building a pre-design ontology
DESCRIPTION
his study is concerned with the formulation of solutions for urban problems. It departs from Alexander’s pattern language theory and from a series of urban design guidelines, to create a system for generating specifications or the ingredients of a plan, given a scale, a site and a community. It takes into account strategies, regulations, guidelines, physical features of the site, and furthermore, the social, cultural and economic characteristics of the population.TRANSCRIPT
UNIVERSIDADE TÉCNICA DE LISBOA
FACULDADE DE ARQUITECTURA
Building a Pre-Design Ontology Towards a model for urban programs
DISSERTAÇÃO PARA OBTENÇÃO DO GRAU DE MESTRE EM REGENERAÇÃO URBANA E AMBIENTAL
Orientador Científico:
Doutor José Manuel Pinto Duarte Co-orientador Científico:
Doutor George Stiny
Jurí: Presidente: Doutor Luís António dos Santos Romão Vogais: Doutor João Altino Serra de Magalhães
Doutor José Manuel Pinto Duarte Doutor George Stiny
Lisboa, Junho de 2010
Nuno Filipe Santos de Castro Montenegro (Licenciado)
building a pre-design ontology: towards a model for urban programs
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building a pre-design ontology: towards a model for urban programs
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Nuno Filipe Santos de Castro Montenegro
Departamento: Urbanismo
Orientador Científico: Professor Doutor José Manuel Pinto Duarte
Data: Junho de 2010
TÍTULO
Uma Ontologia para Planeamento1: Contributo para um modelo de programas urbanos
RESUMO
O objectivo deste estudo é a formulação de soluções para problemas urbanos. O estudo parte
da teoria da linguagem padrão de Christopher Alexander e de um conjunto de informações
relativas a regulamentos e recomendações aplicáveis ao planeamento urbano, para elaborar
um sistema que gera as especificações ou os ingredientes de um plano; dada uma escala, um
local e uma comunidade específicos. O sistema apoia-se num conjunto de dados necessários
ao plano, designadamente estratégias, regulamentos, características físicas do local e
socioeconómicas da população. O sistema inclui a classificação e a organização desses dados
através de uma sequência de eventos, fases, categorias, métodos e utilizadores. O objectivo é
descrever os níveis taxonómicos do sistema e as relações de interdependência entre as
entidades que compõem o referido sistema. Essa ontologia permitirá fornecer, em
investigações futuras, uma estrutura pré-codificada para viabilizar a sua aplicação num modelo
computacional, apoiada no modelo espacial SIG (Sistema de Informação Geográfica). O modelo
de formulação urbana é essencialmente concebido para incrementar índices de qualidade,
reduzindo ambiguidades, e permitindo administrar o planeamento urbano através de um
processo mais flexível e automático.
Palavras-chave: Planeamento urbano, Ontologias, Linguagem Padrão.
1. Planeamento no contexto desta investigação está relacionado com a ferramenta administrativa que normalmente ocorre numa fase anterior ou simultânea ao desenvolvimento do desenho de um plano urbano, permitindo a interpretação de uma dada realidade urbana existente ou desejada, de forma a avalia-la e a estruturar percursos adequados para a implementação. Trata-se de um processo de deliberação que escolhe e organiza acções, antecipando resultados esperados. De acordo com o conceito defendido por Peter Drucker (2007) existem dois critérios indispensáveis ao planeamento: eficácia e eficiência. A eficácia é o critério mais importante, já que nenhum nível de eficiência, por mais alto que seja, compensa a má escolha dos objectivos do planeamento, isto é, a eficiência no desempenho das actividades de implementação de um plano sobrepõe-se a eventuais falhas na definição dos objectivos da sua organização.
building a pre-design ontology: towards a model for urban programs
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Nuno Filipe Santos de Castro Montenegro
Department: Urbanism
Supervisor: Professor Doutor José Manuel Pinto Duarte
Date: June 2009
TITLE
Building a Pre-Design Ontology: Towards a model for urban programs
ABSTRACT
This study is concerned with the formulation of solutions for urban problems. It departs from
Alexander’s pattern language theory and from a series of urban design guidelines, to create a
system for generating specifications or the ingredients of a plan, given a scale, a site and a
community. It takes into account strategies, regulations, guidelines, physical features of the
site, and furthermore, the social, cultural and economic characteristics of the population. This
system, organised according to a sequence of events, through stages, categories, methods and
agents, describes taxonomic levels and their inner relations. Such ontology will provide, in
future research, a pattern encoding structure towards a computational model within the
capabilities provided by the spatial data modelling of GIS (Geographic Information System).
The urban formulation model is conceived to increase qualitative inputs, reducing ambiguities,
through a flexible while automated process applied to urban planning.
Keywords: Urban Planning, Ontology, Pattern Language.
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The author owns any copyright© in this thesis and has given the “Technical University of Lisbon, TULisbon” the right to use such Copyright for any
administrative, promotional, educational and/or teaching purposes. Copies of this thesis, either in full or in extracts, may be made only in accordance
with the regulation of the Faculty of Architecture (FAUTL). The ownership of any patents, designs, trademarks and any and all other intellectual
property rights except for the Copyright (the “Intellectual Property Rights”) and any reproductions of copyright works, for example graphs and tables
(“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual
Property Rights and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the
relevant Intellectual Property Rights and/or Reproductions.
Cover figure: Pre-design ontological classes and slots sketched in the VizTab of the Protégé 2000 editor.
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1.1. Contents
1.1. Contents vi
1.2. List of diagrams viii
1.3. List of tables and figures ix
1.4. Acknowledgements x
1.5. Preface xii
Chapter 1 14
Introduction 14 1
1.6. Introduction 1
1.7. Research context 1
1.8. Problem Definition 2
1.9. Proposed methodology 4
1.10. Concerns involving the creation of the formulation model 6
1.11. Expected outcomes and future work 8
1.12. Organization 10
Chapter 2
Precedents 14
2.1 Introduction 15
2.2 The precedents 15
2.3 Conclusion 20
Chapter 3 23
Methodology 23
3.1. Introduction 24
3.2. Adopted methodology 24
3.3. Ontologies within computer science - (AI) Artificial Intelligence 26
3.4. Ontology Interoperability 27
3.5. Representation of ontologies 27
3.6. Editing ontologies 29
3.7 Comparing ontology editors: Ontolingua and Protégé 32
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Chapter 4 36
Conceptual and Formulation Models 36
4.1. Introduction 37
4.2. The conceptual model 37
4.3. The formulation model 40
Chapter 5 49
The Formulation Process 49
5.1. Introduction 50
5.2. Operational structure of the formulation process 50
5.3. The formulation phases 52
5.4. Categories enclosing the main processes of the pre-design phase 53
5.5. Strategies 54
5.6. Regulations 59
5.7. Site and population context 62
5.8. Document synthesis 70
5.9. Planner’s Language – pattern language 71
Chapter 6 75
The Sketch of a Planning Language 75
6.1. Introduction 76
6.2. The nature of language 76
6.3. Semantics and Syntax 77
6.4. Planners and Language processing 80
6.5. Lexicon 82
6.6. Pattern Language 84
6.7. Urban Pattern Language Sketch (UPL) 93
6.8. The UPL Ontology 93
6.9. The UPL Syntax and Core Components 94
6.10. The UPL lexicon 100
6.11. The UPL Semantics 104
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6.12. Conclusion 112
Chapter 7 114
Conclusion 114
7.1 The Context
7.2 The Problem
7.3 The goal
7.4 The model
7.5 The outcome
7.6 Reflexions for future research
7.7 The opportunity
Glossary 120
References 134
Annexes 145
1.2. List of diagrams
1. Basic process of interaction among the three partial modules of the CI project .......................... 1 2. Change of planning paradigms along time ................................................................................. 3 3. The core matters of the research ............................................................................................... 4 4. Basic diagram: conceptual outline ............................................................................................. 6 5. Formulation research outline……………………………………………………………………..………….. ................. 10 6. Basic diagram: conceptual outline ........................................................................................... 13 7. The core matters of the research (2) ........................................................................................ 13 8. The main laws of urban programs ............................................................................................ 22 9. Example of an urban pattern top level ontology (see Pinho & Goltz)......................................... 29 10. Protégé edition of a climatic pattern........................................................................................ 31 11. The visualization tab of the cold region edited by the Protégé editor ........................................ 31 12. Ontological class hierarchy of the climatic patterns .................................................................. 32 13. Methodology framework…………………….. .................................................................................. 35 14. Duarte’s model (discursive grammar for housing) (Duarte 2007) (Stiny 1981), (Pedro 2001a)
and (Stiny & Gips 1972)………………. .......................................................................................... 38 15. The conceptual model of the urban formulation process (FMo)................................................ 38 16. The urban formulation ontology (Montenegro, N. and Duarte, J, 2008) .................................... 44 17. PD classes, subclass-superclass hierarchy, slots and instances, and the Protégé VizTab ............. 47 18. Urban formulation process (FMo) ............................................................................................ 48 19. A planning schedule………………….. ............................................................................................ 51
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20. Pre-design phases – the PD1 (data acquisition) and the PD2 (data translation) ......................... 53 21. The four categories of the formulation process ........................................................................ 54 22. SWOT analysis - the strengths, the weaknesses, the opportunities, and the threats. ................. 57 23. Strategies shown in the simplified diagram . ............................................................................ 59 24. Regulations and codes shown in the simplified diagram . ......................................................... 61 25. Site and population contextual data shown in the simplified diagram . ..................................... 70 26. Pattern language “specifications for design” shown in the simplified diagram .......................... 73 27. The four different categories of the formulation process. ......................................................... 74 28. Language processing………………….. ........................................................................................... 79 29. The ontological diagram of an urban pattern (Montenegro, N.C. and Duarte, J.P., 2008) ........... 83 30. An example of Pattern’s taxonomy (the created links between patterns).................................. 88 31. Syntax class hierarchical tree (above left), exported piece of XML Schema, CPL diagram
classes, subclass-superclass hierarchy, and slots, CPL diagram zoom ........................................ 99 32. UML diagram of the top level class hierarchy (CityGML) ......................................................... 103 33. The core structure of the CPL………… ...................................................................................... 113 34. Syntax class hierarchical tree, exported piece of XML Schema, CPL diagram classes, subclass-
superclass hierarchy, and slots, CPL diagram zoom (2). .......................................................... 160
1.3. List of tables and figures
1. Benefits of design regulations (Evans et al. 2007) ..................................................................... 60
2. Gate Counter Map and Observation sheet example (Space Syntax). ......................................... 68
3. Participants in the planning process (Evans et al. 2007) – part 1 ............................................... 72
4. Participants in the planning process (Evans et al. 2007) – part 2 ............................................... 72
5. Active drawing phase during the design (Lindekens 2004) ........................................................ 81
6. An example of a CityGML code list for city objects (City GML) ................................................ 103
7. Table with Guterres social patterns (Guterres 2004). ............................................................. 106
8. Form and proportions of buildings in different regions (Olgyay 1963) ..................................... 108
9. Design rule formalization on Protégé Axiom Language (Trento 2009) ..................................... 146
10. Class edition on Protégé 2000………………………………………………………………..……………………………….147
11. PEST analysis (Chapman 2005)………. ...................................................................................... 154
13. Attributes applicable to urban formulation (Gil et al 2009) .................................................... 159
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1.4. Acknowledgements
The author would like to express particular gratitude to José P. Duarte, supervisor of this
dissertation, for the interest, accuracy, and furthermore a high regard for his scientific depth of
outstanding relevance.
The author is also thankful to the City Induction project team members, José N. Beirão
(TULisbon2/TUDelft3) and Jorge Gil (SpaceSyntax4/TUDelft), through the City Induction project 5
(PTDC/AUR/64384/2006), for the engaging discussions and valuable comments during the
development of the research.
I dedicate this thesis in memory of my father
2. http://www.moveonnet.eu/directory/institution?id=PTLISBOA04 3 . http://www.tudelft.nl/ 4 . http://www.spacesyntax.com/
5 . The project PTDC/AUR/64384/2006 was funded by Fundação para a Ciência e Tecnologia and hosted by ICIST (FCT).
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Good planning is good urban design (Evans et al. 2007)
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1.5. Preface
When, in 2006, Jorge Rocha6 encouraged me to submit a research project on ontologies7 for
funding purposes, I was far from realizing the dimension the challenge that this step implied.
I started my research in urban planning during the Urban Regeneration Master Program
at the Technical University of Lisbon (TU Lisbon) where, by a gentle suggestion of Leonel
Fadigas8, Jose P. Duarte9 accepted to supervise my research, introducing me to a wider
framework then I initially expected. This reality delayed the elaboration of the study, but it has
also provided a deeper research context. In fact, Jose P. Duarte brought up a unique
experience consolidated at MIT10, today widely recognized by the international community as
a hub for the application of technologies to the field of architecture.
Based on his own experience, Duarte proposed me to develop an ambitious project
inspired in his work (Duarte 2007). The idea was simple and innovative: to create, in a similar
way to the one he had devised for mass customized housing (Duarte 2003), a system for
generating design proposals based on contextual criteria, but this time focusing on flexible
urban plans. As in the system that Duarte invented for housing, it was necessary to create a
structure involving three interdependent modules; one to formulate the urban program, one
to generate spatial solutions, and another one to evaluate solutions according to
programmatic criteria. Part of such a process, applied to the urban context, has already been
tested by Beirão and Duarte (2005) with students from TU Lisbon. The pioneering experience
was followed by the presentation of an article at the eCAADe conference in the same year
(eCAADe 2005).
This overall context led to the creation of the City Induction research project (CI), being
the development of the formulation model - one of the project modules - my core task.
Although some papers have already been published and presented at international
conferences on this matter (Montenegro & Duarte 2008) (Montenegro & Duarte 2009), and on
6 . Jorge Rocha is a geographer, and lecturer assistant at the University of Lisbon (UL), Portugal. 7 . Ontology consists in the selected methodology of this research, and is described in the 3
rd chapter. Moreover an ontology is a
data model that helps to support the development of the urban formulation model by providing a common vocabulary for users who need to share information in this specific domain. 8. Leonel Fadigas is an urban planner, landscape architect, and professor at the Technical University of Lisbon (TUL) , Portugal. Fadigas is the coordinator of the Urban Regeneration Master at the same university. 9 . José P. Duarte is an architect, scientist researcher, and professor at the Technical University of Lisbon (TUL), Portugal. Duarte is the coordinator of the City Induction project. His CV is available at: http://home.fa.utl.pt/~jduarte/ 10. The Massachusetts Institute of Technology (MIT) is a private research university located in Cambridge, Massachusetts. USA.
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related topics in collaboration with other of the project’s team members (Gil et al 2009)
(Beirão et al 2009), this study comprises a wider research effort on the formulation field.
More precisely, this work corresponds to a first volume that attempts to frame the
context of the urban formulation model by providing its basic ontology. A further volume will
be dedicated to the future implementation of such a model.
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This chapter describes the context,
the problem, and the expected
outcome of the research - The
formulation model and the definition
of its basic ontology.
Chapter 1
1. Introduction
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formulation urban
programsevaluation generation
designevaluation urban plans
sustainable
1.6. Introduction
This first chapter describes the context, the problem, and the expected outcome of the
research.
1.7. Research context
As previously mentioned, the present study evolved simultaneously to the development of the
City Induction project: a model to formulate, evaluate and generate urban plans. This R&D
project aims at the integration of models areas within urban research; the urban formulation
model, the urban evaluation model and the urban generation model. The basic idea is to
create a full system to generate sustainable11 urban plans12.
The interoperability of such system comprises the elaboration of a common ontology (a
language13 based on ontological descriptions further explained in the 3rd chapter), which will
provide the recursive tool used by the partial models to produce integrated results.
This dissertation concerns a CI partial model: the formulation model14 and the definition
of its basic ontology - a knowledge modelling structure15 to support the development and the
management of urban programs.
Such context helps to clarify the mission of the study.
1. The diagram depicts the basic process of interaction among the three partial modules of the CI project.
However, the CI full model foresees more complex types of interaction.
11. A generally accepted definition of sustainability is described by ‘(…) the development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs’. This definition has three key ideas: development, needs and future generations (Moughtin et al. 2003). 12. The model will be applied at a neighborhood scale, setting a vision for an urban extension at the site scale or within a new neighborhood centre. 13 . Language is a system of signs to express meanings (Chomsky 1965). 14. One will use the terms ‘pre-design’ and the more common term ‘planning’ interchangeably to refer to the formulation of the urban program. 15. In data modeling the task is to organize data so that it represents as closely as possible a real world situation, however feasible in computers’ representation. A data knowledge model encapsulates three main elements: objects’ structure, behavior and integrity constraints (Vazirgiannis & Wolfson 2001).
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1.8. Problem Definition
Any territory16 has potential that must be recognized and used in benefit of its population. This
seems to be clear. However a large part of the urban problem is today a direct consequence of
an inefficient use of the spatial resources (Sanchirico & Wilen 1999).
By planning space, one can prevent the waste of resources allowing, at the same time,
to maximize the satisfaction of population needs. Planning plays, therefore, a key role in
spatial and social organization (D. Harvey 2009). First, because it defines objectives that clarify
the mission of the territory, and second because it establishes levels of effectiveness and
efficiency by implementing measures to attain defined goals (Drucker 2007).
However, concerns related with urban planning surpass today the exclusive satisfaction
of local needs. Today, there is the common belief that any population, in a limited space,
contributes towards a balance at a higher scale (Hirst et al. 1996). This scale, that I will call
global ecosystem17, seems to affect each portion of the territory, at the same time as each
territory’s portion also seems to contribute to the global ecosystem (Pieterse 2009) - ranging
from globalized financial markets (Lin & Mele 2005) to climatic global warming (Houghton
2005). In effect, humans pay today, for the first time in history, the global air that they
breathe18 (Hoel 1991).
The perception of this interdependence of scales is relatively recent in history, and
current planning instruments are still not prepared to act in such a complex level (Terrados et
al. 2007). In fact, there it seems to be a lack of mechanisms for providing the participants of
the planning process with a set of efficient tools integrating multiple scales in order to respond
adequately to current needs. This means that it is not enough to develop an instrument
exclusively focused on the optimization of local resources (Buyya et al. 2005). It is necessary to
create one that can be also capable to surpass local scale towards a more global
consciousness. The diagram 2 depicts the timeline sketch of these changes.
A computational platform, I would argue, can facilitate the creation and the
management of such a more complex planning instrument.
16. Territory is a geographic area under control of a single governing entity such as state or municipality; an area whose bord ers are determined by the scope of political power rather than solely by natural features such as rivers and ridges (Britannica & inc. 2002). 17. An ecosystem is a system combined of organic and inorganic matter and natural forces that interact and change, intricate together by chains and cycles. It’s a sum greater than its parts. Its complexity and dynamism contribute to its productivity, but make it challenging to manage (Rosen 2000). 18 . CO2 international taxes and tradeable quotas (Hoel 1991).
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timeline
site
(local needs)
site
surrounding areas
global
(concerns at the planet scale)
site
surrounding areas
(concerns with surrounding areas)
2. Change of planning paradigms along time. First, a focus on local needs, then on spatial relations
established between site and surrounding areas, and finally, a focus on a more global scale
This overlook constitutes a brief of a vast and complex context that will be addressed in the
next chapters of this study. Meanwhile, it is useful to define some of the key concepts used in
the study.
EFFICIENT URBAN PROGRAMS: First is crucial to increase the existing levels of
efficiency in the management of spatial resources in order to improve the quality of
life of the population. Therefore is important to plan space throughout the
development of efficient urban programs in order to attain defined goals. This is the
first problem that this study aims to solve. However, is not the only one.
SUSTAINABLE URBAN PROGRAMS: The current urban paradigm is recent and strongly
related to a more global consciousness of urban problems. This means that it is
necessary to create a tool for supporting the development urban programs from this
particular perspective.
URBAN PROGRAMS BASED ON A COMPUTATIONAL PLATFORM: Finally, it is
important that such a tool, capable of generating efficient and sustainable urban
programs, can be supported by a computational platform. Such platform allows one
to act in a simpler and partially automated way, thereby enabling the planning
participants an easier management of the contextual data.
The main argument that motivates the development of this study is therefore:
The creation of an efficient model for developing and managing sustainable urban
programs, supported by a computational platform (the formulation model).
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Although based on basic principles, the initial mission of this study is far more complex. Urban
planning deals with extended variables (Mabert et al. 2003), becoming difficult to establish the
right ingredients to develop urban programs (Jabareen 2006). One way to solve the amount of
information is to clarify it by creating a knowledge model called ontology (Gruber 2005) that
permits to organize an extended database, relating all its components. Another
complementary way is to describe the phase of the design process where urban formulation
occurs - the pre-design phase (Best & De Valence 1999), to reveal the way programs are
usually developed.
To formulate urban programs is, therefore, crucial to organize a resourceful database,
and understand how pre-design evolves within the design process (Lawson 2006).
The title of this study - Building a Pre-Design Ontology - is a direct result of two research
issues: a) the pre-design phase, and b) the ontology. However is important to keep in mind
that the core subject behind those two issues is the formulation of sustainable urban
programs. One will call this process Formulation Model (FM), and its development is the core
of the present research. The diagram 3 depicts the frame of these main issues of the research.
3. The core matters of the research: the pre-design phase, the formulation model, and the ontology
1.9. Proposed methodology
It was mentioned above that the most efficient method to solve the problem of managing the
extended data that is necessary process in the formulation model is through the development
of an ontology (Gruber et al 1993). However, there are two different types of methodology to
Formulation Model
creation of urban
programs
Pre-Design Phase
Ontology
knowledge database
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describe the formulation model, corresponding to different scales of approaching the research
problem:
a) the first, is the basic methodology that frames the overall process, that defines the
core path for the work, and
b) the second, is the applied methodology (an ontology), created in order to solve
specific problems of the process (the formulation model process), as for example data
management and definition of formulation rules.
In this introductory chapter is important to describe the basic methodology of the research
developed to accomplish the desired goals. The applied methodology will be described in the
3rd chapter. The basic methodology equates two structural concepts of the planning process:
a) urban complexity19 (Healey 2007), which represents the main problem that this study
aims to solve, and
b) the quality of life of the population (QOL)20 (Maclaren 2004) that represent the main
goal of the formulation model.
Such a methodology requires the creation of a system capable to uncover the urban
complexity (the global problem) and its codification into a coherent set of rules that can be
used for producing plans that ensure the quality of life of urban communities (the global aim).
The solution for such a problem encompasses two steps: 1) to generate successful programs
(formulation model) and, 2) to generate successful plans.
The first corresponds to a pre-design phase, which is the aim of this study, and it can be
diagrammed as follows:
19 . ‘Complexity is the physical fact of problems existing at multiple scales simultaneously. Complex systems solve these problems by adopting geometric structures that have structure at multiple scales simultaneously, that is to say fractal geometry. The architectural scientist Christopher Alexander elaborated on the link between fractal geometry and life by defining the theory of centers, which are parts or features that are distinguishable from the whole and cooperate with the whole to survive in the complexity of the universe. Because centers are themselves made of centers, they fit the recursive definition of fractals. Most important of all, complex structures can only be made through generative processes that draw from a previous step, repeated infinitely. The science of complexity is thus focused on discovering how things are produced, their final form being far too complex for one mind to fully grasp’ (Helie 2009). 20 . A Quality-of-Life (QOF) concept is: ‘The approach to the measurement of the quality of life derives from the position that there are a number of domains of living. Each domain contributes to one's overall assessment of the quality of life. The domains include family and friends, work, neighborhood (shelter), community, health, education, and spiritual ’ - The University of Oklahoma School of Social Work (Notes on 'Quality of Life' Website).
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4. Basic diagram: conceptual outline
1.10. Concerns involving the creation of the formulation model
In the way is understood today, research should contribute towards society (Fritsch 2004). The
evaluation of such contribution is generally located between the purpose and the relevance of
the thematic field under study. In the case of this research, the best way to start exploring it is
by answering a simple question:
Why create a formulation model?
Since the dawn of civilization, humans have made cities to support their societies. Although
these urban settlements have been a source of progress, they have never been totally
understood, relying on traditions and trial-and-error processes for their expansion. Attempts
at planning and bringing them under the control of a planner have not entirely resulted yet
(Hélie 2009). However, there is the relatively common belief that planning can be efficient in
the sense that it can manage spatial resources to provide for QOL.
