1.
Ontologies for Urban Systems
Caglioni Matteo
Rabino Giovanni
University of Pisa
Department of Civil Engineering
Polytechnic of Milan
Department of Architecture and Planning

2.
Contents
 What is an ontology:
 Definition
 Features
 Softwares
 Ontologies in geography and planning: a survey
 2 applications:
 A light ontology: alterogeographies
 A reseach work: ontology and modelling

3.
Definition of Ontology
“An ontology is
a formal and explicit specification
of a shared conceptualization”
(Studer, 1998)
Slide 01 di 29

4.
Formal language
 Natural languages aren’t able to describe in a
powerful way concept definitions and
relationships.
 Syntactical machine readable languages
such as HTML or XML are limited because
they are only intended for human consumption.
Slide 02 di 29

5.
 We need to make the information not only
machine readable but machine-understandable.
 In order to gain machine understanding we
need semantic languages which are able to
define meaning for the stored information.
Slide 03 di 29
Formal language

6.
 Requirements for an ontology language
– Easy to use and comprehend
– Compatible with existing standards
– Formally specified
– Adequately expressive
– Possibility to perform an automate reasoning
Slide 04 di 29
Formal language

7.
 OIL (Ontology Inference Layer)
 DAML (DARPA Agent Mark-up Language)
 DAML+OIL
 OWL (Ontology Web Language)
– OWL lite (First Order Logic)
– OWL DL (Descriptive Logic)
– OWL Full
Slide 05 di 29
Formal language

8.
Shared and reusable ontologies
 Ontology building is an iterative process
characterized by an high cost.
 There are databases with ontologies already
developed, but these resources are limited.
 Formal structure and formal language allow to
re-use an ontology in another application.
 Re-using ontologies allows to share knowledge
contained inside them.
Slide 06 di 29

9.
The object
 physical object, which are entities limited in
space and in time.
 social object, which are entities just limited in
time (i.e. a contract, or a promise)
 ideal object, which are entities not limited in
space and in time.
(Casati, 1998; Ferraris, 2005; Varzi 2005)
Slide 07 di 29

10.
Semantic relationships
 The most common way to represent objects in
an ontology is using semantic relationships
among concepts, which give a hierarchical
structure to the whole system.
Slide 08 di 29

11.
 Taxonomy (Hiperonomy, Hiponomy)
X is a kind of Y (o Y has a kind of X).
characterize relationship between classes and subclasses,
where subclasses inherit all proprieties of the their class (flat,
detach house, cinema, theatre are kinds of buildings).
 Partonomy (Meronimy, Olonimy)
X is a part of Y (o Y has a part X).
the sum of parts of an object constitute the object itself
(window, door, roof are parts of a house).
Slide 09 di 29
Semantic relationships

12.
 Semantic relationship between verbs
– Toponimy: a verb is a troponym of another one,
when the first expresses a particular manner of the
second (march - walk).
– Implication: an action implies another one, when the
first action can’t be performed without to perform also
the second (snore - sleep).
Slide 10 di 29
Semantic relationships

13.
 Lexical relationships are important relations
between concepts that depend by phrases in
which they are
– Synonymy: two concepts are synonyms, if
substituting one concept with the other one inside a
phrase, the value of truth of phrase doesn’t change.
– Antinomy: the antonym (or contrary) is a concept
having a meaning opposite to that of another concept.
– Polysemy: the polysemous is a concept with more
than one meaning.
Slide 11 di 29
Semantic relationships

14.
 Semantic relationships are easy to use, also
because we already know their proprieties and
their formal representation…
 …there are other kinds of relationships we can
add to an ontology, but we need to define them
and characterize them in a formal way.
Slide 12 di 29
Semantic relationships

15.
<detach house, artefact, flat, garden, construction, building, structure,
bridge, antropic object>
Slide 13 di 29
Words list {antropic object}
{building}
{garden}{structure, costruction}
{artefact}
{flat} {detach house}
Structured dictionary{bridge}
Semantic relationships

16.
1 define theory: buildings
2 define class: building(x)
a instance-of(White House,building)
b instance-of(Louvre,building)
c instance-of(Scala,building)
3 define relationship: kind-of(x,b)
a kind-of(theatre,building)
b kind-of(hospital,building)
c kind-of(house,building)
4 define relationship: constitute-by(b,x)
a constitute-by(building,doors)
b constitute-by(building,windows)
c constitute-by(building,walls)
Slide 14 di 29
Semantic relationships

