-sortal 

-I 

Role 

~R+D 

Non-rigid 

-R 


Rigid 

+R 

Category +R 

Attribution -R-D 

Formal Role 

Anti-rigid 

Material role 

~R Phased sortal -D 

Mixin -D 

Type +O 

Quasi-type -O 


25

DOLCE 

a Descriptive Ontology for Linguistic and Cognitive 

Engineering 

• Strong cognitive bias: descriptive (as opposite to 

prescriptive) attitude 

• Emphasis on cognitive invariants 

• Categories as conceptual containers: no “deep” 

metaphysical implications wrt “ true” reality 

• Clear branching points to allow easy comparison with 

different ontological options 

• Rich axiomatization 

• 37 basic categories 

• 7 basic relations 

• 80 axioms, 100 definitions, 20 theorems 

DOLCE’s basic taxonomy 

Endurant 

Physical 



Feature 

Non-Physical 

Mental object 

Social object 

… 

Perdurant 

Static 

State 

Process 

Dynamic 

Achievement 

Accomplishment 


Quality 

Physical 

Spatial location 

… 

Temporal 

Temporal location 

… 

Abstract 

Abstract 

Quality region 

Time region 

Space region 

Color region 

… 

… 


A representation of DOLCE’s upper levels 


26

Qualities and qualia 

• Linguistic evidence 

• This rose is red 

• Red is a color 

• This rose has a color 

• The color of this rose turned to brown in one week 

• Red is opposite to green and close to brown 

• The patient’s temperature is increasing 

• The doctor measured the patient's temperature 

• Each endurant and perdurant comes with certain qualities that permanently 

inhere to it and are unique of it 

• Qualities are perceptually mapped into qualia, which are regions of quality 

spaces. 

• Properties hold because qualities have certain locations in their quality spaces. 

• Each quality type has its own quality space 

Qualities 

The rose and the chair have the same color: 

• different color qualities inhere to the two objects 

• they are located in the same quality region 


Therefore,the same color attribute (red) is ascribed to the two 

objects 

Qualities 


Quality attribution Quality 

Quality space 

Rose Red-obj 

Color 

Rose1 

q-location 

Color of rose1 Red421 

Inheres Has-quale 

Color-space 

Red-region 

Has-part 

Has-part 


27

Qualities vs. Features 

• Featu res: “parasitic” physical entities. 

• rel evant parts of their host… 

… or places 

• Features have qualities, qualities have 

no features. 

Abstract vs. Concrete Entities 


• Concrete: 

• located (at least) in time 

• Abstract - two meanings: 

- Result of an abstraction process (something common to multiple 

exemplifications) 

∗ Not located in space-time 


Physical vs. Non-physical Objects 

• Physical objects 

• Inherent spatial localization 

• Not necessarily dependent on other objects 

• Non-physical objects 

• No inherent spatial localization 

• Dependent on agents 

• mental (depending on singular agents) 

• social (depending on communities of agents) 

• Agentive: a company, an institution 

• Non-agentive: a law, the Divine Comedy, a linguistic 

system… 

• Descriptions, an extension of DOLCE 


28

Endurants and Perdurants 

• Endurants (3D “objects”, e.g., a written text) 

• All proper parts are present whenever they are present 

(wholly presence, no temporal parts) 

• Exist in time 

• Can genuinely change in time 

• Need a time-indexed parthood relation 

• Perdurants (4D “eventualities”, e.g., an utterance) 

• Only some proper parts are present whenever they are 

present (partial presence,temporal parts ) 

• Happen in time 

• Do not change in time 

• Do not need a time-indexed parthood relation 

• Participation 

Physical vs. Non-physical Object 


FIAT SpA 

• Physical objects: 

• inherent spatial localization 

• not dependent on other objects (physical objects, like cars) or no 

inherent localization and be dependent on agents (non-physical 

objects, like laws and institutions). 

•Non-physical objects can also be divided into mental (depending on 

singular agents) and social (depending on communities of agents). 


29

Ontology-Driven Conceptual Modelling - Cs.ioc.ee

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