In fact, the main work of planning, embodied by a large quantity of rules and codes
(building, zoning, etc.), is essentially algorithmic21 , and made up of if-statements. - If
something: do this or that. So in this sense, creating the formulation model is a matter of
developing protocols for how a city will grow (Helie 2009). But protocols must to be built upon
21 . ‘In mathematics, computing, and related subjects, an algorithm is an effective method for solving a problem using a finite sequence of instructions. Algorithms are used for calculation, data processing, and many other fields. Each algorithm is a list of well-defined instructions for completing a task. Starting from an initial state, the instructions describe a computation that proceeds through a well-defined series of successive states, eventually terminating in a final ending state’ (Blass & Gurevich 2003). 21a. ‘In computer systems, an algorithm is basically an instance of logic written in software by software developers to be effective for the intended "target" computer(s), in order for the software on the target machines to do something. For instance, if a person is writing software that is supposed to print out a PDF document located at the operating system folder "/My Documents" at computer drive "D:" every Friday at 10PM, they will write an algorithm that specifies the following actions: "If today's date (computer time) is 'Friday,' open the document at 'D:/My Documents' and call the 'print' function". While this simple algorithm does not look into whether the printer has enough paper or whether the document has been moved into a different location, one can make this algorithm more robust and anticipate these problems by rewriting it as a formal CASE statement or as a (carefully crafted) sequence of IF-THEN-ELSE statements’ (Kleene C. & Kleene C. 1936).
complexity of urban space
• global problem
urban programs
quality of urban life
• global aim
pre-design phase
design phase
plan
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theoretical models in order to support a development vision for a site or a region. That’s why
the formulation model is so extremely dependent on the type of paradigms on which is built-
on (Clark 2000). If the paradigm fails so fails its program. Chapter 2 give an idea about the
relevance of urban paradigms for the development of cities, within a large sort of perspectives.
In the effort to understand the impact of urban paradigms on cuty growth, one even needs to
consider those paradigms that aim to demonstrate the advantages of the absence of planning
methods (Mintzberg 2000), by defending the emergence22 of urban morphologies along time,
as a preferable option for urban space (Burgess & Park 2002).
One fact seems to be clear. There are several models of urban programs used in the
creation of urban plans. It seems also clear that some have failed tremendously23; and others
have lacked implementation, remaining as theoretical guides24. Still, its common flaw appears
to be the absence of crucial urban matters like sustainability factors. This has resulted,
systematically, in the creation of inappropriate plans that are far from satisfying the necessities
of the urban populations, and far from making an appropriate use of site features. But there
are prime questions for such a framework.
What are the main concerns behind the idea of producing a plan?
The task of creating a good plan in order to increase the quality of urban life seems to be
relatively easy at a first glance, by simply producing a full and resourceful program, built
according to urban codes, regulations, and standard parameters. However the problem is
more complex. Other urban programs have taken upon that task and have failed in the
implementation of the plan. Creating a plan seems to be similar to the task of creating a
language (Deacon 1998), or even to use a new language, requiring an additional effort to
understand its new rules. In natural language (linguistics) there is an interaction between two
crucial components: the semantics (the ideas), and the syntax (the form according to which as
ideas are organized) (Chomsky 2002). Connecting the two, in order to create logic, is an
22 . ‘Emergence is the creation of systems of greater dimension than the elements that create it, sometimes also called self-organization, through the application of localized rules of action. The most elementary emergent systems are the binary, one-dimensional cellular automatons studied by Stephen Wolfram that create complex fractals when shown in two dimensions. Emergence is also behind all forms of multicellular life, the cells of a plant or an animal following the instructions coded in their DNA to organize themselves into a much bigger organism. Those organisms will then also create emergent structures by following simple rules of action, like the termite cathedrals often used as an icon for emergence. Emergence is also behind human societies, from the invisible hand of economics (invisible because it is a dimension greater than any one of us) to the astonishing grow th of the Internet and later of Wikipedia. Studying the rules that enable emergence will allow us to build the systems to deal with the complexity of the universe (…) Urbanity is the cooperation and mutual-support of large numbers of people in close proximity. It is inevitably emergent, and to understand the science of emergence is the key to inventing the first fully emergent urbanism, capable of resolving all the complexities of a 21st century, sustainable city‘(Helie 2009). 23 . See a further explanation of the CIAM Athens charter’s principles, in the 2nd chapter. 24 . See a further explanation of the Alexander’s pattern language (1977) theory, in the 2nd chapter.
building a pre-design ontology: towards a model for urban programs
8
enormous task, partially because the urban language (or the planning language) is not the
natural language of human beings. Understanding and clarify it needs a supplementary
research effort. However, this does not constitute the unique reason to envisage a good plan.
What is then behind a proficient urban program?
Embedding more knowledge into an urban program could be one of the answers. It is
recognized that the urban environment is extremely complex because it involves an endless
collection of matters and subjects, ideas, time, capital, and technology. All these subjects are
too vast to compile and describe in short terms. Some studies took more than ten years and
still have great difficulties in the implementation of the methodology. The first intuition is that
such a task will never be accomplished. But the other preferable conclusion is that the task
could be in fact achieved by a detailed survey focused on urban core concepts through a
sequence of judicious steps. It is important to understand how such steps are processed and
under which matters they rest. There are two ways of achieving this.
The breadth and depth of such core concepts is further developed in the Chapter 2,
describing the particular occurrences of recent history, and the impact it had on former urban
programs. Chapter 2 is, thus, as an extension of the description of the problem definition just
presented.
1.11. Expected outcomes and future work
The objective is to create a formulation model that encloses two important aspects:
a) One is the development of an ontology that is necessary to describe the urban
space; first the context, and later the context with the solution, and which is also
necessary to capture the structure of the planning framework.
b) The second aspect is the description of the set of rules that describe the solution.
This goal of this study is closer to the first aspect - the development of a sketch of an ontology
to describe the formulation model.
In summary, one can say that this study provides the basic theory and some of the basic
instructions for the functioning of the formulation model. Future work will concern the
development of the mechanism that gives operability to the formulation model. There are
relevant motives to proceed in such a sequence.
building a pre-design ontology: towards a model for urban programs
9
Starting by creating a mechanism for a purpose whatever, without understanding its
wide contextual framework induces often, the creation of efficient laboratory prototypes. This
happens mainly because such prototypes are developed within a very limited context, with
rules that are only efficient in such limited laboratory environments (Pickering 1992).
Unfortunately, such prototypes are in general inefficient when dealing with real world
problems.
One of the main objectives of this research is precisely to capture the rules of interaction of
urban phenomena in its wide context. The best way to trail such an objective is by start digging
in the formulation framework in order to describe its basic structure. Thus, the study
comprises two tasks:
a) the first task is trying to understand the way formulation deals with a large
amount of matters,
b) the second task is to disclose the characteristics that can make it efficient when
dealing with real urban plans.
The complexity involved in the creation of the formulation mechanism25 is somewhat different.
The specific methods and techniques required for its development demand it to be addressed
in subsequent research. Future work will be based on the theory and the set of instructions
proposed by this research, to make the model amenable to computer implementation. The
goal is to sketch the prototype of such an implementation.
How it will be made?
The formulation model will be encoded into a description grammar26 (Stiny 1980) to establish a
protocol with the generation model27 (shape grammars) of the CI project, which is being
developed according to this theory28. The advantage of using grammars is that it provides the
means to encode a certain degree of automated reasoning. One of the additional tasks is to
allow the model to function with other formats, notations or platforms, in way to provide an
ample base for a computational implementation. An ontology editor seems to be one of the
model’s preferable platforms, because it can easily build up a bridge between the structure
and rules of the model. In fact, some of the ontology software editors possess today a
25 . The formulation language will be the formulation operational tool developed to act in real or simulated urban contexts, supported by a computational platform. 26 . Description Grammar is a context-free grammar specialized for mathematical formulae. 27 . The generation model of the City Induction R&D project 28 . In a similar way it was used in Duarte mass customized housing.
building a pre-design ontology: towards a model for urban programs
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procedural framework to develop rules29, and also protocols for design solutions (Trento
2009). The straight linking process between data-taxonomic-structure (ontology class editor)
and data-description-rules (ontology rules editor) allows one to eliminate part of the hard task
of translation that usually occurs when is necessary to transfer information between different
platforms.
Following the encoding framework the model will be implemented and tested. This will
be achieved by structuring the ontology, so that extensions or refinements of the model will be
accomplished by adding or changing parameters, aiming at a flexible and sustainable data
management. The idea is that the creation of the urban formulation model can be improved by
using one or more case studies. In summary, the division of content between the present and
the future work corresponds to the sequence shown in the diagram 5 as follows:
5. Formulation research outline
1.12. Organization
The current research is divided into a sequence of stages, each representing a defined task
designed to achieve a specific goal and described in a specific chapter, as follows:
29 . ‘A ‘Knowledge Structure’ (KS) is composed of a set of Entities (…) dependent on a set of ‘Rules’.‘Rules’ can be classified in: • Reasoning Rules and Algorithms: formal codes for analysis, checking, evaluation and control of concepts associated to specific entities with inferential procedures of ‘If-Then’ type. • Codes, Laws and in force Rules: context dependant rules referred to the in force law that will become constraints for the entities which they are related to; • Consistency Rules: algorithms to check the consistency of values, parameters, attributes, instances, relationships and prop erties referring to the specific meanings associated to each entity in the specific context on which it is used; • Traditional Rules: non-formalized rules, practices and concepts that represent part of the reasoning process of each actor on his own specific disciplinary domain during the design process. By means of Inference Engines able to match rules among the ontologies - all of which formalized into a syntactically coherent IT structure - a deductive layer allows the designers to use in a coherent manner different levels of abstraction, or to exploit a conceptual interoperability (Calvanese D. et al, 2008). The dynamic and semantically-specific representation detecting incoherent/favourable situations by means of a constraint rule mechanism can allow them to be highlighted and managed in real time (Figure 3). At the same time it allows actors to make alternatives, more consciously reflecting on the consequences of their intents. In this way the impact of a networked ontology based system can make actors more aware of overall design problems, helping them in operating more participative and shared choices. ’ (Trento 2009) (continue. see annex 1 of this research)
volume 1
formulation 'theory and basic instructions'
•descriptive (present work)
volume 2
formulation 'machine'
•operative (future work)
building a pre-design ontology: towards a model for urban programs
11
1st Chapter – Introduction - The first chapter describes the context, the problem, and
the expected outcome of the research - The formulation model and the definition of
its basic ontology.
2nd Chapter – Precedents - The contribution of this chapter is 1) to supply the context
that leads to the necessity for elaborating a platform for urban programs and 2) to
define the essential qualities of the urban design paradigm that such platform needs to
support. The text describes theories and paradigms that implicit particular visions of
how a city must be organized and, therefore, the specific forms of designing it that
influence the substance of urban programs and the form of formulating them.
3rd Chapter – Methodology - This chapter describes a methodology for finding a
solution for the following problem: How to develop a formulation model for urban
programs? The creation of the formulation model requires the development of an
ontology that can be used to describe the urban space; first the initial context, and
later the context with the solution. The ontology, a knowledge database model, is also
important to reveal the way in which urban programs can be structured. The
contribution of this chapter is, therefore, to describe an urban ontology, which will
provide the basis for supporting the development of the formulation model.
4th Chapter - Conceptual and Formulation Models - The objectives of the fourth
chapter are: the description of the basic conceptual model and the description of the
three parts of the formulation model: b1) the input, b2) the mechanism and b3) the
output.
5th Chapter - The Formulation Process - The contribution of the fifth chapter for this
research is: to describe the formulation process as well as the design phase where it
occurs – the pre-design phase. The main objective is to provide a better understanding
of the formulation framework and, at the same time, to generate the sketch of its
semantic ground, that is, a consensual vocabulary to enable appropriate specifications
(or the “communication acts”) towards design solutions.
building a pre-design ontology: towards a model for urban programs
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6th Chapter - The Sketch of a Planning Language - Language, like a seed, is the genetic
system which gives our millions of small acts the power from the whole. The chapter 6
explores the most important category of the formulation model: the system language
that is used by planners to formulate urban solutions. In summary, planner’s language.
7th Chapter - Conclusion
building a pre-design ontology: towards a model for urban programs
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complexity of urban space
• global problem
urban programs
quality of urban life
• global aim
pre-design phase
design phase
plan
This research equates two core concepts of the planning process: a) The urban complexity, and b) The quality of life of the population. The goal is to create a system capable to uncover urban complexity (the problem) codified in a coherent set of rules that can be used to produce plans that ensures the quality of life of urban communities (the goal) – as depicted in diagram 6.
6. Basic diagram: conceptual outline
The title of this study - Building a Pre-Design Ontology - is a direct result of two research issues: a) the pre-design phase of the planning process where formulation occurs, and b) an ontology (a methodology that correspond to a data model). The core subject behind these two issues is the formulation of sustainable urban programs. The following diagram 7 shows these related matters in an interactive model.
7. The core matters of the research: the pre-design phase, the formulation model, and the ontology
The main goal that motivates the development of this study is the creation of a model for developing and
managing sustainable urban programs, supported by a computational platform.
01
•research mission
Formulation Model
creation of urban
programs
Pre-Design Phase
Ontology
knowledge database
building a pre-design ontology: towards a model for urban programs
14
The contribution of this chapter is 1)
to supply the context that leads to
the necessity to elaborate a platform
for urban programs and 2) to define
the essential qualities of the urban
design paradigm that such platform
needs to support. The text describes
theories and paradigms that imply
particular visions of how a city must
be organized and, therefore, the
specific forms of designing it that
influence the substance of urban
programs and the form of
elaborating them.
Chapter 2
2. Precedents
building a pre-design ontology: towards a model for urban programs
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2.1 Introduction
The contribution of this chapter is:
1. to supply the context that leads to the necessity for elaborating a platform
for urban programs and,
2. to define the essential qualities of the urban design paradigm that such
platform needs to support.
The text describes theories and paradigms that imply particular visions of how a city must be
organized and, therefore, the specific forms of designing it that influence the substance of
urban programs and the form of elaborating them.
2.2 The precedents
An overview of the spatial transformations30 that led to current urban environments allows
one to understand how their present problems emerged. The objective is to take into account
the course of urban actions in recent past to establish better solutions for future planning
actions. This fact invokes the need to take a closer look at the space and time mechanism to
extract the elementary laws for formulating urban programs.
Why?
Because urban programs can be reinforced by laws that respond efficiently to typical
(sometimes recurrent) occurrences of space. This leads one to a pathway. The best way to
extract laws - due to long-term process of urban transformations - is by depicting the context
of the recent historical events.
First, one will try to disclose a critical event for urban communities - the European chain
of revolutions in the 18th century.
In the 18th century European society changed dramatically. The chaotic city growth that
followed the rural exodus caused by industrial revolution created the need for regulating such
growth to prevent its flaws. However, such changes have deeper origins. In fact, the extensive
mutation of political and geographic configurations that occurred in the modern era stemmed
30. Correspond to urban transformations, as well as the hybrid ones that are at the origin of the urban formations - even if not totally considered as urban.
building a pre-design ontology: towards a model for urban programs
16
initially from the consequences of the French Revolution of 178931. In this period, the
foundation of the illuminist spirit and the Newtonian positivism transformed the organic
structures of states into open systems, promoting the principle of equal opportunity, within a
new democratic political framework. This paradigm had the following shortcomings; a cycle of
social convulsions that shook European societies unchaining revolutionary movements,
controlled by an intellectual nucleus located in France (Lefebvre & Evanson 1962). Territorial
modifications were then largely implemented, and the birth of the “urban government”
originated a new political order. With the free-ground concept, and the destruction of
dominant models (monarchy and nepotism)32 , the territorial borders of new states in
formation build up drastic alterations within a new political and administrative space,
sprouting new ownership relations, based on a new property domain outline. Property
appeared then associated to an omnipresent battle for territorial ownership imposing the
urgency to implement new laws, in order to control spatial transformations (Rossi 1984).
This context was rapidly amplified by the technological dimension of the industrial
revolution (Harvey 2006) which was commanded by private-initiative model, oppressing the
ideals formed in the French Revolution of 1789. The way communities survived in the
sprawling cities created by the industrial revolution evoked the necessity of creating an
embryonic figure of urban government towards the implementation of laws and rules, in order
to organize the urban environment (Rodrıguez et al. 2001, 415).
Although the reaction to territorial flaws imposed the creation of new forms of
government, the 20th century was marked by a quiet urban expansion developed without a
critical support of communities. According to David Harvey (2006) “perhaps the chief sin of the
twenty-century was that urbanization happened and nobody much either care or noticed in
relation to the other issues of the day judged more important.” The establishment of
participative urban political measures was therefore misled, according to Harvey, by self
31 . The French Revolution of 1789 was the ‘Revolutionary movement that shook France between 1787 and 1799 and reached its first climax there in 1789. Hence, the conventional term “Revolution of 1789,” denotes the end of the ancien régime in France, serve also to distinguish that event from the later French revolutions of 1830 and 1848. Although historians disagree on the causes of the Revolution, the following reasons are commonly adduced: (1) the increasingly prosperous elite of wealthy commoners—merchants, manufacturers, and professionals, often called the bourgeoisie—produced by the 18th century’s economic growth resented its exclusion from political power and positions of honour; (2) the peasants were acutely aware of their situation and were less and less willing to support the anachronistic and burdensome feudal system; (3) the philosophes, who advocated social and political reform, had been read more widely in France than anywhere else; (4) French participation in the American Revolution had driven the government to the brink of bankruptcy; and (5) crop failures in much of the country in 1788, coming on top of a long period of economic difficulties, made the population particularly restless’ (Britannica & inc. 2002). 32 . Nepotism, in politics, is when the relative of a powerful figure ascends to similar power seemingly without appropriate qualifications.
building a pre-design ontology: towards a model for urban programs
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exclusion of the critical mass of urban communities who avoided facing the extension of the
urban problem. The result was an absence of efficient politics in urban governance, hence in
plans.
Despite the absence of communitarian participation, some European elites tried to
develop new theories for organizing urban space, aiming to change social ideals. In 1933, with
the Athens Charter published at the 5th CIAM 33 (Congrès International d’Architecture
Moderne), the paradigms although seaming innovative and ideologically perfect to respond to
a lack of collective beliefs, led to an uncontrolled sprawl, induced by mono-functional zoning
program, which created a set of negative impacts on the urban environment. Several of the
contemporary urban problems are still an indirect consequence of that paradigm or, as some
modernists defend, is the result of an inefficient interpretation of the Charter’s philosophy.
In the 1960’s, the Athens Charter began to be criticized, and urban communities
embarked on a discussing of the post-war urban paradigms, mainly represented by a mono-
functional model that had abundant implementations. In his book “framework of the invisible
city” Mumford (1968) depicts a vision of such a model - a city built upon an impersonal “net,”
essentially functional, characterizing an urban “Megamachine” that grows over nature by a
dominant expansion of human activities. Jane Jacobs was a top figure of the sociologic
movement that was spreading in opposition to the modernist vision. Some of her concepts
concerning security, social cohesion, and communitarian participation (Jacobs 1961) are later
embedded in several urban codes and programs.
Amidst the critics of the “urban modernism” emerged a series of studies led by
Christopher Alexander where the most known is A Pattern Language, (1977) which combined
the design process with genetics34 and linguistics theory (Chomsky 1965). Its concepts mainly
react to the repercussions of the zoning model that was embedded in the CIAM vision,
33 . ‘CIAM's early attitudes towards town-planning were stark: "Urbanization cannot be conditioned by the claims of a pre-existent aestheticism; its essence is of a functional order… the chaotic division of land, resulting from sales, speculations, inheritances, must be abolished by a collective and methodical land policy’ (CIAM). 34 . ‘- The idea that materialized in the published pattern language was first of all, of course, intended just to get a handle on so me of the physical structures that make the environment nurturing for human beings. And, secondly, it was done in a way that would allow this to happen on a really large scale. And, what I mean by that is that we wanted to generate the environment indirect ly, just as biological organisms are generated, indirectly, by a genetic code. Architects themselves build a very, very small part of the world. Most of the physical world is built by just all kinds of people. (…) How could one possibly get a hold of all the mass ive amount of construction that is taking place on Earth and, somehow, make it well, that means let it be generated in a good fashion and a living fashion. This decision to use a genetic approach was not only because of the scale problem. It was important fro m the beginning, because one of the characteristics of any good environment is that every part of it is extremely highly adapted to its particularities. in (The Origins of Pattern Theory - The Future of the Theory, and The Generation of a Living World, by Christopher Alexander, in a presentation recorded live in San Jose, California, in October of 1996, at The 1996 ACM Conference on Object-Oriented Programs, Systems, Languages and Applications (OOPSLA)) (Origins of Pattern Theory website).
building a pre-design ontology: towards a model for urban programs
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proposing a set of organized ideas related with the quality of the communitarian spaces, and
the advantage of functional mixing applied to urban programs. The book describes a “planning
language” designed to be applied across different scales, by applying specific patterns, in a
sequence of steps, in a creative design process. The book encodes clear ideas about the quality
of life of urban communities and gives instructions for how to achieve it by surveying urban
problems and setting solutions for them. However, the Pattern Language theory, in contrast to
the Athens Charter, had very limited implementation and planners had difficulties in applying
the envisioned planning method. The results of the scarce implementation of the proposed
language seem to be, in opposition to an axiom of the theory (the timeless way), recurrently
stylistic and dated35.
In the meanwhile, city growth and organization was strongly influenced by information
technology. The “Informational City” presented in the “Theory of Space Flows” (Castells 2004),
contributed for a refreshed vision of the organization of contemporary society by depicting it
as a network society. The flows within a city referred by Castells “do not represent only one
element of the social organization: they represent the processes that dominate our economic,
symbolic, and politic life.” These invisible nets of communication, associated to the urban
dispersion and the accumulation of information, led to form urban constellations like the
North-American Edge-Cities (Garreau 1998). These cities encompass a group of incorporeal
connecting networks (technology and software), as well as material nets (highways and roads).
The interconnection of those two nets has originated a chaotic urban development. This
chaotic growth presents difficulties to the recognition of patterns. However and according to
James Gleick, (1987) the chaos can be object of study, using the “irregularity patterns” concept
based on dynamics theory.
The end of the traditional city was then announced as a victim of the deindustrialization
and the depletion of local resources. It represents one of the deepest alterations in
contemporary urban systems, that led to an increasing urban sprawl36, defined by a territorial
35 . ‘- Although we intended that the pattern language would be generative, that is, would allow people to generate buildings and building designs, for themselves - truthfully, this does not happen. The patterns provide many profound ideas, and geometrical "nuggets": which are needed to make the environment work. But, as written in 1977, they do not actually allow a person to generate a good design, step by step. They do not place the emphasis on morphological unfolding, as they should’. (Pattern Language author website). 36 . Sprawl: ‘A haphazard and disorderly form of urban development. There are several elements that characterize sprawl: a) Residences far removed from stores, parks, and other activity centers, b) Scattered or “leapfrog” development that leaves large tracts of undeveloped land between developments, c) Commercial strip development along major streets, d) Large expanses of low-density or single use development such as commercial centers with no office or residential uses, or residential areas with no nearby commercial centers, e) Major form of transportation is the automobile, f) Uninterrupted and contiguous low- to medium-
building a pre-design ontology: towards a model for urban programs
19
dystopia37 (Harvey 2006) that generates a grid of distant economic free markets and sets out
an invisible net that feeds some top-regions more technologically developed (Castells 2000),
thus promoting an exclusion of the less developed ones. This fragmentation could have been
prevented by the State in an early phase of reaction to such a powerful urban model, however,
the State played a limited role (Stanlake & Grant 1994) facing the hegemony of monopolist
companies, leading to the fall of the state-regulator figure, which dominated traditional cities
before the last post-war (Harvey 2006). The end of the traditional city becomes hence a spatial
transformation factor, where fragmentation emerges as a result of a continuous adaptation to
a spatial model in constant development (Castells 2005). These dynamics appeared partially as
a consequence of a dispersive free market model, in clear opposition to the previous
industrial-localization. Quoting previous works, David Harvey (Harvey 1995:44) refers that
capitalism as a production factor was specially developed to break spatial barriers, speeding up
the “time” factor, with the intention of an exclusive accumulation of capital. Urban economy
seemed then to influence crucial factors in the development of cities, generating new urban
phenomena. The concept of privatization of the communal space and the lack of democratized
access to cities, developed in “Splintering Urbanism” (Graham & Marvin 2001) is directly
associated with the phenomena of social exclusion and stigmatization. This effect is well
represented by the collapse of the traditional city of exchanges and interdependent markets,
supplied by the neoclassical economy, and inspired in the prosperity of the organic and multi-
functional medieval society. Salvador Rueda (1998) evokes this urban phenomenon concluding
that it conduces to the death of Cities; “a planificación funcionalista y el mercado van creando
espacios exclusivos según los niveles de renta, creando de nuevo un puzzle territorial,
desconectando el tejido social y diluyendo el sentido que tiene la ciudad como una civis”. The
contemporary city seams therefore to become a consequence of a globalized community,
generating phenomena of inclusion and exclusion, deeply rooted in its particular economy and
in strong technological development.