17.
1 define theory: buildings
2 define class: building(x)
3 define relationship: made-of(e,material)
a ∀ e,m: made-of(e,m) -> instance-of(e,building) & (m = concrete or m = steel)
4 define relationship: kind-of(e,structure)
a kind-of(e,steel) ↔ instance-of(e,building) & made-of(e,steel) & ¬ made-of(e,concrete)
b kind-of(e,con) ↔ instance-of(e,building) & made-of(e,concrete) & ¬ made-of(e,steel)
c kind-of(e,r_con) ↔ instance-of(e,building) & made-of(e,concrete) & made-of(e,steel)
Slide 15 di 29
Semantic relationships

18.
Ontology and representation
Slide 16 di 29
Top Level Ontology
Generic Ontology
Generic Ontology
Functional level Domain level

19.
Software for ontology (freeware)
 Towntology: developed by Laurini, Laboratoire d'InfoRmatique en
Image et Systèmes d'information INSA. This software contains
several specific libraries about urban field. It uses XML language.
 Protégé: developed by Stanford Medical Informatics at the
Stanford University School of Medicine. It’s a general ontology
editor with several plug-in. It uses OWL language.
 CmapTools COE: integrated suite of software tools for
constructing, sharing and viewing OWL encoded ontologies based
on CmapTools.
Slide 00 of 00

20.
Urban ontologies
 Urbamet thesaurus: lightweight ontology, it’s purpose is to
describe document about urbanism, city planning, construction,
architecture and so one http://www.urbamet.com/doc/bd.htm the
interface to query the documentation database using the urbamet
thesaurus.
 URBISOC thesaurus: lightweight ontology, it’s purpose is a
classification in bibliographic databases (scientific and technical
journals on Geography, Town Planning, Urbanism and
Architecture)
 Mobility ontology : lightweight ontology for teaching and
communication in transportation field.
Slide 00 of 00

21.
Urban ontologies
 GEMET thesaurus: lightweight ontology, for classification of
environmental resources.
 EUROVOC thesaurus: lightweight ontology, for classification of
documents produced by European institutions.
 UNESCO thesaurus: lightweight ontology for classification of
documents in the fields of education, science, social and human
science, culture, communication and information.
 AGROVOC thesaurus: lightweight ontology for classification of
geographic information resources (with special focus on agriculture
resources)
Slide 00 of 00

22.
L. D. Hopkins(2001):
Urban Development: The logic of making Plans.

23.
L. D. Hopkins(2001):
Urban Development: The logic of making Plans.

24.
b
Socially relevant
development issue
c
System knowledge
a
Action domain
Observable
(workable
sustainability
definition) 1
Abstractions
4
Model of the 2
observable Mental models
3
Knowledge levels of the observable
Model domain Model structure
Purpose of the model Urban actors and activities
Analytical perspectives Allocation and spatial patterns
Observation, information Drive of spatial processes
User interface and evolution
Links belonging to the external loop
Links belonging to the internal loop
Elements more sensitive to simulation
The
modelling
process

25.
Model building levels
Slide 17 di 29
Mental Map
Conceptual Map
Ontology
Qualitative Model
Fuzzy Model
Quantitative Model
Cognitive Map
↓
↓
↓
↓
↓
↓
mathematical, deterministic, probabilistic

26.
 It’s possible to identify an isomorphism between
concepts in an ontology and entities in a
model…
 …also between relationships, defined and
represented in an ontology, and equations
which connect different entities using a
mathematical form.
Slide 23 di 29
Urban ontology

27.
 To build an ontology following a top-down
process is an ambitious and rather complex
project…
 we purpose to start from already existing
mathematical models, building an ontology
through a generalization process.
Slide 27 di 29
The Lowry Model

28.
Slide 28 di 29
d2
x1(t+∆t)/dt2
= k1(dx2(t)/dt – dx1(t)/dt)
Differential equations for vehicle movement
The Model

29.
Slide 28 di 29
Flux Road
Vehicle
Human being
Position
Velocity
Administration
Speed limits
The ontology

30.
 The Lowry model was one of the first transportation /
land use model to be developed in 1964.
 Even if its formulation is rather simple, it provides the
relationships between transportation and land use.
 The core assumption of the Lowry model assumes that
regional and urban growth (or decline) is a function of
the expansion (or contraction) of the basic sector.
Slide 26 di 29
The Lowry Model

31.
 According with our systemic view of the city,
we propose to represent an ontology using a
classic input-output structure of the urban
system.
Slide 24 di 29
Urban ontology

32.
Slide 28 di 29
Transportation
Residence
Population
Services
Land use
Economy
Workplace
The Lowry Model

33.
Slide 25 di 29
The Lowry Model

34.
Conclusions
 It’s possible to extract knowledge through
logical inference (reasoning).
 Ontology as method to build a database
and to share information.
 Ontology as model building process for urban
systems.
Slide 29 di 29