Other theories described the welfare-state as a model that sprouted a group of
bureaucratic instruments in an attempt to solve the urban expansion phenomenon, assuring
density (one to six du/ac) urban development g) Walled residential subdivisions that do not connect to adjacent residential development’ (Evans et al. 2007). 37 . A dystopia (from the Greek δυσ- and τόπος, alternatively, cacotopia, kakotopia, cackotopia, or anti-utopia) is the often futuristic vision of a society in which conditions of life are miserable and characterized by poverty, oppression, war, violence and/or terror, resulting in widespread unhappiness, suffering, and other kinds of pain. (Harper & Harper, Douglas n.d.)
building a pre-design ontology: towards a model for urban programs
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an accomplishment of a classic planning dichotomy - “agreed goal” and “known
technology”(Christensen & Bang 2003); a perfect functional and closed system. This system,
supported and strengthened by the modernist ideals, defined a rigid set of goals and
techniques in order to implement plans. Christensen defends that such dichotomy, although
effective during a specific period of time, falls upon social dynamics, due to its relative
inflexible administration. A group of concepts defined in the “Governance of Europe’s City
Regions,” highlights the need for the implementation of flexible policy in order to produce
more efficient plans, acting as a reaction to the classic welfare-state conceptions. In fact, the
changing nature of regions moving from fixed territory (spatial container) to regional groupings
of specialized production clusters, requires flexible policy responses (Herrschel & Newman
2002). Flexible plans appeared therefore to act as the natural reaction to the dynamic
character of the contemporary urban reality, guaranteeing a balance between the public and
the private sectors (within their particular interests), towards a “common good” and “public
interest” (Healey 2007). Plans can thus be executed efficiently (Christensen & Bang 2003) by
implementing flexible models supported by local communities, acting as a protective shell
against the unpredictable dynamics of the urban space.
2.3 Conclusion
In summary one can say that until the 19th century the problem was situated within geographic
borders, and after the 60’s decade of the 20th century concerned a much different subject - the
collapse of the traditional city, and a change imposed by market laws, the zoning concept, and
the free economy model, promoting an endless functional grid involving the expansion of the
urban structure. It is also manifest that at the beginning of the 21st century, another core
discussion appeared on the research bench; the development of an abstract “urban net”
within a new theory of space - “the informational net” (Castells 2003) - an invisible network
connecting new urban space formations. Hence, while prior to the 19th century the urban
phenomenon was related essentially with the physical and visible aspects of property (Rossi
1984), the post-war conceptions appeared to involved a more complex and dynamic problem -
the difficulty of a physical recognition of the urban structures in expansion (Portas et al. 2003:
221); partially attributed to the spreading of an incorporeal society network (Castells 2005)
and to a specific economic model. The immateriality of the contemporary urban space is, in
the words of João Ferrão (Portas et al. 2003), part of the “real city today”; an unrecognized city
building a pre-design ontology: towards a model for urban programs
21
due to the fact that it appears to be morphologic and politically invisible. More recently
numerous group of researchers are pointing out to climatic factors and energy resources as
key issues of urban planning, responding to increasing global concerns as are the climatic
changes (Houghton 2005).
Throughout all these periods, the concerns of planners with solving urban problems
changed dramatically; and several experiences on the field, following new urban theories (as in
the CIAM vision), caused even more problems, creating a sense of a global collapse. Despite all
efforts and failures, important planning concepts remained more or less consensual;
1. The first concept represents a repercussion of the Industrial Revolution,
establishing the need to regulate urban space to guaranty the quality of urban life
- urban goals, rules, and guidelines.
2. The second concept describes the need for implementing a more
multifunctional and organic urban system, refuting the hegemonic economic
model of the dispersive free market, and the modernist CIAM vision - mix-uses/
social space/ participation.
3. A third concept describes a flexible system within urban plans, capable of
absorbing the social mutations, reacting to the unpredictable dynamics of the
urban phenomena - flexible programs,
4. The fourth concept describes the relevance of the sustainability factor, as a
balance between all factors of the urban phenomena, including the economic,
social, energetic and climatic factors - sustainable programs.
As a result, today is more or less consensual that urban programs should: a) be regulated by
goals, rules and constraints, b) be multifunctional, c) be participative, d) be flexible, and e) be
sustainable.
These are the features that the study City Induction project tries to respond to and this
research is concerned with the development of a formulation model according to the same
principles.
building a pre-design ontology: towards a model for urban programs
22
It is more or less consensual that urban programs should: a) be regulated by goals, rules and constraints, b) be multifunctional, c) be participative and collaborative, d) be flexible, and e) be sustainable. These are the features that the formulation model tries to respond to.
The diagram 8 shows the interaction of the main laws of urban programs depicted in this chapter.
8. The main laws of urban programs
Urban programs core structure:
1. Rules and Constraints | goals, rules and constraints
2. Multifunctionality | diversity and mixture
3. Participation | involvement of communities
4. Flexibility | strategies for future actions (change of uses and concepts)
5. Sustainability | environmental and social philosophies
02
• urban programs - the main laws
participation and collaboration
goals, rules and constraints
flexibilitymultifunctionality
sustainability
building a pre-design ontology: towards a model for urban programs
23
This chapter describes a
methodology to find a solution for
the following problem: How to
develop a formulation model for
urban programs?
The contribution of this chapter is to
describe an ontology, which is the
selected methodology to support the
development of the formulation
model.
Chapter 3
3. Methodology
building a pre-design ontology: towards a model for urban programs
24
3.1. Introduction
This chapter describes a methodology to find a solution for the following problem:
How to develop a formulation model for urban programs?
The creation of the formulation model encloses an important aspect - the development of an
ontology that is necessary to describe the urban space; first the context, and later the context
with the solution. The ontology is also important to reveal the way formulation model can be
structured in order to establish communication protocols within the planning process, that is,
the process of generating the urban program from the context.
The goal of the study in which context this thesis evolves is therefore to find a solution
for the formulation model. The solution for this problem includes two steps: one is the
development of an ontology to describe urban space, as well as the ontology of the
mechanism by which a program is generated from the analysis of the context; and the other is
the inference of the mechanism itself, that is, of the rules that composed it. This chapter is
concerned with the development of the ontology to describe urban space.
The ontology corresponds basically to at a knowledge based model applied to urban
programs. The outline and the details involving such methodology will be described in this
chapter.
3.2. Adopted methodology
The planning process requires the establishment of an adequate communication with
stakeholders, to share ideas within a planning team, or to present a strategy to a community.
Urban formulation - an important part of the planning process - requires a method to select
and organize data that describes the urban context, to generate a description of the solution
for that context, and to share and communicate the solutions to the stakeholders. An
ontology, a Knowledge Representation (KR) model is a data modelling process or a language
that is capable to represent and convey such type of information (Caneparo et al. 2007). KR is
not a “picture” of the problem, but rather a device for the attainment of knowledge about it
(Kaplan, 1963). Indeed, sometimes the most important outcome of a data modelling process
(here represented by an ontology) may not be the process itself, but rather the insight one
gains as one struggles to articulate, to structure, to critically evaluate, and agree upon it
(Moore & Agogino, 1987). “Therefore, the purpose of the modelling process - an ontology - is
building a pre-design ontology: towards a model for urban programs
25
not only a proper representation of a process but rather how this process can help one to
better understand the domain of knowledge represented in it” (Luca 2007).
What is an ontology?
The concept comes from a theory that concerns the study of existence born from the legacy of
the Aristotelian philosophy meaning “a systematic explanation of the existence” (Gruber et al
1993). The “Aristotelian ontology offers primitive categories, such as substance and quality,
which were presumed to account for “All That Is”. Ontologies, in general, are created to
facilitate the understanding about a specified a domain by defining its entities, its classes, its
functions and the relationships between all those (Fonseca & Egenhofer 1999). Despite its
philosophical legacy, the ontology described in this research is related with a technical term
and method that is used in computer science.
Why create an ontology?
An ontology is a resourceful data model that helps to support the development of the urban
formulation model by providing a common vocabulary for users who need to share
information in this specific domain (Sachs et al. 2006). In addition, an ontology is an accurate
mechanism to explicit and increase the knowledge about a specific subject matter, in the case
of this research concerning urban space as well as the set of solutions to intervene in it. Some
of the reasons to create an ontology are:
1. A share of a common understanding of the structure of information among people or
software agents,
2. To enable the reuse of the domain knowledge,
3. To make domain assumptions explicit,
4. To separate domain knowledge from operational knowledge, and finally
5. To analyze domain knowledge.
In the context of the formulation model such process permits to:
1. Create a common shared structure of information to support urban programs,
2. To recycle such information in order to use it recurrently in different urban contexts,
3. To explicit the formulation concepts by defining the way entities operate within the
ontology,
4. To separate the domain conceptions from the urban operative descriptions, and
5. To assess the data model in order to improve the pre-design ontology (Noy et al.
2001).
building a pre-design ontology: towards a model for urban programs
26
How to create an ontology?
The best method to create an ontology is with an ontology editor which is a software platform
composed by three basic blocks that include: 1) classes, 2) slots (sometimes also called roles or
properties), and 3) facets (sometimes called role restrictions). An ontology of such type
together with a set of individual instances of classes constitutes a knowledge base (Sachs et al.
2006). There is no one correct methodology, nor is there a single correct result for developing
ontologies. “Developing an ontology is an iterative process. Usually one can start with a rough
first pass at the ontology, and then revise and refine the evolving ontology in order to fill in the
details” (Noy et al. 2000). In practical terms developing an ontology includes: 1) defining
classes in the ontology, 2) arranging the classes in a subclass-superclass hierarchy, 3) defining
slots and describing allowed values for these slots, and 4) filling in the values for slots for
instances. The undertaking of the production of ontologies is according to Smith and Mark,
(Fonseca & Egenhofer 1999): 1) to help to understand the way different communities share
information, 2) to help to discover certain distortions in the cognitive processes of conception
of the world, and 3) to supply patterns towards the development of a process.
3.3. Ontologies within computer science - (AI) Artificial Intelligence
Due to its capabilities, ontologies have been adopted in many business and scientific
communities as a way to share, reuse and process domain knowledge. “Ontologies are now
central to many applications such as scientific knowledge portals, information management
and integration systems, electronic commerce, and semantic web services” (McGuinness et al.
2000). This demonstrates the potential of ontologies within computer science. In this
application field the ontology term denotes a method that is designed for a purpose, which is
to enable the modelling of knowledge about a real or imagined domain. Gruber (1993)
describes in a very explicit way how to develop ontologies and the implications of such
method. He noticed that the term had been adopted by early Artificial Intelligence (AI)
researchers, who recognized the applicability of the work from mathematical logic (McCarthy
1980). He also noticed that AI researchers could create new ontologies as computational
models that enabled certain kinds of automated reasoning (Hayes-Roth 1985). Gruber refers
that “in the 1980's the AI community came to use the term ontology to refer to both a theory
of a modelled world (Hayes 1979) and a component of knowledge systems; referring that
building a pre-design ontology: towards a model for urban programs
27
“some researchers, drawing inspiration from philosophical ontologies, viewed computational
ontology as a kind of applied philosophy” (Sowa 2000).
3.4. Ontology Interoperability
It was patent in an effort, in the early 1990's, to create interoperability standards by identifying
a technology stack that called out the ontology layer as a standard component of knowledge
systems (Neches et al. 1991). “A widely cited web page and paper associated with that effort
is credited with a deliberate definition of ontology as a technical term in computer science”
(Gruber et al. 1995). The paper defines ontology as an “explicit specification of a
conceptualization,” which is, in turn, “the objects, concepts, and other entities that are
presumed to exist in some area of interest and the relationships that hold among them.”
While the terms specification and conceptualization have caused much debate, the essential
points of this definition of ontology are, according to Gruber that: 1) an ontology specifies the
concepts, relationships, and other distinctions that are relevant for modelling a domain, and 2)
the specification is in the form of definitions of representational vocabulary (classes, relations,
and so forth), which provide meanings for the vocabulary and formal constraints on its
coherent use. One of the essential characteristics of the ontologies is the sharing of
information - the shared knowledge, which allows the creation of common systems. The
advantage is to provide an integration of different studies on the same substance of inquiry,
through a recurrent general procedure. This focus allows and prevents ambiguities between
results. However the difficulties caused by the heterogeneities of the information have
invoked an increased necessity of creating a science of integration (Fonseca et al. 2002).
According to Fonseca and Egenhofer (1999) the elaboration of ontologies requires also the
participation of diverse entities in permanent interaction. They described the key elements of
such system by; “container” (container of objects from diverse sources), “data repository”
(within a defined research and classes), “user interface”, and the “ontologies” (dynamic
structures - objects in a pattern catalogue). In such scheme, these forms are mediated by the
“coordinator”.
3.5. Representation of ontologies
The ontology allows one to act within two differentiated and complementary levels: the “top
level ontology” (Guarino 1997) where the concepts and the macro scale relations are located;
and the “application ontology”, where are specified the concepts describing the nature of its
building a pre-design ontology: towards a model for urban programs
28
particular interactions. The “top level ontology”, as mentioned, describes relations at a macro
scale – for example the core components of the pre-design phase. The “application ontology”
specifies particular concepts belonging to particular fields which include detailed tasks - for
example the urban codes of the pre-design phase. The representation of ontologies can also
be expressed through standard associations (Novello et al. n.d.) to qualify the relations
between entities, namely: taxonomy (is a, type of), partonomy (part of), mereology (“part-of-
all” theory), chronology (precedents between concepts) and topology (theory of limit and
border). Moreover, ontologies can be represented by; a) dominions, which describes the
vocabulary used in a specific field of knowledge; b) tasks, which describes the vocabulary used
in a specific activity of a field; and c) representations, which explains the concepts of formal
entities.
Urban ontologies are usually called spatial ontologies, due to its relevant spatial
descriptions. The development of research in the field of spatial ontologies has created a
specific lexicon and a theoretical structure, to responds to the specific demands of spatial
domain. Smith and Mark (1999) purposed the creation of spatial ontologies with the objective
of getting a better understanding concerning the geographic world. The same authors allege
that the use of this type of ontologies can assist users in the exchange of information
preventing distortions from human cognition, which is a recurrent idea in the creation of
generic ontologies. To Pinho and Goltz (n.d.) the geographic objects, that are the spatial
fundamentals of the urban space, can be divided in two types, defined by the Latin axioms
Bona Fide and Fiat. The first type congregates objects that possess a physical delimitation
more or less accepted between people of different cultures. They are tangible objects as a
road, a mountain, or a lake. In opposition Fiats referrers to objects with abstract limits. Such
Fiats can be divided by 1) Fiats and vagueness that are geographic objects that do not possess
a well-defined border, and were limits are diluted in space, b) Consensus Fiats that are objects
that have its existence on a consensual form by given information from inhabitants in a
determined area, c) Legal fiats that are objects that have their limits defined on some legal
basis, as the land use or the airspace, and the GIS fiats that are objects generated from the
mathematical logic of the GIS.
The development of the diagram (9) is inspired in the urban plot diagram developed by
Pinho and Goltz [n.d.]. This diagram aims to explain some types of entities that compose an
ontology, in this case involving urban patterns.
building a pre-design ontology: towards a model for urban programs
29
9. Example of an urban pattern top level ontology. This diagram is inspired in the urban plot diagram
developed by Pinho & Goltz [n.d.]
3.6. Editing ontologies
As aforesaid the best method to create an ontology is with an ontology editor.
But what is an ontology editor?
According to Sachs (2006) an ontology editor is an integrated software tool used by system
developers and domain experts to develop knowledge-based systems. The applications
developed with an ontology editor are generally used in problem-solving and decision-making
in a particular domain. In the case of this research the problem is focused on the urban space
phenomena, and the decision-making on the set of solutions to implement in such a space in
order to support sustainable communities.
Where to start?
One might start by determining what the ontology is going to be used for, and how detailed or
general the ontology is going to be. In this thesis the objectives is clear: to define a formulation
model for urban programs. Such ontology, in a primary phase, will describe basically the
general concepts of the formulation model, and eventual methods to categorize its entities.
is
is
is part of
urban patterns
inanimate objects
geographic object
fiat
legal fiat
urban codes
GIS fiat
GIS data
consensus fiat
field analysis
fiat and vagueness
private space (example)
bona fide
common object
building a pre-design ontology: towards a model for urban programs
30
There are several viable alternatives for creating the ontology. One of the first steps will
be to determine which alternative would work better for the projected task, be more intuitive,
more extensible, and more maintainable - remembering that an ontology is a model of a real
domain in the world, ant that the concepts in the ontology must reflect this reality. After
defining an initial version of the ontology, one can evaluate and debug it by using it in
applications or problem-solving methods or by discussing it with experts in the field. Such a
framework is crucial to develop the formulation model. “As a result, one will almost certainly
need to revise the initial ontology. This process of iterative design will likely continue through
the entire lifecycle of the ontology” (Sachs et al. 2006).
To explicit the functioning of an ontology editor it will be develop an example with the
Protégé editor (Noy et al. 2001) following the trail of its tutorial. The case is simple. Suppose
one wants to develop an ontology for climatic patterns. The “examples/climatic patterns”
subfolder of the ontology editor installation directory contains a completed Editor-Frames
project, - urban climatic patterns, which provides one possible ontology for this domain. Some
of the questions one want to answer are:
1. What are the components responsible for each climatic pattern?
2. What is the content of each pattern, and what is the theory behind it?
3. To what matters each pattern is related with?
4. What is the layout of each pattern?
Once one has an idea of what one wants to cover, one can list some of the important terms
needed. These can include basic concepts, properties they might have, or relationships
between them. To begin with, one can just collect the terms without regard to the role they
might play in the ontology. In the climatic patterns example one have particular patterns. Each
one contains content such as “type of climatic aspect that is covered” and “applicability” and it
has a theory behind it that is responsible for the validity of its existence. Each pattern has a
form, and that form may or may not be material. For each material pattern, one wants to
know its name and subject, and to what it relates with. As one continues to generate terms,
one are implicitly defining the scope of our ontology, by deciding what to include and what to
exclude. For example, upon initial examination of the term material pattern, one might want
to add “sun protected windows” or “wind impact on streets”. However, upon reflection, one
might realize that one wants the ontology to focus on the costs associated with the content of
the “sun impact on buildings”. Therefore, one would decide not to include “wind impact on
building a pre-design ontology: towards a model for urban programs
31
streets” as a term of interest. When one has a fairly complete list, one can start to categorize
the different terms according to their function in the ontology. Concepts that are objects, such
as “pattern” or “site application”, are likely to be best represented by classes. Properties of the
classes, such as “wind” or “sun”, can be represented by slots, and restrictions on properties or
relationships between classes and or slots, are represented by slot facets (Noy et al. 2000).
Above is shown an example of the development of a climatic pattern in the Protégé editor. The
example presents cold region patterns.
10. Protégé edition of a climatic pattern
11. The visualization tab of the cold region edited by the Protégé editor
building a pre-design ontology: towards a model for urban programs
32
12. In the left is shown the class hierarchy of the climatic patterns ontology. In the top right is shown the
type of role of each class (related with a different symbol) – abstract or concrete. In the bottom right is
shown an instance slot (bioclimatic pattern slot) where one can fill up all required data
3.7. Comparing ontology editors: Ontolingua and Protégé
The Ontolingua editor was developed by the Knowledge Systems Laboratory of Stanford
University (KSL), and it offers a set of program tools that allows the editing of ontologies. The
system is referred to by several authors, amongst them, Fonseca and Egenhofer (1999).
Ontolingua is an online software where web sessions are authorized for registered users. The
Stanford KSL Ontology Editor allows, through a set of procedures, to create series of axioms,
made within a hierarchy of classes, and associations of “Examples” or individual “Instances”,
establishing “Functions”, “Facets” e “Slots” as schematic entities. This comprises the basic
vocabulary of the Ontolingua Editor. The generation of these entities is clarified by the
program’s tutorial (Farquhar 1997), within a set of suggestions and guidelines for the
development of ontologies, namely; “1) to write a few sentences describing the ontology
including the general subject area that is intended to cover with the ontology, 2) to make a list
of what one would like to state in the ontology, 3) to make a list of the concepts that one think
should be included in the ontology, 4) to look for ontologies in the library of ontologies that
may contain terms which one can use to develop the ontology, and5) review and make
modifications to one’s lists as needed throughout these steps” (Farquhar 1997).
building a pre-design ontology: towards a model for urban programs
33
Like the Ontolingua editor, the Protégé editor is a free, open-source platform that
provides a growing user community with a set of tools to construct domain models and
knowledge-based applications with ontologies. One of its advantages is the plain access to
formats and protocols towards the creation of resourceful data models. The Protégé
implements a rich set of knowledge-modelling structures and actions that support the
creation, visualization, and manipulation of ontologies in various representation formats.
Protégé can be customized to provide domain support for creating knowledge models and
entering data, appearing to be friendlier than the Ontolingua in the management of its
platform. Furthermore, Protégé can be extended by way of a plug-in architecture and a Java-
based Application Programming Interface (API) for building knowledge-based tools and
applications. The Protégé platform supports two main ways of modelling ontologies: 1) The
Protégé-Frames editor enables users to build and populate ontologies that are frame-based, in
accordance with the Open Knowledge Base Connectivity protocol (OKBC). “In this model, an
ontology consists of a set of classes organized in a subsumption hierarchy to represent a
domain's salient concepts, a set of slots associated to classes to describe their properties and
relationships, and a set of instances of those classes - individual exemplars of the concepts that
hold specific values for their properties” (Sachs et al. 2006). 2) The Protégé-OWL editor
enables users to build ontologies for the Semantic Web, in particular in the W3C's38 Web
Ontology Language (OWL). “An OWL ontology may include descriptions of classes, properties
and their instances. Given such an ontology, the OWL formal semantics specifies how to derive
its logical consequences, i.e. facts not literally present in the ontology, but entailed by the
semantics. These entailments may be based on a single document or multiple distributed
documents that have been combined using defined OWL mechanisms”. Protégé ontologies can
be exported into a variety of formats including RDF39(S), OWL, and XML Schema40. Protégé is
38 . W3C: World Wide Web Consortium. 39 . The RDF data model is similar to classic conceptual modeling approaches such as Entity-Relationship or Class diagrams, as it is
based upon the idea of making statements about resources (in particular Web resources) in the form of subject-predicate-object
expressions. These expressions are known as triples in RDF terminology. The subject denotes the resource, and the predicate
denotes traits or aspects of the resource and expresses a relationship between the subject and the object. For example, one way
to represent the notion "The sky has the color blue" in RDF is as the triple: a subject denoting "the sky", a predicate denoting "has
the color", and an object denoting "blue". RDF is an abstract model with several serialization formats (i.e., file formats), and so the
particular way in which a resource or triple is encoded varies from format to format. http://www.w3.org/TR/PR-rdf-syntax/
"Resource Description Framework (RDF) Model and Syntax Specification".
40 . An XML schema is a description of a type of XML document, typically expressed in terms of constraints on the structure and
content of documents of that type, above and beyond the basic syntactical constraints imposed by XML itself. These constraints
are generally expressed using some combination of grammatical rules governing the order of elements, Boolean predicates that
building a pre-design ontology: towards a model for urban programs
34
based on Java, is extensible, and provides a plug-in environment that makes it a flexible basis
for rapid prototyping and application development. “Protégé is also supported by a strong
community of developers and academic, government and corporate users, who are using
Protégé for knowledge solutions in areas as diverse as biomedicine and intelligence gathering.
Protégé is a U.S. national resource for biomedical ontologies and knowledge base supported
by the U.S. National Library of Medicine, and is a core component of The National Centre for
Biomedical Ontology, within the Stanford Centre for Biomedical Informatics Research” (Noy et
al. 2000).
the content must satisfy, data types governing the content of elements and attributes, and more specialized rules such as
uniqueness and referential integrity constraints.
building a pre-design ontology: towards a model for urban programs
35
data knowledge model
(an ontology editor)
attributes
data
relational rules
how to develop a pre-design model
to launchsustainable
urban programs
1
•problem
2
•methodology
3
•management tool
helps to create and manage
urban programs
classes slots
instances
phases procedures
rules constraints
sorted data
The objective is to create a model that encloses the development of an ontology to describe the urban space; first the context, and later the context with the solution. The objective is to make use of an administrative tool that helps to create and manage urban programs.
The framework is described in the following diagram scheme.
13. Methodology framework
Methodology (management tool):
1. Problem |Complexity of urban data
2. Methodology |Organizes data elements to facilitate understanding
3. Management tool |Help with the creation and management of urban programs
03• an ontology (a data model) is a good way of describing the pre-design phase of the urban design process.
•an ontology helps with the creation and management of urban programs.
building a pre-design ontology: towards a model for urban programs
36
The objectives of the fourth chapter
are:
a) the description of the basic
conceptual model, and
b) the description of the three parts
of the formulation model: b1) the
input, b2) the mechanism, and b3)
the output.
Chapter 4
4. Conceptual and Formulation Models
building a pre-design ontology: towards a model for urban programs
37
4.1. Introduction
The objectives of the fourth chapter are:
a) the description of the basic conceptual model, and
b) the description of the three parts of the formulation model41: b1) the input, b2)
the mechanism, and b3) the output.
4.2. The conceptual model
The basic conceptual model represents the core concept of this research, and the goal of this
chapter is to explain it.
The conceptual model describes the structure of the formulation process and is inspired
in a more global mathematical model invented by Duarte (2003) for developing interactive
systems for generating design solutions. Duarte’s model is called discursive grammar, and it
includes a program system for formulating the design brief based on contextual data, a design
system for generating a solution that matches the brief, and an evaluation system for
guaranteeing that the brief fits the context and the solution matches the brief (Diagram 14).
The program or formulation system is encoded by a description grammar (Stiny 1981),
whereas the design system is composed of a description and a shape grammar (Stiny 1980).
The evaluation system compares the description in the design brief with the description of the
evolving design. A set of heuristics is then used to guide the generation of solutions towards to
ensure that the solution’s description matches the brief’s description. The model developed in
this research explores the “formulation system” (the first module in Duarte’s model), adapting
it to the urban context, and introducing additional functions, such as a clear definition of the
design brief ‘s description structure by means of an ontology and its encoding using an
ontology editor.
41. The ‘formulation’ term, in this research, denotes the planning framework of producing an urban program (and also its process). Formulation occurs during the ‘pre-design phase’ and it corresponds to an initial phase of the urban design process where the actions to intervene in the urban space are planned by deriving the program from the context.
building a pre-design ontology: towards a model for urban programs
38
•contextual data
INPUTS
•machine
INTERPRETER
•design specifications
OUTPUTS
portuguesehousing
program system
Siza’sMalagueira
design system
portuguesehousing
evaluation system
context program design
Pedro, 1999Description grammar (Stiny, 1981) Shape grammar (Stiny and Gips, 1972)
Pedro, 2000
14. Duarte’s model (discursive grammar for housing) based in three theories (Stiny 1981), (Pedro 2001a)
and (Stiny & Gips 1972)
1. INPUT Read Data (urban context) DATA COLLECTION
2. INTERPRETER Interpretation of data MECHANISM (for generating the program)
3. OUTPUT Define Specifications (for design) PROGRAM (design brief)
As in Duarte’s model, in FMo there is a clear path information flow between the three basic
functions or components of the model, as shown in Diagram 15.
information path
information path
15. The conceptual model of the urban formulation process (FMo)
building a pre-design ontology: towards a model for urban programs
39
Model’s functioning
In a sense, the conceptual model is a representation of a “computational procedure that takes
some value or set of values, as inputs and produces some value, or set of values, as output”
(Cormen et al. 2001). One can also argue that, informally, this process corresponds to an
algorithm which is any well-defined computational procedure based on data exchanges - a
sequence of computational steps that transform the input into the output. An algorithm that
can also be interpreted as a tool for solving a well-specified computational problem - a
problem here focused on the generation of urban solutions.
As mentioned, the algorithm describes a specific computational procedure for achieving
the input/output relationship. For example, one might want to sort a sequence of numbers in
decreasing order. This problem arises frequently in practice and provides a ground for
introducing standard design techniques. Alexander’s Pattern Language (Christopher Alexander
et al. 1977) was created under a similar conceptual structure. Here is how one formally can
define a sorting problem:
Input: A sequence of n numbers a1, a2,..., an .
Output: A permutation (reordering) a’1, a’2,..., a’n of the input sequence such
that a’1 a’2 ... a’n.
Given an input sequence 41, 61, 79, 36, 61, 78, a sorting algorithm returns as output the
sequence 36, 51, 61, 61, 78, 79. Such an input sequence is called an instance of the sorting
problem. In general, an instance of a problem consists of the input (satisfying whatever
constraints are imposed in the problem statement) needed to compute a solution to the
problem. The input corresponds to urban contextual data, being the constraints part of its
interpretation. The solution corresponds thus to the interpretation output, which in this case
corresponds to specifications for design solutions.
An algorithm is said to be correct if, for every input instance, it halts with the correct
output. Cormen (2001) says that a correct algorithm solves the given computational problem,
as an incorrect algorithm might not halt at all on some input instances, or it might halt with an
answer other than the desired one. An algorithm can be specified (in computer science) as a
computer program, or even as a hardware design. The requirement is that the specification
must provide a precise description of the computational procedure to (Cormen et al. 2001) - if
something, then do something - the recurrent concept of the urban formulation framework.
Now, a closer look at the model’s basic components:
building a pre-design ontology: towards a model for urban programs
40
INPUT: The first component of the conceptual model (Data) corresponds to the set of
information that is gathered to describe the urban space (among other contextual
information). Data corresponds to the set of information collected on the site and
the local population, as well as on the promoter’s features, mandatory requirements,
or ideas about the plan’s development.
INTERPRETER: The Interpreter42 corresponds to the core of the model - a centre of
data exchange and interpretation (analysis, conversions, and synthesis). The
Interpreter defines the flow between the contextual data and the final list of
requirements or ingredients that will be used as patterns for design.
OUTPUT: The third component corresponds to the set of specifications that will help
to described spatial solutions (organization, shape, and morphology). The data
structure43 organization of the output data (its ontology) is particularly important. An
adequate formulation ontology (the structure of the urban program) will facilitate
the generation of better solutions as it facilitates the flow between descriptions
(urban program) and generation (urban solutions). Model descriptions will be
created on the foundations provided by the Alexander’s Pattern Language theory.
4.3. The formulation model
The formulation model (FMo) is the detailed structure of the conceptual model that enfolds a
simple sequence of ideas, that is;
a) a problem is perceived (the urban context),
b) thus emerges the need to intervene to solve the problem,
42 . A classical translating machine stands with one foot on the input text and one on the output. The input text is analyzed by the
components of the machine that make up the left leg, each feeding information into the one above it. Information is passed from
component to component down the right leg to construct the output text. The components of each leg correspond to the chapters
of an introductory textbook on linguistics (…), then syntax, semantics, and so on. (…) We cannot be sure that the classical design is
the right design, or the best design, for a translating machine. But it does have several strong points. Since the structure of the
components is grounded in linguistic theory, it is possible to divide each of these components into two parts: a formal description
of the relevant facts about the language, and an interpreter of the formalism. The formal description is data whereas the
interpreter is program. The formal description should" ideally serve the needs of synthesis and analysis indifferently. (…) (Kay
1984).
43 . A data structure is a way to store and organize data in order to facilitate access and modifications. No single data structure
works well for all purposes, and so it is important to know the strengths and limitations of several of them (Luger 2005).
building a pre-design ontology: towards a model for urban programs
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c) however the problem needs to be made explicit to enable the development of
solution(s),
d) thus it has to be created a path towards solution(s),
e) this requires the creation of an instrument to manage the e1) contextual data, e2)
the interpretation of the problem, and e3) the coding of specifications for the
solution(s).
The formulation model consists of the instrument to solve this finite sequence of instructions.
Its framework fits well in the typical workflow of an expert system44, which involves the
following steps (Forsythe & Hess 2001):
a) collecting information from one or more human informants and/or from
documentary sources.
b) ordering that information into procedures (e.g., rules and constraints) relevant to
the operations that the prospective system is intended to perform.
c) designing or adapting a computer program to apply these rules and constraints in
performing the desired operations.
So, one of the most important aspects of the formulation model is how entities are
congregated to accomplish an efficient role in the formulation process.
What is then the role of the model’s entities?
In urban space problems are complex and multifaceted. In general, a model built to respond to
urban problems involves a great amount of entities45 (classes’s46 data) in intrinsic competition
within the definition of its basic structure. The questions involving such a competition are
diverse. One can set a trial question: If contradictory, is an urban rule (from an urban code)
more or less important than a political measure to define a specification? At a first glance, it is
44 . ‘Expert systems are designed to emulate human expertise; they are constructed using computer languages that can represent
and manipulate symbolic information. Each system is intended to automate decision-making processes normally undertaken by a
given human ‘expert’ by capturing and coding in machine readable form the background knowledge and rules of thumb
(‘heuristics’) used by the expert to make decisions in a particular subject area (‘domain’). This information is encoded in t he
system’s ‘knowledge base’, which is then manipulated by the system’s ‘inference machine’, in order to reach conclusions related
with the task at hand’(Forsythe & Hess 2001).
45 . In the urban context such entities (data classes and processes) covers a wide range of matters such as political visions, mandatory policies, participation actions (experts and communities), but they also comprise a data collection process, a cont extual analysis, and a design paradigm. 46 . Classes describe concepts in the domain.
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easy to suppose that such type of problems is out of the model. However, entities have to be
positioned in the formulation structure so as its meaning enables the description of their
precise role. If a role of an entity is not initially (or entirely) described, the formulation model
has to frame it somehow. This means that classes and instances of information that are
distributed and related with each other can impact the way the model functions. So, in a
sense, the model entities are intrinsically the builders of their structure. But there are other
difficulties. One is the range and diversity of the contextual data (rules, recommendations,
existing population, existing morphology, culture, economy, strategies, etc.). The type of
relations established among model entities changes according to the context. Such an
unpredictability amplifies the difficulty to setup a closed chart of formulation rules. Therefore,
theoretically, such a closed system is not viable because knowledge consists of a flexible
structure to enable appropriate activities for specific problem demands. The conclusion is
simple: knowledge acquisition and translation is often problematic (Forsythe & Hess 2001). This
leads one to be faced with a problem. How to deal with model flexibility while, at the same
time, data rules need to be encoded into a machine-usable form?
It is important to a understand that formulation model entails a decision-making process
of data acquisition and translation which calls for the use of a knowledge base model47 (KBS)
here represented by a computational ontology48. Such a particular model provides the basis for
dealing with the problems mentioned above, as explained in Chapter 3.
Then, how to create such an ontology?
As mentioned in Chapter 3 there is no one correct way to build an ontology49. An ontology is a
formal explicit description of concepts in a domain of discourse, and its framework
consists of a data modelling process within a problem-solving method that, in some measure,
depends on assumptions of model’s manager (the formulation ontology engineer).
Assumptions require a clean–up process of precision and accuracy. With precision, the non-
47 . An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins (Noy et al. 2000). 48 . Computational ontologies, in the way they evolved unavoidably mix together philosophical, cognitive, and linguistic aspects. Ignoring this intrinsic interdisciplinary nature makes them almost useless (Guarino 1998). 49 . An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them (Noy et al. 2000).
building a pre-design ontology: towards a model for urban programs
43
intended models are excluded, and with accuracy50 the negative examples are excluded
(Guarino 1998). This means that capturing all intended entities, concepts, and models, is not
sufficient to create a “perfect” ontology.
To create an ontology, one has also to look at its application dominion. It is well known
that cultural frameworks vary widely. Therefore, it is improbable that a sole model functions,
properly, in a wide universe. This constraint demands for the establishment of a limit for the
model’s applicability. For now one will consider the Western culture range. A complementary
issue is the definition of territorial scale to which the ontological model can be applied. The
site planning scale will be the application scale for the intended model.
Framing the ontology
The first approach to the ontology is by means of cognitive domain knowledge and the domain
of discourse, together with a definition of conceptual relations and ontology relations. Such an
approach demands the creation of a conceptual diagram where main model classes are
described. The diagram requires a formal structure of (a piece of) reality as perceived and
organized by an agent, independently of the vocabulary used, and the actual occurrence of a
specific situation, which is the base of an ontological conceptualization (Gruber 2005)51.
The conceptual ontology52 shown in the next page was first developed to be presented
at the eCAADe 2008 conference, and it corresponds to a domain of discourse or a
conceptualization of the urban planning domain. The objective of the elaboration of the
diagram was to organize the concepts and the relations that are established in a very initial
phase of the planning process. Such phase corresponds to the pre-design phase, where the
development and the management of an urban program occur.
The developed ontology model is summarized in Diagram 16 (Montenegro, N. and
Duarte J.P. 2008).
50 . When is a precise and accurate ontology useful? a)When subtle distinctions are important, b) When recognizing disagreement is important, c) When general abstractions are important, d) When careful explanation and justification of ontological commitment is important, e) When mutual understanding is more important than interoperability. 51 . Example of a conceptualization: A conceptualization for D is a tuple C = <D, W, ℜ>, where ℜ is a set of conceptual relations on <D, W>. A model for a language L with vocabulary V is a pair structure <S, I>, where S = <D, R> is a world structure and I: V→D∪R is the usual interpretation function. A model encodes a particular extension interpretation of the language. Analogously, we can encode an intension interpretation by means of a structure <C, ℑ>, where C = <D, W, ℜ> is a conceptualization and ℑ: V→D∪ℜ is an intension interpretation function. We call such a structure K=<C, ℑ> an ontological commitment for L. L commits to C by means of K. C is the underlying conceptualization of K (Guarino 1998). 52 . There is an ontology of the process (how is organized the pre-design phase?) and an ontology of the context and the product (description of the precise context of the urban space, its regulations, its sorted data, and the description of a series of solutions, and guidance).
building a pre-design ontology: towards a model for urban programs
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16. The urban formulation ontology (Montenegro, N. and Duarte, J, 2008)
Now, the description of the diagram
The diagram is organized in two distinct parts:
a) the pre-design phase 1, and
b) the pre-design phase 2.
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In general, in the pre-design phase 1 (PD1) site and population are analysed, as well as general
strategies and constraints imposed on the territory. PD1 corresponds to the input data of the
basic conceptual model. In the end of this first phase, a document53 will synthesise all
collected data enabling its use in the second phase of the pre-design process. Then, in the pre-
design phase 2 (PD2), data is codified towards the creation of specifications for urban design.
Such specifications correspond, in summary, to the urban program. The output of PD2 is,
therefore, the output of the basic conceptual model.
The diagram depicts the different phases of the formulation process, the type of data
manipulated, and the participants involved.
In the gray boxes positioned in the bottom of the diagram are located the crucial components
of the formulation model. These elements encompass core categories of the model that
correspond to diverse functions or tasks. Their related elements are disposed in a vertical line
within the diagram, as the example described below; to the component “stages” corresponds
two different vertical entities:
1. pre-design phase 1, and
2. pre-design phase 2.
This vertical reading dominates over other elements. Overlaid on the described vertical
dominant line co-exists a horizontal reading. Considering the example above, the pre-design
phase 2 is one of the stages of the overall pre-design phase that includes two types of planning
actions/themes:
1. the language, and then to
2. the design patterns.
While the vertical line represents the thematic domains of the formulation process drawn in
chronologic order, the horizontal line embodies a scale decomposition of the necessary
subjects essential to produce an urban program. Both vertical and horizontal readings are
complementary.
53 . The Document Synthesis (DS).
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To facilitate the understanding of the diagram, a set of additional representation aids,
such as arrows and small gray titles, were located among diagram entities to qualify and clarify
their roles in the process (role representation). Moreover, the way arrows are pointing
indicates the action flow that usually occurs between adjacent entities.
Sketching the ontology of the formulation process
Although the structure of Diagram 16 seems clear, it is not entirely precise. The relations
established among PD classes and instances do not correspond to the result of a
computational ontology. On the contrary, the structure of the diagram corresponds to a
conceptual sketch (or a conceptual discourse of the urban domain) to feed the final ontology-
building.
By computing an ontology (using an ontology editor like Protégé), one can assure a high
level of accuracy of the developed model. Such precision drifts from the embedded rules of
the editor that constrain how ontological objects are linked and impose implicit conventions
on their relational status. At the same time, such edition maintains a hierarchical order within
model classes54. It is important to mention that, in future research the diagram components
will be encoded into such a knowledge modelling structure (a computational ontology) to
enable the description of implicit rules in an explicit way.
This means that it is important to establish instances within the model classes in order
to portray value and partnership, defining if an element or entity is part of another one, or if
an entity interacts with another one in some way, or even what an entity “is” following the
description of “what is”.
The diagram 17 shows the sketch of an edition built in the Protégé-Frames editor in
accordance with the Open Knowledge Base Connectivity protocol (OKBC).
The ontology describes PDP (dark green box), PD1, and PD2 (light green boxes) super-
classes, between context and final specifications slots.
54 . The descriptions of such methodology are defined in the third chapter of this research.
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17. PD classes, subclass-superclass hierarchy, slots and instances (in light blue). Bellow the Protégé VizTab
building a pre-design ontology: towards a model for urban programs
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•contextual data
INPUTS
•machine
INTERPRETER
•design specifications
OUTPUTS
The objectives of the fourth chapter are: a) the description of the basic conceptual model, and b) the description of the three parts of the formulation model: b1) the input, b2) the mechanism, and b3) the output.
The basic conceptual model consists of three basic components that represent the three basic functions of the model as shown in Diagram 18:
1) the Input (to read contextual data), 2) the Interpreter (to interpreter received data), and 3) the Output (to describe specifications for design).
data path
data path
18. Urban formulation process (FMo)
The formulation model (FMo) is the detailed structure of the conceptual
model as shown in the ontological Diagram 12 of this research.
04
• basic conceptual model
• formulation model
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The contribution of the fifth chapter for
this research is to describe the
formulation process as well as the
design phase where it occurs – the pre-
design phase. The main objective is to
provide a better understanding of the
formulation framework and, at the
same time, to generate the sketch of its
semantic ground, that is, a consensual
vocabulary to enable appropriate
specifications or the “communication
acts” towards design solutions.
Chapter 5
5. The Formulation Process
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5.1. Introduction
The contribution of the fifth chapter of this research is to describe the formulation process as
well as the design phase where it occurs – the pre-design phase. The main objective is to
provide a better understanding of the formulation framework and, at the same time, to
generate the sketch of its semantic ground, that is, a consensual vocabulary to enable
appropriate specifications (or the “communication acts” (Gandon 2002)) towards design
solutions.
The formulation process corresponds to a specific phase of the design process called
pre-design phase. In short, the pre-design phase consists in a phase of analysis and
interpretation of data that occurs before design begins (Best & De Valence 1999). Usually,
during this phase, studies are done to analyze the context and identify the requirements,
constraints, and opportunities for a given site (McCallum et al. 1996). In general, it also
consists of a set of guidelines to assist planner’s actions.
5.2. Operational structure of the formulation process
The relevance of the pre-design phase becomes apparent when placed in a project scheduling
diagram. PD phase represents about of the overall design process varying in significance
throughout different stages55 (Best & De Valence 1999). PD represents the query phase of the
design process, and its main objective is to facilitate the definition of strategies towards design
solutions. To understand more clearly the purpose of the formulation model it is essential to
observe its different stages.
All starts with a contract that corresponds to an agreement between two parties -
frequently a promoter and a design team. These parties, governed by particular interests,
configure a team searching for specified goals (occasionally dissimilar). The possible existence
of different visions among different parties requires an effort of convergence to benefit the
55 . In fact, the planning process can be present during all design process mainly because it deals with permanent factors such as collaboration, and participation.
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end result. The success of a collaborative environment is therefore crucial for the
accomplishment of formulation goals (Mabert et al. 2003).
Following the contractual agreement, the process usually continues with a definition of a
schedule to implement the necessary steps required for generating the plan. It is important to
mention that the pre-design process frequently extends to the schematic design phase (SDP)
(Alexander et al. 1987) - the phase that follows the pre-design phase. This happens because it
is essential to monitor the development of this early and conceptual phase of the design
process. This means that the formulation process56 corresponds more to an extended course
of action rather than a locked process (Huberman & Miles 1994).
Diagram 19 describes a summary of the conventional main actions of the design process.
19. A planning schedule57
56 . It is also usually called as the programming phase (or framework) of the design process. 57 . The Bid phase described in the schedule corresponds at the following concept: Design-bid-build (or design/bid/build, and
abbreviated D-B-B or D/B/B accordingly), also known as Design-tender (or "design/tender"), is a project delivery method in which
the agency or owner contracts with separate entities for each the design and construction of a project. Design-bid-build is the
traditional method for project delivery and differs in several substantial aspects from design-build. There are three main
sequential phases to the design-bid-build delivery method: 1. The design phase, 2. The bidding (or tender) phase, and 3. The
construction phase.
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5.3. The formulation phases
It seems that the formulation process includes two different main phases:
a) pre-design phase 1 (PD1) and
b) pre-design phase 2 (PD2).
How and why such phases are subdivided from the generic pre-design phase?
In general, the division into different parts writes to a method of simplification. The main idea
behind this method is - divide a problem (PDP) into sub-problems (PD1 and PD2) of the same
type58 to simplify and explicit the problem domain.
As a computer programming technique this is called divide and conquer (dialecting59),
and it is key to the design of many important algorithms, as well as a fundamental part of
dynamic programming.
The division of the formulation process into different parts (here represented by its
phases) has an additional logic - it corresponds at two different conceptual sub-dominions of
the formulation framework, as is shown in the diagram 16;
a) A data acquisition phase (that occurs in the PD1) and,
b) A data translation phase (that occurs in the PD2).
Data acquisition corresponds to a phase where contextual data (site and population as
well as strategies politically framed and existing regulations) are acquired (Kay 1984). This
phase is crucial to identify the essential ingredients that will constitute the formulation
database.
Data translation corresponds to the creation of the set of specifications to describe a
solution (or a set of solutions) by applying rules that link contextual data to programmatic
features, that is, the translation of the contextual data (from the formulation database) into
design specifications. The idea is to build-up such specifications under the form of patterns
58 . Such type of division will be implemented throughout all formulation process where divided parts will describe sub-classes of
super-classes of the overall process (here refer to as an ontology).
59 . Dialects are domain specific sub-languages of a programming language or a data exchange language. (See also Grammar-
oriented programming, Language oriented programming, Reflection and Metaprogramming.) A language supporting this paradigm
encourages users to create new dialects for specific problematic domains.
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des
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(so
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according to Alexander’s formalities (Alexander 1979). The rules are inferred a priori for a
general context, say, Portuguese urban environments, and then applied to a specific context,
that is, a specific site and its surroundings. The ultimate goal of this research is to infer such
rules.
In this chapter, it will be presented, when necessary, a simplified version of the
ontological Diagram 16 to explicit the main phases and processes of the formulation
framework. In the first simplified diagram reproduces below are highlighted (in black text) the
different phases of the pre-design phase – the PD1 (data acquisition) and the PD2 (data
translation).
20. Pre-design phases – the PD1 (data acquisition) and the PD2 (data translation)
5.4. Categories enclosing the main processes of the pre-design phase
The categories shown in Diagram 21 are to ontological super-classes that correspond to two
information acquisition and processing phases that occur during the formulation process; in
the first phase the goal is to analyze the context (PD1), in the second phase (PD2) it is to
develop specifications to guide the planner’s design process.
There is a conventional hierarchy in the use of that information.
Normally, in the PD1, the first required data (that will guide and constraint the other
categories of information) is composed by the set of political strategies defined for a territory
under study (I). The second data category usually includes urban regulations that are
PD1 data acquisition
strategic plans
site andpopulation context
urban codes and guidelines
PD2 data translation
pattern language
'specifications for design'
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(so
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applicable to the intervention site (II), and the third one is a portrait of the site and population
(III).
In the second phase (PD2) there is only one category group that is used to translate the
PD1 database into a set of specifications encoded as urban patterns (IV).
Despite the description above, the hierarchy of the described categories can changed
according to specific demands of the problem (such as particular procedures undertaken,
involved parties, or strategic procedural recommendations, etc.).
21. The four categories of the formulation process
Now, a closer look at each one of the categories, starting by the formulation strategies.
5.5. Strategies
Strategies consist of the first category of the pre-design phase 1 (PD1) and are related with
high level decisions that are usually taken even before the intention of producing a particular
plan is completed. Strategies are crucial in the implementation of urban programs because
they represent a crucial benchmark towards sustainable development.
The outcome of an urban design process is an urban plan. So, in urban design the resulting
design is delivered in the form of a plan, and one of the top requirements for urban plans is
the definition of a strategy, to identify the main purposes of the plan (Ulrich & Eppinger 2003).
PD1 data acquisition
strategic plans (I)
urban codes and guidelines(II)
site and population context (III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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How to manage strategy in the ontology?
The flow between strategies and design can collapse if strategies reveal insufficiency,
ambiguity, or inaccuracy within its conceptualizations (Gruber 1991). The creation of a
computational ontology helps to surpass this difficulty as its main goal is to disambiguate60 by
means of an inference61 machine that attains at data consistency (Caneparo et al. 2007).
Therefore, there is a clear advantage in the use of a knowledge modelling62 structure (in this
case an ontology) to frame a plan’s strategies. Above all, an ontology can avoid ambiguities
within design outcomes and, at the same time, it can reinforce its accuracy.
The chain seems to be clear. Designs well supported by precise and proficient strategies
(or development visions) lead to better plans.
What are the subject matters behind a plan’s strategies?
Strategies are framed by political visions supported by national and regional policies
established for territories (Graham & Marvin 2001a). The economic, the cultural, and the social
foci in urban communities correspond to core components of such policies (Herrschel & P.
Newman 2002b). These policies are difficult to capture in the formulation database model. The
main reason for such difficulty stems from the variable character of policy which changes
according to the nature of the administration. Political parties hold particular conceptions
about governance and management of spatial resources. This has a direct influence on the
definition of urban programs and thus on plans. Strategies also work at different scales. In
abstraction, strategies may start with policies endorsed to vast regions and may end in rules or
60 . In computational linguistics, word sense disambiguation (WSD) is an open problem of natural language processing, which comprises the process of identifying which sense of a word (i.e. meaning) is used in any given sentence, when the word has a number of distinct senses (polysemy). The solution of this problem impacts other tasks of computation linguistics, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference, and others. Research has progressed steadily to the point where WSD systems achieve consistent levels of accuracy on a variety of word ty pes and ambiguities. A rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date (Navigli & Velardi 2005). 61 . Inference is the process of drawing a conclusion by applying rules (of logic, statistics etc.) to observations or hypothesis; or by interpolating the next logical step in an intuited pattern. The conclusion drawn is also called an inference. 62 . Knowledge management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. An established discipline since 1991 (see Nonaka 1991), KM includes courses taught in the fields of business administration, information systems, management, and library and information sciences (Alavi & Leidner 1999). More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy.
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recommendations at the urban site scale covering a wide spectrum of influence. At site scale,
strategy represents the very initial step towards the implementation of the plan. However site
strategies also entail a higher sphere of decision that usually defines a development path for a
wider region (Evans et al. 2007). Such path focuses on a site within a region (a “part” within
“whole”). The purpose is to obtain a territory balance surpassing the neighbourhood scale
range (J. C. Moughtin et al. 2003).
When this process starts?
An important aspect concerning planning actions is related with the necessity of defining a
plan’s strategy before planers start their design conceptions. Planners have to consider the
demands of the strategy to fit the design into the strategy’s goals.
What is the role of planners in this process?
If one states the problem in a plain and rhetorical way, on one side of the formulation process
stands the promoter, public or private, with a particular set of goals and, on the other side,
complementarily, stands the planer with its particular design approach. The first has the
responsibility to conceive the macro strategy and the general confinements for the plan. The
second has to collect data from the defined strategy and the plan’s confinements to transform
it into spatial solutions, supporting these on design guidelines. However, the involvement of
planners in the development of plans varies according to the context. Planners are usually
skilled to participate throughout the formulation of the program and in the creation of designs.
However, they also can participate in the elaboration of strategic plans contributing within an
ample participative process (Graham & Marvin 2001b).
How to elaborate a strategy?
One can say there is no universal formula to define a strategy. The existing
methodologies are varied, however, the instruments that regulate the elaboration of strategic
plans are relatively well known.
What is then a strategic plan?
A strategic urban plan63 (SUP) is a planning instrument that holds in its framework a wide
number of subjects to inquire (McCallum et al. 1996). Such variety requires the use of a
multiplicity of methodologies and tools to identify and clarify the subjects focused on
63 . A strategic plan lets an organization know where they are now and where they want to be some time in the future.
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population and site features (Healey 1997). At the core of the strategic outline are placed the
economic, the cultural, the social and the political features, frequently identified using tools
like SWOT (Strengths, Weaknesses, Opportunities, Threats) depicted in Diagram 22, and PEST
(Political, Economic, Social, and Technological analysis) methods. In addition, other tools may
be use to deal with complementary matters such as “PERS (Pedestrian Environment Review
System) by TRL Software (http://www.trlsoftware.co.uk/: May 2008) or “Design Quality
Analyser” by CABE (http://www.whichplaceswork.org.uk/: May 2008)”, (Gil 2008) amongst
others.
Despite its relevance. SUP methods are not generalized in urban design processes yet.
22. SWOT analysis - the strengths, the weaknesses, the opportunities, and the threats.
SUP is today considered a type of Governance. According to Borja and Castells (1998), “the
definition of a city project that unifies diagnoses specifies public and private actions and
establishes a coherent mobilization framework for the cooperation of urban social actors. A
participative process is a priority when defining contents, as this process will be the basis for
the viability of the objectives and actions proposed. The result of the Strategic plan should not
necessarily be the creation of regulations or a government program (although its adoption by
the State and Local Government should mean the instigation of regulations, investment,
administrative measures, policy initiatives, etc.) but rather a policy contract between public
institutions and civil society.”
What are SUP’s assessment instruments and methodology?
Strategic plans are framed by specific frameworks towards the definition of a plan’s
purposes (Mintzberg 2000b). Usually they consist of the following five main concepts:
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1) Vision – to define the vision / to set a mission statement with a hierarchy of goals;
2) SWOT – to analyse according to the desired goals;
3) Formulate64 - to prepare actions and processes that can be taken to attain these
goals;
4) Implement – to implement of the agreed upon processes; and
5) Control – to monitor and get feedback from implemented processes to fully control
the SUP operation.
There are a number of ways to develop SUP’s but typically a three-step process may be
used to support the development of the mentioned concepts above (Mason & Mitroff 1981):
1) Situation – to evaluate the current situation and how it came about,
2) Target – to define goals and/or objectives (sometimes called ideal state),
3) Path – to map a possible route from the goals to the objectives.
One alternative approach is called Draw-See-Think;
1) Draw – where the key question is: what represents the ideal image or the desired end
state?
2) See – setting the relevance of observing reality: what is today's situation? What is the
gap from ideal and why?
3) Think – defining a prospective path: what specific actions must be taken to close the
gap between today's situation and the ideal state?
4) Plan – and finally, how to make it: what resources are required to execute the
activities?
An alternative to the Draw-See-Think approach is called See-Think-Draw;
1) See - what is today's situation?
2) Think - define goals,
3) Draw - map a route to achieving the goals.
The diagram 23 depicts strategies as the initial phase of the pre-design process (PD1).
Moreover an example of SWOT and PEST tables is presented in Annex 3.
64 . Formulate corresponds here to a precise term used in SUP theory.
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23. Strategies shown in the simplified diagram (highlighted in black text and box).
5.6. Regulations
Now, a closer look at the description of the second category of the formulation model -
regulations.
In summary, regulations consist of a compilation of urban rules, codes, standards, and
sorted requirements (Carmona et al. 2006). An important aspect related to its nature is the
width of its application.
Such aspect set a difficulty.
Urban rules generally differ from country to country, and from site to site within particular
geographic locations. In fact, this variation can be extended to the universe of cultural contexts
which comprise an infinity of variables. To solve width and differentiation one can search for
agreed upon rules applied to vast regions of the globe as the regulations applied to the
European Union (EU). However the dilemma remains. The EU is just a part of a wider universe
of urban realities and cultures, and additionally its administration largely lacks the legal means
to enforce regulations. This occurs since the “EU policy is mainly focused on structural policies
to regulate international trade and economic markets, employment, and industry sectors” (Hix
1999).
How rules are defined?
Rules usually depend on policy within state administrations, however social involvement of
communities in the definition of specific constraints or rules for plans, can add performance
into plans by adequating designs to community’s particularities (Harvey 2009). Such
PD1 data acquisition
strategic plans (I)
urban codes and guidelines
(II)site and population context
(III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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community participation generally occurs during the SUP framework or following it, in the
definition of the plan’s final layout. However, it can also occur in other phases of the pre-
design framework as in the definition of urban rules to apply in the development of particular
plans.
Meanwhile one can argue that such processes involve several formalities and nuisances.
For now it will be just acknowledged the relevance of such a participation process.
Who should be involved in such a participation process?
In fact, all society can be involved in participation but some civil sectors seem to receive more
direct benefits with the application of regulations or design-codes than others. Thus they are
able to contribute with additional knowledge that can bring benefits to plans requirements as
a result of their particular visions and experiences.
Traditionally such sectors are composed by landowners, developers, local authorities, as
the community in general (represented by individuals or a committee) (Evans et al. 2007).
Table 1 shows the mentioned participants and the roles that they play in the
formulation framework.
1. Benefits of design regulations (Evans et al. 2007)
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In future research it will be elaborated a catalogue of regulations within a case-study. The
objective is to create a consensual directory of standards. Such directory will represent a
particular universe giving the prototype model of the formulation process some accuracy. Such
directory will be organized into modules that can be retrieved and manipulated by planners to
inform the development of a particular plan.
In general the directory will contain a sort of regulatory controls (includes on-site and
off-site considerations) such as:
a) LRDP land-use designation,
b) urban codes and requirements,
c) precinct or area plans,
d) site zoning and surrounding area zoning,
e) existing land-use type and density,
f) permitted uses and exemptions,
g) deed restrictions and covenants,
h) setbacks (lot coverage, and height limitations),
i) parking requirements, and
j) signage requirements.
The diagram 24 shows the regulation’s box that follows the strategies box in PD1. In Annex 4
are presented some core attributes, which are usually necessary to apply regulations.
24. Regulations and codes shown in the simplified diagram (highlighted in black text and box)
PD1 data acquisition
strategic plans
(I)
urban codes and guidelines(II)
site and population context
(III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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5.7. Site and population context
Site and population data is normally acquired during (or as sequence of) the strategic phase
(Rogers & Vertovec 1995). In such a phase, if the SUP defines, for example, a specific goal
towards the increasing of social cohesion within a plan. A planner may also want to extend or
transform SUP defined goals to respond to other needs of the plan. In this case is important to
maintain a high level of flexibility within the formulation model so that management of the
formulation database (by planners) can be made in a flexible and extensive way.
The selection of such data is basically built on:
i) population statistics, and
ii) site analysis (sub-divided into ii1, ii2, ii3, and ii4).
Now, let us take a closer look at each of the data groups.
i) Population statistics
A relevant part of population data can be directly gathered from national and international
statistical institutes, (UNESCO) 2009; Balachandran 1980) which generally provides for vast
amounts of information related to people. Usually such information supports community’s
characteristics where profiles are ordered by age, ranges, skills, professions, genders,
economic stratification, etc. This information is frequently well supported by relational65
diagrams that help the visualization of data correlation66. Data correlation can be managed by
the organization of features into charts in order to express specific values that can be divided
by timeline periods. These diagrams portray global tendencies (Chenery & Taylor
1968)(Montgomery 2008) to define or correct planning streams.
65 . A relational database matches data by using common characteristics found within the data set. The resulting groups of data are organized and are much easier for people to understand. 66 . A correlation function is the correlation between random variables at two different points in space or time, usually as a function of the spatial or temporal distance between the points. If one considers the correlation function between random variables representing the same quantity measured at two different points then this is often referred to as an autocorrelation function being made up of autocorrelations. Correlation functions of different random variables are sometimes called cross correlation functions to emphasize that different variables are being considered and because they are made up of cross correlations. Correlation functions are a useful indicator of dependencies as a function of distance in time or space, and they can be used to assess the distance required between sample points for the values to be effectively uncorrelated. In addition, they can form the basis of rules for interpolating values at points for which there are observations.
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Population represents a crucial factor towards the definition of a plan which is quite
simple to explain. Urban space is designed by people and for people. Communities are the
main purpose and the main constraint of a plan - its first ingredient. Therefore population
characteristics determine and deeply influence spatial configurations.
ii) Site analysis67
Site analysis is the second top group of contextual data, which consists of a crucial task
of the pre-design process implying spatial perception (Pereira 1996).
Such a relevance is easy to depict.
Space is perceived, apprehended, and seized by humans. Lynch (1960) wrote that users
understood their surroundings in consistent and predictable ways by forming mental maps. By
providing a framework to take this world of visual and formal perception into account, Lynch’s
“The Image of the City” has had important and durable influence on the field of urban
planning. Today’s methods of site analysis, deeply embedded in Lynch’s principles, are
elaborated through a collection of visual annotations, and interpreted through simple
statistical charts. Nevertheless, such a process reveals a variety of flaws due to cognitive
constraints on the behalf of the observer.
Site analysis is also extensive. To explicit its different implications and methods one
presents a partition within four types of site analysis.
The first is based on a method to read the image of an urban area (Pereira 1996), as
described in following.
ii.1) Site Analysis (The image of the city)
According to Pereira (Pereira n.d.), the analysis an urban area needs to take into account:
1) a global interpretation,
2) the problems and potentials,
3) the urban character,
4) the dynamics of transformation, and
67 . The analysis phase is a chronological step of the design process. This step involves programming the site as well as site and user analysis, which is focused on in-depth below. There are numerous site elements related to the analysis during this phase.
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5) the objectives, the politics, the strategies, the solutions, and intervention actions.
Such site scrutiny requires a methodology of implementation, that is;
a) the preparation of a technical team,
b) the organization of its actions, and
c) the compilation of assessment studies.
In general, this type of analysis starts from the description of the urban context (Rogers &
Vertovec 1995), namely through the description of its morphology, the stages of its historical
evolution and urban demography, its social-economic growth, its accessibilities, its general
distribution of population and land uses, its landmarks (centrality, historical, and touristic), its
planning strategies, and its urbanization plans and public works (existing or approved, its
constrains and commitments).
Its fieldwork68 usually involves the use of cartography and photography, toponymic
analysis, street interviews and registration of opinions through blogs, sites or other media,
noise levels registration (in the case of an absence of noise-charts these data are registered
directly on site), etc. The use of complementary studies also helps on data collection in matters
such as landscape morphology (plateaus, lines of the landscape, slopes, three-dimensional
representation of land), urban historical evolution (the stages of urban formation, the
demassification and growth of the urban structure), social patterns, ideals and the models of
city, social-economic characterization of the population (age, composition of the families,
activities), neighbourhood relationships, as well as the forms of access to the interior of the
urban site under study.
The physical and visual inspection of the site is considered a crucial step in this type of
urban analyses. There are several aspects that need to be taken into account in the analyses,
namely;
1) the recognition of approach pathways,
2) the definition of the site peripheral edge,
3) the recognition of connections with the surroundings,
68 . Field work is a general descriptive term for the collection of raw data. The term is mainly used in natural and social sciences
studies. It is more technically known to scientific methodologists as field research. Field work, which is conducted in situ, can be
contrasted with laboratory or experimental research which is conducted in a quasi-controlled environment.
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4) the morphologic continuities and discontinuities, and
5) the observation of distant focal points.
Such analysis follows the elaboration of a chart list (Pereira 1996) that can be described as
follows:
a - Site Data
a1 Morpho-typological structure:
a1.1 Land form and features (topography: slope and aspect).
a1.2 The formation bases of the urban structure (site morphology and
historical evolution),
a1.3 Land use (general indicators of land use),
a1.4 Urban mesh (grids and their orientation, mesh geometry, public spaces
network),
a1.5 Urban space (public space, private space and semi-public space),
a1.6 Built space (building construction dates, types of construction, current
and state of conservation, typologies, patrimony, delimitation of rundown
areas, costs, regeneration strategies).
a2 Active structure: Activities during the day, night and weekends:
a2.1 Housing, equipment, public administration and economic activities,
a2.2 Transportation, parking, loading docks and circulations,
a2.3 Leisure, culture and exchanges.
a3 Social structure:
a3.1 Characteristics of the population: Socio-economic, age and ethnic
groups69,
a4 Significant structure:
a4.1 System of orientation,
a4.2 Axes,
a4.3 Focal points,
a4.4 Passages,
a4.5 Reference areas,
69 . a) 3.1 can overlap with content in i), population statistics. One of the tasks of the Protégé 2000 Editor is to clean up such type
of occurrences in order to prevent ambiguities.
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a4.6 Tourist routes.
b - Urban furniture and symbols, plant and animal species:
b1 Illumination,
b2 Culture and leisure,
b3 Information and orientation,
b4 Services to the community,
b5 Security,
b6 Vegetal and animal species.
c - Urban character:
c1 Sequences of public spaces,
c2 Sequences of façades,
c3 Significant details,
c4 Pallet of colors,
c5 Human environment,
c6 Environment of the installed activities and circulation,
c7 Sound and light environment,
c8 Vegetation and landscape.
d - Urban Dynamics:
d1 Modernity or traditionalism of the activities,
d2 Socio-economic contrasts.
e - Climate:
e1 Prevailing winds (direction and velocity),
e2 Solar orientation (including shade and shadows),
e3 Temperature ranges and seasonal norms,
e4 Humidity,
e5 Precipitation.
f - Environmental influences:
f1 Noise levels,
f2 Odors,
f3 Fumes,
f4 Dust,
f5 Smoke from adjacent sites,
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f6 Air quality,
f7 Vibration, and
f8 General nuisances.
ii.2) Site Analysis (Data Mining)
Data mining comprise a very specific type of site analysis related with the use of technology.
The relevance of its methodology and specificity calls for its description.
What is then Data Mining?
A data mining (DM) process is “characterized by a recursive withdrawal procedure
enthused by a statistical platform towards data emergence, and is commonly used to perform
three main tasks” (Fayyad et al. 1996):
1) Classification - arranging the data into predefined groups,
2) Clustering - where the groups are not predefined and the algorithm tries to group
similar items together, and
3) Regression - to find a function which models the data with the least error.
Technically data mining is the process of finding correlations or patterns among dozens of
fields in large relational databases. The relevance of these techniques to the planning process
is that they allow users to analyse data from different angles, categorise, and summarise the
relationships identified. Data mining seems to facilitate the discovery of patterns that would
be difficult to reveal in a complex urban space, today controlled by a bursting environment of
economic and social phenomena.
ii.3) Site Analysis (Space Syntax and other methodologies - Hillier, 1984)
This group embraces another important chapter in spatial analysis.
Space syntax is based on linear representations of space (desire lines theory) through
definitions of lines and segments (axial mapping methodology). One of the methodologies
used by space syntax (SpS) is characterized by network measurement through graphs
representations. The results of the applied theory seem to provide accurate results that are
essentially focused on social and traffic assessment. The aphorism of the space syntax (Bafna
2003) is based on visual space perception and physical space recognition; “to see how much
we can learn about (…) surroundings without taking into account intent” , defining as main
subjects under study; “moving people, bicycles or vehicles”. The method usually encloses a
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number of street locations covering a range of well-used, moderately-used and poorly-used
spaces, in and around a defined area of study. SpS methodology identifies a set of “gate”
positions. “The more gates, the more accurate the picture of movement patterns” (Batty 2004).
Finally, it defines a simple procedure, by “stand at each gate position and draw an imaginary
line crossing the street space (the line should be at a right angle to the direction of the street)
(see map and observation sheet 2). Those gates are spots where one will count the people or
vehicles that cross this line for a set period of time. Some of the instructions are; “Count only
the people or vehicles that have crossed the line. The time periods vary from 2.5, 5 to 7.5
minutes depending on the busyness of the area: shorter times for busy areas and longer times
for quieter areas. The time period should be as precise as possible down to the nearest
second. Always record the time period. This is so that when times are multiplied up to arrive at
rates per hour no mistakes are made” (Hillier et al. 1976).
2. Gate Counter Map and Observation sheet example.
ii.4) Site Analysis (Measuring quality)
The last group of site analysis is focused on quality standards. It states that “measuring quality
means involving a variety of interested people to define how well a space works. Through this
process one can learn about requirements of different groups of people to understand if their
needs are being met. It will identify both good and bad characteristics and stimulate new ideas
for improvements and how it could be managed” (Dempsey 2008). This process will help to
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develop good relations between users and people who run space and will help one prioritise
improvement. By measuring quality70 one is basing such decisions on good evidence.
In summary the existing tools for measuring quality can be used for:
a) identifying the strengths and weaknesses of a space,
b) establishing what is most important to people,
c) comparing different people’s views,
d) measuring how well the space meets everyone’s needs,
e) stimulating new ideas for improvements,
f) tracking changes in people’s views over time,
g) bringing staff and users together in a structured way to discuss the space (Hurley et
al.)
The use of Site Analysis within the formulation model.
The techniques used in SUP’s and in the site analysis phase, involving this type of information,
can be similar despite the different moments in which they occur during the pre-design phase.
The question concerning the necessity of covering twice the same problems using similar
methodologies (in SUP and in the Site Analysis) needs to be addressed by the participants of
the plan that should decide if the sources of the SUP are sufficient or even if they should be
presented taking into account the specific requirements of the design and pre-design phase.
Finally, the diagram 25 represents the site and population contextual data acquisition as
the last process of the pre-design phase 1 (PD1). Once more it can be mentioned that order of
the processes described in the diagram can be structured differently, according to the plan’s
specificity.
70 . A quality (from Latin qualitas) is an attribute or a property. Attributes are ascribable, by a subject, whereas properties are
possessible. Some philosophers assert that a quality cannot be defined. In contemporary philosophy, the idea of qualities, and
especially, how to distinguish certain kinds of qualities from one another remains controversial (Thomson et al. 2003).
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25. Site and population contextual data shown in the simplified diagram (highlighted in black text and box)
5.8. Document synthesis
There is too much information for analysis?
The wide-range of matters under analysis seems to be endless, sometimes confusing and
frequently overlapping. Such extended data is difficult to understand in order to organize and
select. The task is especially hard when such information is manipulated by several parties with
different visions about its management.
The data from the analysis phase is useful for the plan’s stakeholders only when
inclusive, limited and precise. Though is crucial to have the perception of what to do with it.
So, how to deal with such an amount of information?
In this phase, it is essential to elaborate a final document to summarize all the compiled data.
This document is usually called synthesis document (SD) and its structure is defined by: a)
objectives, guidelines and strategies, as well as b) a formulation of hypotheses towards
implementation.
Pereira (1996) recommends a set of five instructions to define SD’s.
a) the first describes the need to elaborate general cost estimates and execution phases
for the plan,
b) the second defines all formulation rules for implementation on site,
c) the third defines the financial resources required to implement the plan,
d) the fourth identifies the social participants involved in such implementation, and
PD1 data acquisition
strategic plans
(I)urban codes and guidelines
(II)
site and population context (III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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e) the fifth develops a series of public discussions through media (meetings, blogs, etc.).
What are the data attributes?
It is difficult to describe with precision what represents (in a moment) each contextual entity
because it changes according to the plan’s requirements. However, is possible to describe a
relatively consensual database of their related attributes71.
Annex 4 provides a list of attributes related to contextual data, including their proposed
codes, the description of their types, their reference values, their data sources, and also their
related calculations. The tables express a set of attributes usually used in Buildings, Blocks,
Plots, and Streets configurations. Such tables were developed as the database for data-mining
research (Gil et al 2009).
5.9. Planner’s Language – pattern language
This category of the formulation process is located in the second phase of the pre-design
process – the PD2, and it is essentially related with the description of design specifications.
A first question arises immediately concerning this topic.
The development of the formulation database seems to reduce the role of planners in decision
making concerning the planning actions. In contrast, planners are crucial elements in the
management of the formulation model, as they can also act as its system engineers (the
administrators of the formulation ontology and its rule based system). The idea is that some
balance can be made.
Another important role of planners is to achieve consensus amongst stakeholders by
harmonizing different visions regarding a site. Consensus is hard to manage specially before
the wideness of participants possessing dissimilar interests. Table 3 and 4 gives one a notion
concerning stakeholder’s roles, as well as their short-term value/ long-term value within a
plan’s development. This management consists, largely, of a planner’s language the planner’s
communication acts.
71 . The word ‘attribute’ can express: in philosophy - property, an abstraction of a characteristic of an entity or substance; in social sciences - a characteristic of a variable; in linguistics - a syntax unit, either a word, phrase or clause, that modifies a noun; in computing - attribute (computing), a factor of an object or other kind of entity.
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3. Participants in the planning process (Evans et al. 2007) – part 1
4. Participants in the planning process (Evans et al. 2007) – part 2
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During the second pre-design phase planners are called to produce the largest part of their
work before starting the design of a plan. It is a complex activity involving different knowledge
domains, some linked to personal assumptions72.
Planners communicate their ideas by a sort of language, a planning language composed
by; a) a particular lexicon73 (built of patterns), b) a specific organization (syntax74), congregating
a c) group of intentions (a semantic corpus).
This language will determine the structure of the design specifications.
Diagram 26 shows the location of the planning language box (the planner´s pattern language)
in the overall pre-design process - phase 2 (PD2). This process is further described in the
Chapter 6.
26. Pattern language “specifications for design” shown in the simplified diagram (highlighted in black text
and box)
72 . An assumption is a proposition that is taken for granted, as if it were true based upon presupposition without preponderance of the facts. Assumption may also refer to: in logic, natural deduction systems are defined as an assumption is made in the expectation that it will be discharged in due course via a separate argument; in mathematical modeling it can be used to map the outcome of different assumptions on the system being modeled. 73 . In linguistics, the lexicon (from the Greek: Λεξικόν) of a language is its vocabulary, including its words and expressions. More formally, it is a language's inventory of lexemes (Podgorski 2008). 74 . In linguistics, syntax (from Ancient Greek σφνταξις "arrangement" from σφν syn, "together", and τάξις táxis, "an ordering") is the study of the principles and rules for constructing sentences in natural languages. In addition to referring to the disc ipline, the term syntax is also used to refer directly to the rules and principles that govern the sentence structure of any individual l anguage, as in "the syntax of Modern Irish. Modern research in syntax attempts to describe languages in terms of such rules. Many professionals in this discipline attempt to find general rules that apply to all natural languages. The term syntax is also s ometimes used to refer to the rules governing the behavior of mathematical systems, such as logic, artificial formal languages, and computer programming languages (Santorini & Kroch 2000).
PD1 data acquisition
strategic plans
(I)urban codes and guidelines
(II)site and population context
(III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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This chapter describes the formulation process as well as the design phase where it occurs – the pre-design phase.
The main objective is to provide a better understanding of the formulation framework and, at the same time, to generate the sketch of its semantic ground, that is, a consensual vocabulary to enable appropriate specifications (or the “communication acts” towards design solutions. The main categories of information that compose the framework are:
1. Strategic plans 2. Codes and guidelines 3. Contextual data 4. Specifications for design.
27. The diagram shows the four different categories of the formulation process. Each one enclosing a
crucial process within the pre-design framework (black text and boxes).
05
• detailing each category of the pre-design-phase
PD1 data acquisition
strategic plans (I)
urban codes and guidelines(II)
site and population context (III)
PD2 data translation
pattern language
'specifications for design'
(IV)
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The chapter 6 explores the most
important category of the
formulation model: the
systemic language that is used
by planners to formulate urban
solutions, in short, the planner’s
language.
Chapter 6
6. The Sketch of a Planning Language
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6.1. Introduction
Language, like a seed, is the genetic system which
gives our millions of small acts the power from the
whole (Alexander et al. 1977).
The chapter 6 explores the most important category of the formulation model: the systemic
language that is used by planners to formulate urban solutions, in short, the planner’s
language. When a designer is designing something, whether it is a house or a computer
program or a stapler, s/he must make many decisions about how to solve problems. A single
problem, documented with its most common and recognized good solution seen in the wild, is
a single design pattern. Each pattern has a name, a descriptive entry, and some cross-
references, much like a dictionary entry. A documented pattern must also explain why that
solution may be considered a good one for that problem, in the given context.
How to describe such a language?
The description of a specific domain language beyond natural languages requires an
appropriate disclosure of its specific system. The first step to find out how language is
structured is by searching deep its semantic field, here consisting of particular meanings
encoded in the form of patterns. Another complementary way is to explore the structure of
language in the way subjects are described (in multiple combinations), to understand how
logic is created.
To better understand this process is important to discover the way natural languages
function.
6.2. The nature of language
Language is a system of signs to express meanings - a simple algorithm to produce
communication. What seems to be interesting in the universe of communication is the analogy
that can be established between different fields of knowledge that seem to be linked by
equivalent concepts. This seems to be the case of the planning language and the linguistics
theory.
Natural language is composed of a sort of definitions supported by:
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a) a syntax and
b) semantics.75
While syntax corresponds to structure, semantics is associated with meaning (Chomsky 1965).
Together they compose a medium for communication - a definition that seems to fit in the
description of the planning language. Such a link was established in the ‘70s by Christopher
Alexander (1977) who inspired by natural languages attempted to adapt the linguistics76
concept to planning.
6.3. Semantics and Syntax
Now, a closer look at the main components of language.
In summary, language is composed by:
a) syntax, which contains Classes - taxonomies of “speech” (ideas / semantic level),
Inflections - changes or mutations of the language ingredients, and Codes - description
of possible combinations, and
b) semantics, which is based on cognitive schemas that are mental models of different
aspects of the world, containing knowledge, opinions, suppositions, associations, and
expectations.
75 . Semantics is the study of meaning, usually in language. The word "semantics" itself denotes a range of ideas, from the popular to the highly technical. It is often used in ordinary language to denote a problem of understanding that comes down to word selection or connotation. This problem of understanding has been the subject of many formal inquiries, over a long period of time. In linguistics, it is the study of interpretation of signs or symbols as used by agents or communities within particular circumstances and contexts. Within this view, sounds, facial expressions, body language, and proxemics have semantic (meaningful) content, and each has several branches of study. In written language, such things as paragraph structure and punctuation have semantic content; in other forms of language, there is other semantic content. The formal study of semantics intersects with many other fields of inquiry, including proxemics, lexicology, syntax, pragmatics, etymology and others, although semantics is a well-defined field in its own right, often with synthetic properties. In philosophy of language, semantics and reference are related fields. Further related fields include philology, communication, and semiotics. The formal study of semantics is therefore complex. Semantics is sometimes contrasted with syntax, the study of the symbols of a language (without reference to their meaning), and pragmatics, the study of the relationships between the symbols of a language, their meaning, and the users of the language (Yule 2006). 76 . Linguistics is the scientific study of natural language. Linguistics encompasses a number of sub-fields. An important topical division is between the study of language structure (grammar) and the study of meaning (semantics and pragmatics). Grammar encompasses morphology (the formation and composition of words), syntax (the rules that determine how words combine into phrases and sentences) and phonology (the study of sound systems and abstract sound units). Phonetics is a related branch of linguistics concerned with the actual properties of speech sounds (phones), non-speech sounds, and how they are produced and perceived. Other sub-disciplines of linguistics include the following: evolutionary linguistics, which considers the origins of language; historical linguistics, which explores language change; sociolinguistics, which looks at the relation between linguistic variation and social structures; psycholinguistics, which explores the representation and functioning of language in the mind; neurolinguistics, which looks at the representation of language in the brain; language acquisition, which considers how children acquire their first language and how children and adults acquire and learn their second and subsequent languages; and discourse analysis, which is concerned with the structure of texts and conversations, and pragmatics with how meaning is transmitted based on a combination of linguistic competence, non-linguistic knowledge, and the context of the speech act.
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The language is also structure by a sort of combinations, namely by:
b1) structuring sounds into digitized segments (phonemes) which are sequenced into
fixed combinations (words/morphemes);
b2) treating these sequences as symbols for concepts (meanings) that can be used in
many different situations; and
b3) organizing sequences of words/morphemes into hierarchical phrases and sentences
(syntactic structures) whose meanings are constructed systematically from the
meanings of the words (Chomsky 2002).
Alexander’s pattern language (PL) (1977) is organized in a similar way despite its specific
vocabulary involving space and people, public and private, natural and artificial things and
concepts. As natural languages, PL morpho-syntax describes the elements of language. For
example, PL number 19 relates to shops, people needs, centres, services, and then organizes
them into a simple sequence of meanings (three interdependent concepts); “catch basis”77 for
services to serve people’s needs. At the end, it sets a design solution; the creation of a “web of
shopping”.
In what consists PL structure?
Alexander considers that planning language has a more complex functioning than a tree of
hierarchies as proposed by Chomsky for natural languages (Chomsky 1965). For Alexander
such a tree does not explain language usage, since language seems to depend much more on
the type of selection of the lexicon to produce particular results that express particular
meanings. Alexander calls it semi-reticulated language due to its recursive and combinatorial
system based on user multiple choices and heuristics.
Diagram 28 represents a Chomsky’s tree structure78 hierarchy for natural languages,
dissimilar from Alexander’s PL.
77. Alexander’s expression. 78 . A tree structure is a way of representing the hierarchical nature of a structure in a graphical form. It is named a "tree structure" because the classic representation resembles a tree, even though the chart is generally upside down compared to an actual tree, with the "root" at the top and the "leaves" at the bottom. In graph theory, a tree is a connected acyclic graph (or sometimes, a connected directed acyclic graph in which every vertex has indegree 0 or 1). An acyclic graph which is not necessarily connected is sometimes called a forest (because it consists of trees).
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28. Language processing79
What are the main concepts of modern linguistics that fit in the planner´s language?
In linguistics theory language is described as a semantic phenomenon “situated in the mind of
the user” based on cognitive schemas (CS) (Croft & Cruse 2004) that represent mental models
of different aspects of the world. In design languages such a cognitive process could be
interpreted as the creative facet of planners. CS are difficult to encode into the formulation
model once it represents an important aspect of the planner’s role within the design process.
It is possible to establish analogies between modern linguistics theories and design languages,
which supports the idea that planners possess an analogous system of communication.
A closer look at three important concepts of modern linguistics is revealing and useful
for the remaining of our discussion:
1) Mentalism - Where language is situated in the minds of speakers. Herein language is
an idealization of the practices of a homogeneous community with a vast individual
variation and mixture - where every speaker commands a number of different records of
vocabulary and usage to be used in different contexts (Katz 1964).
2) Combinatoriality - Where language is a combinatorial system that can be used
creatively and systematically following a non conscious process. Linguistics and
psycholinguistics are concerned with discovering such a process as recent research on
psychology of vision suggests. Herein the important question concerns what aspects of
language does a speaker store in memory (including words, but also much else), and
what does a speaker construct in the course of speaking? The latter involves the use of
rules/schemas/principles that are applied creatively (Sugita & Tani 2005).
79 . Language processing refers to the way human beings process speech or writing and understand it as language. Most recent theories back the idea that this process is made completely by and inside the brain.
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3) Inner resources for language learning - Where one acquires language by learning on
the basis of experiencing practices community. Herein the important question is what
are the inner resources that one brings to such a task? Some of the resources are fairly
general (e.g. ability to interact socially, ability to imitate). But some are specific to
language, a “language instinct” - a cognitive specialization of humans (Manning &
Schütze 2002).
6.4. Planners and Language processing
Planners manage creativity by formulating associations or bridges between patterns in a
process of multiple combinations – similar to the concepts of modern linguistics described
above. Such a process is related with two different aspects of creation: systematization and
instinctiveness. Formagio (1976) citing Heidegger refers that a piece-of-art is an exercise of
design over meaning only present within a context of illumination (systematization) and
occultation (instinctiveness).
Creativity seems thus to enclose;
1) revealed information (systematized) and
2) unexpected information (created by associations and inner management).
Several studies focused on design phenomenology have targeted their case-studies at the
iterative nature of creation. The aim of such protocol80 studies is the disclosure of the action
paths that occur during a planning phase when resolution and judgment (decision making) are
focal points. One of the techniques used is centred on monitoring discussions, drawings, and
comments of design teams, capturing the flow of ideas that lead to decisions and design
outputs.
80 . In natural sciences a protocol is a predefined written procedural method in the design and implementation of experiments. Protocols are written whenever it is desirable to standardize a laboratory method to ensure successful replication of results by others in the same laboratory or by other laboratories. Detailed protocols also facilitate the assessment of results throug h peer review. Protocols are employed in a wide range of experimental fields, from social science to quantum mechanics. Written protocols are also employed in manufacturing to ensure consistent quality. Protocol is also an agreement that governs the procedures used to exchange information between cooperating entities; usually includes how much information is to be sent, how often it is sent, how to recover from transmission errors, and who is to receive the information.
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In a similar study, Lindekens (2004; 2007) describes a monitored process showing a
sample of solutions generated by a planning team. Moreover he describes how solutions are
converted into designs and how designs express personal assumptions in a cycle that flows
continuously. Such framework is useful to understand how humans behave when manipulating
concepts in order to produce results. The recognition and the description of these heuristics81
represents an opportunity for the definition of a common set of procedures with the objective
of creating design solutions in a more organized and systematic fashion.
5. Active drawing phase during the design (Lindekens 2004)
The following lines were taken from the discussion between planning team members. This
“chat” and drawing session was recorded by Lindekens (2004) as part of his research. Herein
team members express verbally their thoughts while making a set of sketches depicted in the
above figure. The session was recorded and surveyed for a time period (follows an extract of
the team’s comments).
0:43:54 - actually an important circulation … connection is still between… 0:44:03 - the elbow of the mill here 0:44:05 - because here the important steps are situated 0:44:08 - also the shortcut towards auditorium “de molen” [the mill] 0:44:12 - so this is an important circulation 0:44:17 - we the stairs over here … 0:44:20 - will be restored
81 . Heuristic is an adjective for experience-based techniques that help in problem solving, learning and discovery. A heuristic method is particularly used to rapidly come to a solution that is hoped to be close to the best possible answer, or 'optimal solution'. Heuristics are "rules of thumb", educated guesses, intuitive judgments or simply common sense. A heuristic is a general way of solving a problem. In more precise terms, heuristics stand for strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines (Dechter & Pearl 1987).
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0:44:21 - the former stairs are continued till the ground floor 0:44:25 - so that a better connection is created that … 0:44:30 - that corridor with the gothic arches … towards … the stone staircase 0:44:37 - so we will make sure that this actually is the most important 0:44:41 - the most important route 0:44:43 - maybe here somewhere...
This fragment is insufficient to evaluate the planner’s language. The mechanism of thoughts is
difficult to understand, although it often seems to follow a random order where concepts and
scales are presented without a particular logical sequence. In such mechanisms, cognitive
assumptions are usually abundant in problem solving82. In fact, one of the challenges in the
elaboration of the formulation model is to create a system of predefined rules to avoid
randomness, enabling at the same time the contribution of planner’s cognitive assumptions.
The idea is to provide a logical structure to the model, as well as flexibility and manipulability.
6.5. Lexicon
The elaboration of “speech” in a language requires the manipulation of a lexicon (or
vocabulary). The urban design language enables a specific speech that entails a particular
glossary associated with spatial features. The difficulty related with such lexicon is the
vagueness of its semantic field and the breadth of its context. This is why it is so important to
create an ontology to define a right path towards the description of the urban lexicon.
How lexicon can thus be described?
The urban lexicon consists of descriptions of single entities (vocabulary) that compose of
groups of entities (patterns) ranging from concepts, geometric representations, land
classifications, urban object’s descriptions, to physical delimitations (see Diagram 29), etc.
Lexicon is thus the descriptive basis of patterns.
The way lexicon is combined to define patterns is in the way different matters concerning
urban space converge to form concepts (for space).
Diagram 29 gives an idea about such type of convergence.
82 . Problem solving is a mental process and is part of the larger problem process that includes problem finding and problem
shaping. Considered the most complex of all intellectual functions, problem solving has been defined as higher-order cognitive
process that requires the modulation and control of more routine or fundamental skills. Problem solving occurs when an organi sm
or an artificial intelligence system needs to move from a given state to a desired goal state (Goldstein & Levin 1987).
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In the diagram, the abstract pattern entity located at its centre connects to a variety of matters
such as economy, geometry, population, boundaries, rules, etc. These matters correspond to
the vocabulary that supplies pattern’s semantics. Put simply, urban patterns are made of a
combination of entities (lexicon) and Diagram 29 depicts the basic ontological structure of
urban patterns.
29. The ontological diagram of an urban pattern (Montenegro, N.C. and Duarte, J.P., 2008)
Concluding with a simple syllogism: A given amount of entities or subject matters (a pattern’s
lexicon) congregated, create a pattern. The value and the combinations established between
these subject matters enable the creation of a set of different patterns. A consistent set of
patterns, running collectively, creates a particular language.
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6.6. Pattern Language
The creation of a formulation instrument for urban design, proposed in this research, is
inspired in the principles described in Alexander’s series of books published in the 70’s, which
has created a new theory for urban design.
“A pattern language”83 (PL) provides a method for designs based on a language of
patterns for things ranging from rooms to towns. The “Timeless Way of Building” (Alexander
1979) provides the theory and instructions for the use of the language that made it possible to
use the patterns to create a building or a town. Alexander’s premises depart from linguistics
theory, which defines language as a combinatorial and creative method of communication in
different contexts, with clear instructions, and within a defined vocabulary. The aim for this
language is to allow users to manipulate creatively its ingredients to develop an appropriate
speech that is a design adequate to a given context.
In planning, such characteristics are particularly useful for enabling a creative and
flexible process.
Pattern Language main concepts
Pattern Language is a term denoting elements of language (Alexander et al. 1977).
In the formulation model presented here, language is the metaphor for urban design
whilst urban space. Patterns or elements of language correspond then to recurrent urban
features or events where each pattern has a particular structure described by;
a) a composition with a set of minor elements related to urban space,
b) a definition of a recurrent urban problem or event, and
c) a description of a solution to solve the urban problem.
Patterns are akin to recipes in which by combining a collection of ingredients or metadata84
according to specified routines one may arrive at adequate descriptions of solutions and then
at solutions themselves through design generation.
83 . Patterns hide a lot of cultural and conceptual "baggage," providing a compressed intensity and an economy of expression in return. Patterns users who experience the power of patterns have acquired this baggage, either tacitly (through repeated use) or explicitly, by studying the literature. This is the opposite of models, for which syntax and semantics act as decoder rings for the model message. But it also explains the complementary ability of models and patterns as tools for successful and quality-focused software development (Evitts 2000). 84 . The first use of the term “Metadata” has been attributed to Jack E. Myers who subsequently trademarked the word. Since then the fields of library science, information technology and GIS have widely adopted the term. In these fields the word metadata
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The idea of recurrence85 within patterns was developed by Alexander and defines an important
logic within the language and its syntax, that is the combinatorial and recursive way patterns
can be manipulated allows one to use them indefinitely and extensively. This feature permits
one to use the language in a creative way.
Urban patterns are basically formulated to assist planners86. Thus planners are pattern
administrators possessing an intermediary level of intervention towards the development of
solutions. In the formulation model patterns should generate some kind of proficient solutions
even with a low managing intervention of planners. This means that the formulation model
comprise a mechanism for, departing from a description of a context; arrive at a description of
a solution.
Formulation patterns, which are deeply inspired in Alexander’s formalities, follow its basic
scheme, that is;
1) all patterns have the same format,
2) patterns are defined by a picture with the archetypal example of the pattern,
3) each pattern has an introductory chapter that sets its context,
4) patterns are defined by one or two sentences defining the essence of its problem,
5) the problem is described in the longest section of the structure – pattern background,
its validity, and the ranges of its manifestation,
6) the solution, the heart of the pattern, given by a set of precise instructions to
guarantee instances of patterns,
7) the description of the solution in a diagram with its main components,
is defined as “data about data”. While this is the generally accepted definition, various disciplines have adopted their own more specific explanation and uses of the term (Dudley n.d.). 85 . In mathematics, a recurrence relation is an equation that recursively defines a sequence: each term of the sequence is defined as a function of the preceding terms. 86 . • From a broad perspective, a pattern can be seen as a form for documenting best practices. In a profession that lacks centuries of experience and scientific underpinnings of engineering, architecture, or urban planning, best practices have become a touchstone for ensuring that risks are understood and that commonly accepted techniques and technologies are used. Patterns provide a standard format and repository for them—replacing what has been, until now, anecdotal reporting and documentation of the best ways to do things. • From a narrower perspective, a pattern can be seen as a rule of thumb: a heuristic—quick way of providing a starting point for solving a problem. The craft of software development has generated many rules of thumb in its brief history. Patterns can provide a home for them that is formalized without being fussy. • Finally, and even more narrowly, a pattern can be viewed and used as a template. This definition captures a critical aspect of patterns: they can be applied over and ov er again, in different situations. They are not specific solutions, but rather the basis for a solution. And, in software development, they derive from the fact that software solutions themselves tend to be repetitive. There is only a small set of solutions for any design problem in information systems, whether the problem is in software architecture or in development organization (Evitts 2000).
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8) the set of smaller patterns related with the specific pattern in order to complement or
enrich its description (similar to (Alexander’s, 1977: xi)).
The following text corresponds to a stretch from the Alexander’s Pattern Language book
(1977). Texts and figures are taken from the book to portrait the above pattern structure. The
pattern shown in following is the 26th of Alexander’s patterns, called “Life Cycle”.
”26. LIFE CYCLE
(…) real community provides, in full, for the balance of
human experience and human life - COMMUNITY OF 7000 (12).
To a lesser extent, a good neighborhood will do the same -
IDENTIFIABLE NEIGHBORHOOD (14). To fulfill this promise,
communities and neighborhoods must have the range of things
which life can need, so that a person can experience the full
breadth and depth of life in his community (…)
Therefore
Make certain that the full cycle of life is represented and balanced in each community. Set the ideal of a
balanced life cycle as a principal guide for the evolution of communities. This means: 1. That each
community include a balance of people at every stage of the life cycle, from infants to the very old; and
include the full slate of settings needed for all these stages of life; 2. That the community contain the full
slate of settings which best mark the ritual crossing of life from one stage to the next.
To live life to the fullest, in each of the seven
ages, each age must be clearly marked, by
the community, as a distinct well marked
time. And the ages will only seem clearly
marked if the ceremonies which mark the
passage from one age to the next are firmly
marked by celebrations and distinctions.
By contrast, in a flat suburban culture the seven ages are not at all clearly marked; they are not
celebrated; the passages from one age to the next have almost been forgotten. Under these conditions,
people distort themselves. They can neither fulfill themselves in any one age nor pass successfully on to
the next. Like the sixty-year-old woman wearing bright red lipstick on her wrinkles, they cling ferociously
to what they never fully had. This proposition hinges on two arguments. a) The cycle of life is a definite
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psychological reality. It consists of discrete stages, each one fraught with its own difficulties, each one
with its own special advantages. b) Growth from one stage to another is not inevitable, and, in fact, it
will not happen unless the community contains a balanced life cycle.
(…) To re-create a community of balanced life cycles requires, first of all, that the idea take its
place as a principal guide in the development of communities. Each building project, whether the
addition to a house, a new road, a clinic, can be viewed as either helping or hindering the right balance
for local communities. We suspect that the community repair maps, discussed in The Oregon
Experiment, Chapter V (Volume 3 in this series), can play an especially useful role in helping to
encourage the growth of a balanced life cycle.
But this pattern can be no more than an indication of work that needs to be done. Each
community must find ways of taking stock of its own relative "balance" in this respect, and then define a
growth process which will move it in the right direction. This is a tremendously interesting and vital
problem; it needs a great deal of development, experiment, and theory.
x STAGE IMPORTANT SETTINGS RITES OF PASSAGE
1
INFANT
trust
Home, crib, nursery, garden Birth place, setting up the home . . . . out of
the crib, making a place
2
YOUNG
CHILD
autonomy
Own place, couple's realm, children's realm,
commons, connected play
Walking, making a place, special birthday
3
CHILD
Initiative
Play space, own place, common land,
neighborhood, animals
First ventures in town . . . joining
4 YOUNGSTER
Industry
Children's home, school, own place, adventure
play, club, community
Puberty rites, private entrance paying your
way
5 YOUTH
Identity
Cottage, teenage society, hostels, apprentice,
town and region
Commencement, marriage, work, building
6 YOUNG
ADULT
Intimacy
Household, couple's realm, small work group,
the family, network of learning
Birth of a child, creating social wealth . .
building
7 ADULT
Generativity
Work community, the family, town hall, a room
of one's own
Special birthday, gathering, change in work
8 OLD
PERSON
Integrity
Settled work, cottage, the family, independent
regions
Death, funeral, grave sites
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The rites of passage are provided for, most concretely, by HOLY GROUND (66). Other specific patterns
which especially support the seven ages of man and the ceremonies of transition are HOUSEHUOLD MIX
(35), OLD PEOPLE EVERYWHERE (40), WORK COMMUNITY (41), LOCAL TOWN HALL (44), CHILDREN IN
THE CITY (57), BIRTH PLACES (65), GRAVE SITES (70), TEENAGE SOCIETY (84), CHILDREN'S HOME (86)
(…)”
This pattern is an example of the PL language scheme, which consists of links established
between the working pattern (26) with minor patterns (12), (14) of the language, as well as
with major patterns as (66), (35), (40), (41), (44), (57), (65), (70), (84), (86). Pattern (66)
denotes dominance over the others.
The following diagram shows the 26th PL ontology taxonomy.
30. An example of Pattern’s taxonomy (the created links between patterns)
Such description helps one to understand the role of each particular pattern within the
planning language.
PL fragilities
The work of Alexander stirred the field but had little practical impact. With a set of
comparative examples is possible to detect latent fragilities in the description of PL sorts. For
example, there are patterns that repeat analogous solutions (example: patterns 57 and 68)
due to the PL scale structure. There is also a lack of key patterns relevant for design such as
urban grids or network morphologies. Without them is very difficult to structure a plan. Some
other PL patterns are embedded in very particular cultural contexts which constrains the
possibility of a wider general use. Finally a large amount of PL patterns are applicable at a
larger scale (the city scale for example) than site planning scale, which is the focus of the
current.
major patterns related
working pattern
minor patterns related12
26
66 35 40 41 44 57 65 70 84 86
14
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How then to select patterns?
To define a contemporary pattern language for the site planning scale, one may exclude
Alexander’s patterns based on three criteria: similar solutions, cultural context, and scale. In
general, patterns that can be excluded on scale refer to urban facilities that are normally
considered at a city scale (cemetery, sports facilities, etc). In the elaboration of a plan at a site
scale many of such patterns may have no applicability. However, if necessary, city scale
patterns can be inherited by site scale patterns in order to match SUP/SD criteria (PDP1). Such
patterns can then be included in the program. One possible way of managing large scale
patterns is to create a module for them, in order to prevent the creation of a pattern language
with a high number of exceptional patterns. To exclude patterns based on cultural criteria is
more difficult, in a simplified model, due to the complexity and the extension that involves
such descriptions. To surpass this difficulty one proposes a formulation “module”.
The idea is simple.
The basic structure of the formulation model is built on an agreed set of structural patterns,
where modules can be added or removed to adjust the language of the program to the context
of the plan and to the users of the urban program. The modules will include, among others,
different cultural contexts and theoretical models of the city. This means that, this way, the
formulation model is built in an extensible and combinatorial way, and it will be always a work
in progress. This flexibility sets one of the key concepts of the proposed model.
The assessment of related studies in order to revise and improve PL concepts and
patterns might be necessary in the development of a contemporary pattern language. Thus a
set of new patterns has to be introduced into the language to take into account new
knowledge, models, and theories. PL patterns might also have to be improved regarding
aspects such as data attributes, indicators and cross-references.
In summary:
1. It is necessary to bring-up-to-date and redefine Alexander’s “pattern language”,
having into account:
1.1 the advances in knowledge that occurred since the initial definition of the
“pattern language,” and
1.2 the evolution of the cultural context (communities do not live today as
before).
2. This redefinition can imply:
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2.1 the elimination of patterns,
2.2 the inclusion of new patterns, and
2.3 the modification of patterns.
The entire redefinition of the pattern language, and the addition of new final patterns will be
the subject of future work, however, it is crucial to present a preliminary list of selected
patterns.
Urban patterns selected from Alexander’s PL patterns
This section is concerned with a tentative list of urban patterns that apply at the site planning
scale elaborated after Alexander’s list. In this a list, patterns that do not apply at the site
planning are out of the list or are written in red. Patterns that are usually applied at a larger
scale but occasionally also at the site planning scale are written green. Patterns that could be
applied at the site planning scale but were excluded are written in blue. The list is the
following:
TOWNS SCALE
10. MAGIC OF THE CITY
11. LOCAL TRANSPORT AREAS
12. COMMUNITY OF 7000
13. SUBCULTURE BOUNDARY
14. IDENTIFIABLE NEIGHBORHOOD
15. NEIGHBORHOOD BOUNDARY
16. WEB OF PUBLIC TRANSPORTATION
17. RING ROADS
18. NETWORK OF LEARNING
19. WEB OF SHOPPING
20. MINI-BUSES
21. FOUR-STORY LIMIT
22. NINE PER CENT PARKING
23. PARALLEL ROADS
24. SACRED SITES
25. ACCESS TO WATER
26. LIFE CYCLE
27. MEN AND WOMEN
28. ECCENTRIC NUCLEUS
29. DENSITY RINGS
30. ACTIVITY NODES
31. PROMENADE
32. SHOPPING STREET
33. NIGHT LIFE
34. INTERCHANGE
35. HOUSEHOLD MIX
36. DEGREES OF PUBLICNESS
37. HOUSE CLUSTER
38. ROW HOUSES
39. HOUSING HILL
40. OLD PEOPLE EVERYWHERE
41. WORK COMMUNITY
42. INDUSTRIAL RIBBON
43. UNIVERSITY AS A MARKETPLACE
44. LOCAL TOWN HALL
45. NECKLACE OF COMMUNITY PROJECTS
46. MARKET OF MANY SHOPS
47. HEALTH CENTER
48. HOUSING IN BETWEEN
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49. LOOPED LOCAL ROADS
50. T JUNCTIONS
51. GREEN STREETS
52. NETWORK OF PATHS AND CARS
53. MAIN GATEWAYS
54. ROAD CROSSING
55. RAISED WALK
56. BIKE PATHS AND RACKS
57. CHILDREN IN THE CITY
58. CARNIVAL
59. QUIET BACKS
60. ACCESSIBLE GREEN
61. SMALL PUBLIC SQUARES
62. HIGH PLACES
63. DANCING IN THE STREET
64. POOLS AND STREAMS
65. BIRTH PLACES
66. HOLY GROUND
67. COMMON LAND
68. CONNECTED PLAY
69. PUBLIC OUTDOOR ROOM
70. GRAVE SITES
71. STILL WATER
72. LOCAL SPORTS
73. ADVENTURE PLAYGROUND
74. ANIMALS
75. THE FAMILY
76. HOUSE FOR A SMALL FAMILY
77. HOUSE FOR A COUPLE
78. HOUSE FOR ONE PERSON
79. YOUR OWN HOME
80. SELF-GOVERNING WORKSHOPS AND
OFFICES
81. SMALL SERVICES WITHOUT RED TAPE
82. OFFICE CONNECTIONS
83. MASTER AND APPRENTICES
84. TEENAGE SOCIETY
85. SHOPFRONT SCHOOLS
86. CHILDREN'S HOME
87. INDIVIDUALLY OWNED SHOPS
88. STREET CAFE
89. CORNER GROCERY
90. BEER HALL
91. TRAVELER'S INN
92. BUS STOP
93. FOOD STANDS
94. SLEEPING IN PUBLIC
BUILDINGS SCALE
95. BUILDING COMPLEX
96. NUMBER OF STORIES
97. SHIELDED PARKING
98. CIRCULATION REALMS
99. MAIN BUILDING
100. PEDESTRIAN STREET
101. BUILDING THOROUGHFARE
102. FAMILY OF ENTRANCES
103. SMALL PARKING LOTS
104. SITE REPAIR
105. SOUTH FACING OUTDOORS
Embedded concepts of patterns
Patterns are different because its concepts and descriptions depend on the point of view of its
developers. So to surpass this univocal picture it is important to look at related studies, first to
become aware of different visions, and then to ease the selection of the formulation language
structure.
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Alexander (1977) and Pedro (2001b) are good examples of such dissimilarity. They
present two different visions regarding the development of patterns. Alexander has created a
sort of language for design - the Pattern Language book87 is ample on semantics. The work of
Pedro is largely framed by the universe of the quality standards - Pedro’s patterns deals
essentially with quality attributes.
While Alexander lacks main design actions as the creation of urban grids, focusing
extensively on political ideals, Pedro seems to lack flexibility and narrative88. Alexander
supports its vision upon a liberal philosophy. When defining patterns such as “Dancing on the
Streets” (PL 63) or “Sleeping on Public” (PL 94) it proposes ethics - often in opposition with
traditional conventions regarding the use of space. PL embraces thus a creative vision by
setting up desirable environments - however it seems too vague and too politically framed.
Pedro supports its vision on a more prescriptive philosophy focusing quality demands for a site
and a population. When defining a type of spatial quality he defines it following a constrained
path to guarantee accuracy according to predefined parameters.
A contemporary PL
In the update of the pattern language it must be taken into consideration these two different
visions concerning the formulation process. In the one hand, it is important to increase the
accuracy of the language, as Pedro did, and on the other hand, it is necessary to maintain
sufficient conceptual and visionary paths like Alexander.
A balance between such different conceptions can bring benefits to the formulation
model, because it amplifies the range of knowledge and manipulation.
87 . A Pattern Language: Towns, Buildings, Construction is a 1977 book on architecture. It was authored by Christopher Alexander , Sara Ishikawa and Murray Silverstein of the Center for Environmental Structure of the University of California at Berkeley, , with writing credits also to Max Jacobson, Ingrid Fiksdahl-King and Shlomo Angel. Twenty five years after its publication, it is still one of the best-selling books on architecture. The book is a substantive, illustrated discussion of a pattern language derived from traditional architecture, with 253 unitary patterns such as Main Gateways given a treatment over several pages. It is written as a set of rules that are invoked by circumstances. This is a form that a theoretical mathematician or computer scientist might call a generative grammar. The work originated from an observation that many medieval cities are attractive and harmonious. The authors said that this occurs because they were built to conform with local regulations that required specific features, but freed the architect to adapt them to particular situations. The book provides rules and pictures, and leaves decisions to be taken from the precise environment of the project. It describes exact methods for constructing practical, safe, and attractive designs at every scale, from entire regions, through cities, neighborhoods, gardens, buildings, rooms, built-in furniture, and fixtures down to the level of doorknobs. 88 . A narrative is a story that is created in a constructive format (as a work of writing, speech, poetry, prose, pictures, song, motion pictures, video games, theatre or dance) that describes a sequence of fictional or non-fictional events. It derives from the Latin verb narrare, which means "to recount" and is related to the adjective gnarus, meaning "knowing" or "skilled". (Ultimately derived from the Proto-Indo-European root gnō-, "to know"). The word "story" may be used as a synonym of "narrative", but can also be used to refer to the sequence of events described in a narrative. A narrative can also be told by a character within a larger narrative. An important part of narration is the narrative mode, the set of methods used to communicate the narrative through a process called narration.
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6.7. Urban Pattern Language Sketch (UPL)
Until now, the research was essentially focused on a variety of topics related with language
processing and planning methods. Now, it is time to build up the base (or the structure) of the
planner´s language. Facing the considerable variety of matters involving the description of
such a structure a question arises: Where to start?
First of all, it is important to mention that pre-design ontology (the core process of this
research) requires the sketch of an urban pattern language (UPL) to be used as a
contemporary flexible tool by planners. The axiom UPL is not an obsessive premise. It basically
drafts the name to distinguish it from other studies. So, herein, urban pattern language will be
written UPL in order to differentiate from Alexander’s PL (pattern language). Some overlapping
with PL is expected, though the word urban was chosen due to the exclusive field of
application, the word pattern because it concerns type and value within the urban
formulation, language due to the similarity with natural language’s structure.
How does UPL work in the proposed model?
The flow of information of UPL patterns acts at two different levels: one within the formulation
model and the other in association with the generation (design) and evaluation models. The
first level is simple to describe. Acquired data (PD1) acts as an input of the formulation model.
Such data is interpreted in order to be embedded into patterns to support and guide design
decisions. The second level consists of a data recursion process where data is in updating flow
(between formulation, generation and evaluation models) to compose more integrated
results. Evaluation is particularly important in such a process because it can act between
patterns and design correcting and updating the entire flow.
6.8. The UPL Ontology
The creation of a language’s ontology faces a set of difficulties. When one starts to handwrite a
diagram following the principles of “classic” ontology-building is faced with a set of
temptations (Gruber & others 1995). These concern mainly ambiguities prompted by the
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manual manipulation of elements, groups, classes, and types, within its taxonomic description.
Such ambiguities drift from personal assumptions promoting a sense of vagueness in the
partitions of the model.
There is a critical problem between hand sketching and computational edition of
ontologies. The computational edition of ontologies allows the emergence of relational
structures, many of them without even having been previously imagined (Noy et al. 2000).
Basically, the software asks a set of questions to the agent (heuristically) asking for new
descriptions (domain, classes, and semantic attributes) (Sachs et al. 2006). Then the ontology-
building is led by a sequence of emerging semantic relations, fill-in the empty spaces of the
model.
The mission of congregating all semantic relational data into the ontology is massive.
One can initiate the process of organizing ingredients by a) describing a hierarchic tree of
elements that compose of urban space (a taxonomy), then by b) describing a list of semantics
that qualifies the urban elements (such as social, economic, and environmental features
among others), and finally c) describing a list of attributes for the specified elements.
6.9. The UPL Syntax and Core Components
Developing an ontology is usually an iterative process. As aforementioned, one can start with a
rough take at the ontology, and then revise and refine the evolving ontology by filling in the
details. As mentioned in the methodology chapter, developing an ontology includes the
following tasks:
1) definition of classes,
2) organization of the classes in a subclass-superclass hierarchy,
3) definition of slots by describing allowed values for such slots, and
4) the fill in the values for instances slots.
Furthermore an ontology allows one to act on two complementary levels of description: a top
level ontology on which are located the concepts and the relations of the model at a macro
scale; and an application ontology which specifies and details the concepts, thereby describing
the nature of its particular interactions.
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The initial task concerns the description of the core features of the UPL top level
ontology. Such a selection requires a discovery of the crucial components of the urban
planning process, that is:
1) The nature of urban space (the field of its application),
2) The nature of design actions (the field of its proposals), and the interoperability of
these within,
3) A supporting computational system (the field of its administration).
These components are detailed as follows:
1) The nature of the urban space
Kevin Lynch (1960) wrote that users understood their surroundings in consistent and
predictable ways, by forming mental maps with defined elements: paths, streets, sidewalks,
trails, and other channels in which people travel (Networks); edges, perceived boundaries such
as walls, buildings (Blocks), and shorelines; districts, relatively large sections of the city
distinguished by some identity or character (Zones); nodes, focal points, intersections or loci;
and landmarks, readily identifiable objects which serve as reference points (Landmarks). Such
classes are hence defined by a) Networks, b) Zones, c) Blocks, and d) Landmarks.
2) The nature of the design actions
The urban design guidelines books surveyed for the current study recurrently presented similar
descriptions (as in the ByDesign CABE, the Urban Design Compendium, or in the Green
Dimensions books) (Gann et al. 2003)(Evans et al. 2007) (C. Moughtin & Shirley 2005). The core
element that occasionally appears separated from the Lynchian outline is the Landscape
element, somewhat denoting a tendency of planners to lead their actions based on this
additional feature. The elements can be thus described as a) Networks, b) Zones, c) Blocks, d)
Landmarks, and e) Landscape.
3) The supporting computational system
A GIS (Geographic Information Systems) software platform will support the operability of the
full model due to its resourceful spatial descriptors. Its representation standards encompass a)
Points, b) Lines, and c) Polygons.
The correlations seems to be clear: Landmarks can be represented by Points, Networks
by Lines, and Blocks and Zones by Polygons. In summary, Lynch’s appraisal matches GIS core
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description while the element Landscape (a design action component) seems to promote
fuzziness with the element Zones.
Therefore the Top Classes will be herein defined as:
a) Networks (Lines),
b) Zones (Polygons I),
c) Blocks (Polygons II), and
d) Focal points or Landmarks (Points).
However such a fuzziness limits the process understanding. To produce the ontology is thus
necessary to congregate three concepts:
1) the nature of urban space,
2) the nature of design actions, and
3) the interoperability of these with a supporting computational system.
The descriptions of patterns that will inform designs will follow the scheme: a) Networks
(Lines), b) Zones (Polygons I), c) Blocks (Polygons II), and d) Focal points (Points).
Now, describing the top ontological classes:
Networks
Networks appear here without having a hierarchical dominion over the other three core
components of the program (blocks, zones, and focal points or landmarks). It just sets one of
the possible four actions that planners can input into designs in a crucial phase of their work.
The Network component can be described by a framework of routes and spaces that connect
locally and more widely, and open spaces that are sequentially related to one another (Gann et
al. 2003). This component upholds a strong social impact once streets make a large part of
people’s experience of place. They are the main spaces where people interact, and they
combine their function as a place with a role as part of a movement network for vehicles and
pedestrians (Evans et al. 2007). There are various classes of Networks depending on form and
function. Networks involve mainly movement paths and infrastructure paths (Gann et al. 2003).
Other type of more abstract networks can be related with landscape networks or building
masses networks. Networks are divided into different class groups across different
taxonomies. According to Lynch (1960) there are three main metaphors which attempt to
explain city form through networks: the magical metaphor for the earliest ceremonial centres
of religious ritual to link the city to the cosmos and to the environment; the metaphor that
makes an analogy with a machine; and the metaphor that compares city form to an organism.
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According to Moughtin and Shirley (2005) these three metaphors are related to five main
forms of urban grids: 1) hierarchy of boxes, each nesting another, 2) orthogonal geometrical
figure / grid-iron plan, 3) directional grid, 4) triangular grid, and 5) informal lacework of
paths. Marshall (2005) further describes the network system and details network movement
patterns by describing performance correlation between different morphologies.
Blocks
Blocks represent compositions of buildings or groups of buildings within an urban site. The
space in between the volumes of blocks generally implies movement grids. The mixture
between blocks and grids defines the main structure of urban settlements. This component of
the urban program involves street blocks arrangements with its plots and buildings in
settlements (buildings < plots < blocks) (Gann et al. 2003). Buildings can range from housing,
office areas, recreation, leisure, and sports to crèches, education, health, and training to
community workspaces. Buildings within blocks also provide a secure base for community
organisations to establish a presence by developing partnerships between locals and other
stakeholders. Blocks also configure the best local resources to generate income (Evans et al.
2007). There are few studies committed to the definition of block morphologies and its classes
within city descriptors. The existing ones seem to be vague or too classic. Once again,
Alexander’s “pattern language” (1977) lacks this core category of “city objects”. When
Alexander refers to blocks he avoids a physical or geometric recognition or description of it,
setting a group of social semantics upon a vague notion of neighbourhood. Post-modern
research (Krier & Porphyrios 1984) correlates blocks with types of classic archetypal
morphologies while building masses tend today to be more abstract or topologic, sometimes
inspired in natural forms, or even developed under conceptual art or technology. The range of
block designs is today quite wide and open. Mitchell (1993) talks about an absence of a
theoretical critic able to explain the origin of shapes. However the starting point to define
block in a somewhat formalized way can be found in Pedro (2001b), where blocks descriptions
comprise a set of flexible archetypal forms that can be parameterized.
Zones
The component Zones comprise areas within perimeters defining types of environments within
sites. Zones are here defined within boundaries containing groups of meanings involving
matters such as the range of services and facilities, including commercial, educational, health,
spiritual and civic services (Evans et al. 2007). Design under this component is similar to
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“planning through portraits” (Lynch 1960) where concepts as neighbourhood and mixture
represent a design core. Zones also require caution in the design process to avoid any form of
segregation. It is therefore essential to promote diversity in terms of: a) development forms; b)
land use; c) density; d) tenure; and e) market segments. Zones are usually carved into
development parcels around a road system with a clear urban design structure in place (DETR
2000). This approach frequently involves routing the main road around the site rather than
across it and locating the traffic generating uses such as retail and employment areas close to
entrance junctions and along the main road. “The road is used as a boundary to segregate
uses. Such attempts to create a sense of place around a focal point often fail because the very
uses that generate activity are on the edge of the site or beyond, in a nearby business park or
out-of-town centre, and tend to be internalised in “big boxes”(Evans et al. 2007).
Focal Points or Landmarks
The development of a plan can start with the identification or definition of focal points and/or
landmarks in space (pre-existing or new). These marks act as structural nodes from which
planners can define networks and masses of the plan. The relevance of landmarks and focal
points is simple to portray (Gann et al. 2003); “People find it easier to orient themselves and
recognise where they are when new development safeguards important views between places
or creates new ones, whilst respecting or adding new local landmarks. To ensure that a
particular place is legible, assess the relationship between existing elements and, in consulting
local people, determine how proposals contribute to a linked series of spaces and markers that
make it easy to get from A to B and to C” (Evans et al. 2007).
The following diagram (31) shows the main classes of the pre-design phase. The core
ontology (Blocks, Focal Points, Networks, and Zones) is located in the purple boxes of the
diagram entities. Its shared super-class is Design Core (light purple and dark green boxes).
Diagram 31 is also presented in Annex 5 at a different scale.
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31. Syntax class hierarchical tree (above left), exported piece of XML Schema (above centre), CPL diagram
classes, subclass-superclass hierarchy, and slots (middle right), CPL diagram zoom - the design core -
Networks, Zones, Blocks, and Landmarks (at the bottom).
note: the CPL was built in the Protégé-Frames editor, in accordance with the Open Knowledge Base
Connectivity protocol (OKBC).
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6.10. The UPL lexicon
A considerable part of the information related with urban space comprises geographic data,
that is, information that describes territorial features. Such information type is currently
shared by some communities and managed by central governments or controlled by other
administrative organizations. These specific databases are internationally known as geographic
information systems (GIS). The main purpose of such systems is the assemblage of relevant
geographic data to produce comprehensive descriptions of spatial configurations. One of the
advantages of GIS is related with its system of coordinates known as geo-reference, which
means that geographic information is related to a precise location on the planet, within a
continent, a region, or a site, and can be correlated with other geo-referenced information.
Due to strong investments by state and private corporations with interests on property and
territorial management, GIS software constitutes a well developed platform today. GIS thus
represents an important resource to be used in the formulation model to quickly retrieve and
store geographic data in the process of developing urban proposals. A GIS database can be
used to feed the formulation model with data about the context. It also can be used to store
data about designs produced by the generation module. Compatibility amongst both
contextual and design data requires the definition of a common ontology. Such ontology will
allow an easy flow of information within the formulation model and between this and the
other two models of the planning process - the generation model and the evaluation model. At
present there is an absence of an urban planning ontology covering the core matters of the
urban planning process. One way of surpassing the difficulty of defining a totally new ontology
is to use partial existing ones adapted to the needs of the formulation model. This creates the
possibility of using ontological descriptions within existing GIS databases as the Spatial Data
Transfer Standard (SDTS)89 approved by the US Federal Information Processing Standard (FIPS)
89 . Purpose of SDTS -- The purpose of the SDTS is to promote and facilitate the transfer of digital spatial data between dissimilar computer systems, while preserving information meaning and minimizing the need for information external to the transfer. Implementation of SDTS is of significant interest to users and producers of digital spatial data because of the potential for increased access to and sharing of spatial data, the reduction of information loss in data exchange, the elimination of the duplication of data acquisition, and the increase in the quality and integrity of spatial data. SDTS is neutral, modular, growth-oriented, extensible, and flexible--all characteristics of an "open systems" standard. (http://data.geocomm.com/sdts/) accessed January 2009.
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(Rugg 1995), or the OpenGIS City Geography Markup Language90 (Kolbe, Gröger et al. 2005).
Those GIS “standards” were built to support operations between different computational
systems within a data transfer philosophy based on geographic and cartographic information
as well as other relevant metadata. This relevance demands a closer look at both systems:
The SDTS – GIS
The SDTS has a concept model consisting of detailed specifications such as content, structure,
and format. The spatial data model structure is based on three types of object description: a)
The “Spatial entities model”, which describes real spatial entities such as buildings, roads,
rivers, and so on, through rate attributes, b) the “Spatial objects model”, which describes
spatial objects such as lines, polygons and dots, used to represent real entities in digital
systems and, c) the “Spatial descriptions model”, which describes entities related to the real
world, objects related to the digital world, as well as spatial descriptions and connections that
exist between them. To guarantee data homogeneity and compatibility between data transfer,
SDTS describes a formal list of entities. The actual list includes more than 200 entity types, 244
attributes and more than 1200 alternative terms. The standard definition of entities includes
the following data structure: a) “Entity type”, a definition of a set of similar entities, b) “Entity
instance”, an example of a specific formalization within a type; “Attribute Entity”, a feature
that describes a type, c) “Attribute value”, a specific quality of an attribute, d) “Standard
expression”, a stereotyped name for an entity or an attribute, and e) “Integrated expression”,
a synonym used to refer to an entity or an attribute, defined by SDTS rules (Rugg 1995).
The OpenGIS – CityGML
The OpenGIS City Geography Markup Language (Kolbe, Gröger et al. 2005) has a similar
functional structure, with entities and classes definition that can be applied to the current
study model. One of the relevant aspects of GIS within geographic data gathering is the focus
on the creation of spatial ontologies (GIS-O). GIS spatial ontologies comprise today one of the
most advanced fields of ontology research and implementation. GIS software applications are
90 . . OpenGIS® Encoding Standard is for representation, storage, and exchange of virtual 3D city and landscape models. CityGML is implemented as an application schema of the Geography Markup Language version 3.1.1 (GML3). CityGML models both complex and georeferenced 3D vector data along with the semantics associated with the data. In contrast to other 3D vector formats, CityGML is based on a rich, general purpose information model in addition to geometry and appearance information. For specific domain areas, CityGML also provides an extension mechanism to enrich the data with identifiable features under preservation of semantic interoperability.
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also widely implemented facilitating the access to classified data managed by institutions
ranging from governmental institutes to private corporations as mentioned above. However,
one of the recurrent problems involving GIS databases is the data sharing knowledge. This
difficulty occurs particularly in Europe where GIS is largely administrated according to an
individual management philosophy. In the U.S., GIS databases have a large public shared
character although this seems to lead to lower quality. In this region GIS databases are
financed and promoted by governments.
The UPL lexicon could correspond to ontological sub-classes mainly taken from the
CityGML GIS standards, which consists in vast class definitions for the most important types of
objects within 3D city models. Its basic definitions representing the spatial objects and their
aggregations are defined by ISO 19109 and GML3 standards, and it comprises different types
of interrelationships between Feature Classes like aggregations, generalizations and
associations. An important outcome of such descriptions is a high degree of semantic
interoperability between different applications along their UML mapping, defining feature
types, attributes, and data types with a standardised meaning or interpretation. Towards an
ontological integration of descriptions the data is encoded by UML - Unified Modeling
Language within its static structure diagram. The structure is simple. The base class of all
thematic classes is CityObject. “CityObject is a subclass of the GML class Feature, thus it
inherits its metadata (e.g. information about the lineage, quality aspects, and accuracy). The
subclasses of CityObject comprise the different thematic fields of a city model: the terrain, the
coverage by land use objects, transportation, vegetation, water bodies and sites, in particular
buildings” (Kolbe, Gröger et al. 2005). CityFurniture is another GML class, and is used to
represent traffic lights, traffic signs, flower buckets, or similar objects. The features that are
not covered explicitly by them are modelled by the class GenericCityObject. However CityGML
schema still lacks some descriptions of subclasses like tunnel, bridge, excavation, wall or
embankment. At present, these objects have to be represented by GenericObjects, or will be
defined herein by new classes.
There is a normative to apply to Feature attributes: unless it is stated otherwise each
feature has attributes classes, function, and usage. The class attribute can occur only once,
while the attributes usage and function can be repeated within the ontology. The class
attribute describes the classification of objects, e.g. road, track, railway, or square. For the
purpose of an object, like national highway or county road, it is used the attribute function,
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while the attribute usage may define if an object is e.g. navigable or usable for pedestrians.
The most relevant Top level classes are: Land Use, Building Model, City Furniture,
Transportation Object, Vegetation Object, and Water Bodies (Kolbe, Gröger et al. 2005).
The following diagram presents the top level class hierarchy of the lexicon.
32. UML diagram of the top level class hierarchy (CityGML)
The figure below shows some of the CityGML object listed codes, that will be used in the
edition of the language ontology, and which composes part of the vocabulary used in the
above UML diagrams.
6. An example of a CityGML code list for city objects
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6.11. The UPL Semantics
UPL semantics are key attributes of the formulation model enclosing performance91. These
attributes bring up recursive data to fill in slots such as meaning and substance within the
ontology. Such data is therefore crucial to compose the ontology of an urban program. The
field of its application is mainly focused on:
a) Events upholding the human quotidian life (social/safety patterns),
b) Features as energy and environment control (bioclimatic patterns), and
c) Features with a value sight (technology and economy patterns).
Where is located this semantic field in the ontology?
The Alexander’s patterns are part of this semantic field and represent the core instrument of the
ontology-building. In fact, the patterns that are here portrayed represent an addition to the Alexander
patterns. These are the patterns that will be conjugated at the final pattern language redesign. The final
organization of all these components of the planning language will be concluded in future research.
Now, a closer look at the item a) events upholding the human quotidian life (social/safety
patterns).
a) Social core. CPL semantics are guided by the social nature of a site as described by the
following:
1. Character – which is a place with its own identity. The idea is to “promote character
in townscape and landscape by responding to and reinforcing locally distinctive
patterns of development, landscape and culture”,
91 . . A performance indicator or key performance indicator (KPI) is a measure of performance. Such measures are commonly used to help an organization define and evaluate how successful it is, typically in terms of making progress towards its long-term organizational goals. KPIs can be specified by answering the question, "What is really important to different stakeholders?". KPIs may be monitored using Business Intelligence techniques to assess the present state of the business and to assist in prescrib ing a course of action. The act of monitoring KPIs in real-time is known as business activity monitoring (BAM). KPIs are frequently used to "value" difficult to measure activities such as the benefits of leadership development, engagement, service, and satisfact ion. KPIs are typically tied to an organization's strategy using concepts or techniques such as the Balanced Scorecard. The KPIs differ depending on the nature of the organization and the organization's strategy. They help to evaluate the progress of an organization towards its vision and long-term goals, especially toward difficult to quantify knowledge-based goals. A KPI is a key part of a measurable objective, which is made up of a direction, KPI, benchmark, target, and time frame.
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2. Continuity and enclosure – which is a place where private and public spaces are
distinguished. Here the concept is to promote the continuity of street frontages and
the enclosure of space by development which defines private and public areas,
3. Quality of the public realm – which is a place with attractive and successful outdoor
areas. The idea is to promote public spaces and routes that are attractive, that are
safe, and work efficiently for all in society, including disabled and elderly people,
4. Ease of movement – which is a place that is easy to get to and move through. The
idea is to promote accessibility by making places that are easy to move through and
connect with each other, putting people before traffic and incorporating land uses
and transport,
5. Legibility – which is a place that is easy to understand. The concept is to promote
legibility through development that provides recognisable routes, intersections and
landmarks to help people find their way around,
6. Adaptability – which is a place that can change easily. The idea is to promote
adaptability through development that can respond to changing social,
technological and economic conditions, and g) diversity – which is a place with
variety and choice” (Gann et al. 2003).
The social quality needs to be evaluated through requirements such as security, spatial and
functional potential, personalization and economy; which are applicable within the space
relations of a particular site (Pereira 1996). Those are held to reinforce links between
populations within their surrounding environment. Moreover further studies deepen the
notion of social space comprising new urban research outcomes. This seems to be the case of
the “The City Joust” of Guterres (2004) that consists of an innovative social study regarding
urban planning. In “The City Joust”, social metrics are enclosed in the “experience of the city”,
in a phenomenon that gauges the universe of the urban space relations, its intrinsic empathies
and the social behaviours. The study presents an extensive study on social space measuring
consequences implicit on public and private areas (as well as hybrid). It describes the impacts
on the quality of a population’s everyday life. The concepts are supported by different theories
and indicators, namely from Maslow (1954), Jacobs (1961), Hall (1973), Newman (1972), Hillier
& Hanson (1984), and Coleman (1990).
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Those social patterns were encoded into new patterns, and transform into indicators as
shown in the table 7.
Some of the created patterns are described as follows:
1. Empathy Distance (ea),
2. Public Green (pg),
3. Total Area With Sense of Sociability (tass),
4. Private Areas With or Without Social Interaction (pawwsi),
5. Public Area With Everyday Existence (pgee),
6. Sidewalks With Social Interaction (ssi),
7. Private Areas, or with Diaphragms, with Social Monitoring (padm),
8. Pedestrian Areas (pa) and,
9. Private Areas without Social Interaction (pawsi).
codes calculations site values indicators
ea p1 (%) 12,0% 0 > desirable
ea (m2/hab) 79,56 0 > desirable
pgee p3 (%) 0,0% > 3,5%
pgee (m2/hab) 0,00
tass p4 (%) 18,0% > 25%
tass (m2/hab)
119,62
ssi p7 (%) 13,0% > 20%
ssi (m2/hab)
86,03 > 10
pg p8 (%) 1,1% 10%
pg (m2/hab) 7,11 5
pawsi p10 (%) 0,0% < 6%
pawsi (m2/hab)
0,00 < 3
7. The above table presents some indicators of Guterres social patterns (2004).
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The provisory codes and names for this sample are described by:
GP ea1
GP pg2,
GP tass3,
GP pawwsi4,
GP pgee5,
GP ssi6,
GP padm7,
GP pa8,
GP pawsi9.
b) Sustainability core (environmental domain). UPL is also informed by sustainability factors.
The definition of patterns encompassing such factors follows a basic set of concepts. In
summary they require urban space to be:
a) active, inclusive, and safe – which means that urban settlements needs to be fair,
tolerant and cohesive with a strong local culture and other shared community activities;
b) well run – this is related with an effective and inclusive participation, representation,
and also leadership;
c) environmentally sensitive – because is important to provide places for people to live
that are considerate of the environment;
d) well designed and built – which concerns the quality of the built and the natural
environment;
e) well connected – with good transport services and communication linking people to
jobs, schools, health and other services;
f) thriving – with a flourishing and diverse local economy;
g) well served – with public, private, community and voluntary services that are
appropriate to people’s needs and accessible to all; and
h) fair for everyone – because is crucial to include minorities in communities, now and in
the future (Evans et al. 2007).
Further research will give depth to concepts and indicators defining the corpus of sustainability
patterns. Despite such a framework some examples of sustainable patterns are presented as
follows.
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b1) Bioclimatic. These patterns consist of a group of instruments inspired in the “Bioclimatic
Urbanism” domain (Higueras 1997). These studies are mainly focus on climatic features and
urban environmental conditions. The main outcome is a set of design guidelines for green and
open areas, buildings, volume orientations, etc., supported on energy and environmental
sustainability criteria.
Olgyay (1963)charts both architecture and climate attributing different urban forms for
buildings in the four main world regions, establishing for each region design strategies that
serve as guidelines to architects as much as to city planners. In this context building forms are
shaped by temperature, sun exposure and humidity.
8. Form and proportions of buildings in different regions (Olgyay 1963)
The formal descriptions of the climatic patterns (Higueras, 1997) traduce a set of standards
towards the definition of form, setting itself as an essential support to develop climate-based
formal features. The following example of a cold region reveals the relevance of climate for the
definition of design solutions. In fact, each description of a climatic recommendation seems to
enclose a relevant pattern for design. As an example I describe below patterns for the Cold
Region (Higueras, 1997).
General considerations
1. Selection of a location. For sun exposure, slopes S and SE are most favourable. Locations on a
mid slope are beneficial to prevent excessive effect of winds and avoid cold air. 2. Urban
structure. Planning management has to provide protection against winds. Sets of constructions
of a larger scale can be grouped, although maintaining free space between them to take
advantage of the solar effect. Houses tend to be united to decrease the exposed surface as much
as possible and avoid heat loss. 3. Public Spaces. These should be protected from the wind,
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open, and have with periodic shaded areas. 4. Landscape. Topography, generally rough,
influences the definition of the forms of streets and the use of the space, granting it an irregular
character. 5. Vegetation. The most favourable vegetal protecting barriers are those constituted
by perennial vegetation, oriented according to the NE direction, and located within a distance of
twenty times the height of its hoist. Near the houses should stand deciduous trees. Is should be
avoided to locate vegetation near houses because it can produce humidity.
The design of the house
1. House Type. In residential arrangements, houses of one or two levels must favour
compactness. Terraced houses offer the advantage of loosing less heat. In larger apartment
buildings the compact volume is the better choice. 2. General distribution. Heating saving is
three times more important than the provision of comfort in summer. Extreme conditions in
summer and in winter suggest the creation of two separated zones that play the double roles in
building. The location of steps in the outside and the presence of ramps for cars must be avoided.
3. Distribution Plan. Design will be governed by the predominant conditions in cold months. The
period of “stay inside the house” represents 70% of annual hours. Although the plan will have to
satisfy both conditions through compactness, it is essential to include additional zones of activity
or use in deeper spaces for summer comfort. 4. Form and volume. The constructions must be
compact and display a minimum exposed outer surface. A proportion of 1:1,1 or 1:1,3, along the
East-West axis will give the finest results. 5. Orientation. The most favourable solar orientation is
located to 12° SE. The predominant wind pattern NW-SE can influence the location of isolated
buildings. 6. Colour. Surfaces exposed to the sun must have average tonalities. Surfaces can be
made of absorbent dark colours, assuring that they will always be in the shade during the
summer.”
These guidelines will be patterns or design rules only if they will be applied to generate
patterns, that is, recurrent solutions for designs. The deference for these guidelines will
generate descriptive patterns of properties of urban objects.
In summary, the set of cold region patterns can be used to reinforce UPL semantics by
complementing Alexander’s patterns. The provisory codes and names for these patterns are:
HP cr1. Selection of the location,
HP cr2. Urban structure,
HP cr3. Public Spaces,
HP cr4. Landscape,
HP cr5. Vegetation,
HP cr10. House Type,
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HP cr20. General distribution,
HP cr30. Distribution Plan,
HP cr40. Form and volume,
HP cr50. Orientation, and
HP cr60. Colour.
All these patterns will be tentatively added to the previously selected Alexander’s patterns,
following the mentioned criteria. The list of Alexander’s patterns complemented with the
added patterns is, therefore, organized as follows;
AP lta11. LOCAL TRANSPORT AREAS
AP cm12. COMMUNITY OF 7000
AP in14. IDENTIFIABLE NEIGHBORHOOD
AP nb15. NEIGHBORHOOD BOUNDARY
AP wpt16. WEB OF PUBLIC
TRANSPORTATION
AP rr17. RING ROADS
AP fls21. FOUR-STORY LIMIT
AP pr23. PARALLEL ROADS
AP ss24. SACRED SITES
AP aw25. ACCESS TO WATER
AP lc26. LIFE CYCLE
AP en28. ECCENTRIC NUCLEUS
AP dr29. DENSITY RINGS
AP an30. ACTIVITY NODES
AP p31. PROMENADE
AP ss32. SHOPPING STREET
AP nl33. NIGHT LIFE
APhm35. HOUSEHOLD MIX
AP dp36. DEGREES OF PUBLICNESS
AP hc37. HOUSE CLUSTER
AP rh38. ROW HOUSES
AP ope40. OLD PEOPLE EVERYWHERE
AP wc41. WORK COMMUNITY
AP nc45. NECKLACE OF COMMUNITY
PROJECTS
AP mms46. MARKET OF MANY SHOPS
AP hb48. HOUSING IN BETWEEN
AP llr49. LOOPED LOCAL ROADS
AP tj50. T JUNCTIONS
AP gs51. GREEN STREETS
AP npc52. NETWORK OF PATHS AND
CARS
AP mg53. MAIN GATEWAYS
AP rc54. ROAD CROSSING
AP bpr56. BIKE PATHS AND RACKS
AP cc57. CHILDREN IN THE CITY
AP qb59. QUIET BACKS
AP ag60. ACCESSIBLE GREEN
AP sps61. SMALL PUBLIC SQUARES
AP ps64. POOLS AND STREAMS
AP hg66. HOLY GROUND
AP por69. PUBLIC OUTDOOR ROOM
AP sw71. STILL WATER
AP ls72. LOCAL SPORTS
AP ap73. ADVENTURE PLAYGROUND
AP sgwo80. SELF-GOVERNING WORKSHOPS AND
OFFICES
AP sswrt81. SMALL SERVICES WITHOUT RED
TAPE
AP oc82. OFFICE CONNECTIONS
AP ts84. TEENAGE SOCIETY
AP ch86. CHILDREN'S HOME
AP iws87. INDIVIDUALLY OWNED SHOPS
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AP sc88. STREET CAFE
AP bh90. BEER HALL
AP ti91. TRAVELER'S INN
AP bs92. BUS STOP
AP fs93. FOOD STANDS
AP bc95. BUILDING COMPLEX
AP ns96. NUMBER OF STORIES
AP cr98. CIRCULATION REALMS
AP mb99. MAIN BUILDING
AP ps100. PEDESTRIAN STREET
AP bs101. BUILDING THOROUGHFARE
AP fe102. FAMILY OF ENTRANCES
AP spl103. SMALL PARKING LOTS
AP sr104. SITE REPAIR
AP sfo105. SOUTH FACING OUTDOORS
And more occasionally by:
AP i34. INTERCHANGE
AP lth44. LOCAL TOWN HALL
AP hc47. HEALTH CENTER
AP bp65. BIRTH PLACES
AP gs70. GRAVE SITES
All patterns are described by its codes as shown in the following list. The code is defined by:
two capital letters, the first identifying the pattern’s author and the second confirming it as
pattern (P) (example: AP – Alexander pattern), then, two or three small letters representing
the particular axiom of the pattern (example: Birth Places – bp), finally, the relative number of
each pattern. The following list congregates all provisional patterns discussed in this
document.
AP lta11
AP cm12
AP in14
AP nb15
AP wpt16
AP rr17
AP fls21
AP pr23
AP ss24
AP aw25
AP lc26
AP en28
AP dr29
AP an30
AP p31
AP ss32
AP nl33
APhm35
AP dp36
AP hc37
AP rh38
AP ope40
AP wc41
AP nc45
AP mms46
AP hb48
AP llr49
AP tj50
AP gs51
AP npc52
AP mg53
AP rc54
AP bpr56
AP cc57
AP qb59
AP ag60
AP sps61
AP ps64
AP hg66
AP por69
AP sw71
AP ls72
AP ap73
AP sgwo80
AP sswrt81
AP oc82
AP ts84
AP ch86
AP iws87
AP sc88
AP bh90
AP ti91
AP bs92
AP fs93
AP bc95
AP ns96
AP cr98
AP mb99
AP ps100
AP bs101
AP fe102
AP spl103
AP sr104
AP sfo105
AP i34
AP lth44
AP hc47
AP bp65
AP gs70
HP cr1
HP cr2
HP cr3
HP cr4
HP cr5
HP cr10
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HP cr20
HP cr30
HP cr40
HP cr50
HP cr60
GP ea1
GP pg2
GP tass3
GP pawwsi4
GP pgee5
GP ssi6
GP padm7
GP pa8
GP pawsi9
6.12. Conclusion
Following Christopher Alexander’s conceptual pathway it is straightforward to elaborate a
relatively balanced and functional selection of patterns in order to provide for an efficient and
effective urban pattern language. However, problems emerge after such selection, more
precisely, when the task is to relate the selected patterns with each other (from so different
domains)92 to build-up the syntax of the language.
Up to this point, the focus was on organizing patterns according to scale. Alexander
classified defined patterns based on scale because in a way it corresponds to a model of
rational planning. As a model it seems as clear as it can be. However, city planners might select
thematic fields of interest when planning and designing urban space. In this context, organizing
patterns by scale seems to restrict some of the ideological facets of traditional planning
activity.
One of the future missions of our research is, therefore, to find an alternative taxonomy that
can first be based on thematic urban problems, and only then controlled by scale
considerations.
92 . Economic, climatic, social, regulatory, cultural, etc.
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PD2 data translation
pattern language
'specifications for design'
(IV)
This chapter explores the most important category of the formulation model: the systemic language that is used by planners to formulate urban solutions, in short, the planner’s language.
In Diagram 33 is depicted the design core of the language.
33. The diagram shows the core structure of the CPL, first described in a hierarchical tree (above left), then
in an exported piece of XML Schema (above centre), and finally in a diagram (ontology core - Networks,
Zones, Blocks, and Landmarks (at the bottom)). See annex 5.
05
• planners have their own language to plan - one will call it urban pattern language (UPL)
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Chapter 7
7. Conclusion
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7.1. The Context
This thesis is part of a larger research which is concerned with the development and
implementation of a computer model for urban design. The ultimate goal of this model is the
development of a computer tool to assist in the conception and implementation of urban
design plans at the site planning scale. This larger model includes three partial models and
tools for formulating, generating, and evaluating such plans.
This thesis is concerned with the formulation model, which aims at creating the
programs of urban interventions from contextual data, including, regulations, site, and
population data. It represents one step towards the development of this model and the
corresponding tool. The thesis sketches an ontology and a pattern language for describing
urban space and composing urban programs. The tool will consist of an interactive computer
system that codifies a pattern language that can be used for describing urban solutions for
predefined contexts, according to the ontology. The computer implementation of the ontology
is the immediate following step in the research. Other future steps will be the inference of the
rules that link particular contextual features to specific patterns and the computer
implementation of the urban pattern language (UPL) defined in this way.
7.2. The Problem
One of the main concerns related with the development of the formulation model and tool is
the selection and definition of its core components and the efficiency of the embodied
methodology.
This first problem was solved to a certain extent in this thesis.
A knowledge model in any domain requires an initial listing of the base concepts of that
domain. The proposed ontology allowed one to indentify the main classes of such concepts, in
order to structure the taxonomy of urban space that is manipulated in the planning activity.
These classes are networks, blocks, zones, focal points, and landscape and they were compiled
based on several previous studies. The ontology allows one to map the relationships among
the entities and components of the model and to understand how they work.
The methodology embodied in the formulation model concerns the series of steps that
are necessary to follow in a certain order to arrive at the urban program departing from the
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context. So far, research permitted to link such a methodology to a large data model formed
by key concepts, called patterns, and to the relations among them.
Still, the relation between ontological objects and urban patterns is not completely clear
yet. Are they the same type of entities? This is an important aspect to clarify in further
research. It is our hope that in fact, the exhausting description of these concepts will allow one
to understand the overall process as a vast relational database constituted of independent but
interrelated parts (patterns and sub-patterns). So, future research will be concerned with using
an ontology editor to describe the concepts and the relations among them exhaustively so as
to arrive at the rules for generating programs from the context.
7.3. The Goal
As said before, by planning space, one can prevent the waste of resources allowing, at
the same time, to maximize the satisfaction of population needs. Planning plays, therefore, a
key role in spatial and social organization (D. Harvey 2009). First, because it defines objectives
that clarify the mission of the territory, and second because it establishes levels of
effectiveness and efficiency by implementing measures to attain defined goals (Drucker 2007).
A computational platform, here expressed by an ontology, facilitates the creation and
the management of such a more complex planning instrument. With the ontology sketch was
thus possible to classify the core entities of the planning domain knowledge, as well as set up a
strategy to assess to its inconsistencies as well as reasoning the model.
By undertake this first step towards the ontology building it was possible to define the
strategy to implement the planning instrument in a more accurate, flexible and open process.
7.4. The Model
According to what was said above, it is important to guarantee that the theories on which the
proposed model is based are theoretically sound and meet to the desired goal. The academic
theories used as a basis for this study are threefold: are well-known.
The first one is Duarte’s model for the mass customization of housing (2001), upon
which the formulation conceptual model was developed. Its premises are focused on context,
interpretation, and formulation. The contribution of this model is to provide the technical
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apparatus, which is based on Stiny’s description and shape grammars and permits to link
contextual descriptions to programmatic descriptions and then these to design outcomes.
The second theory is the notion of pattern language proposed by Christopher Alexander
(1977), which launched the bases for a planning language theory. Alexander’s premises depart
from linguistics theory, which defines language as a combinatorial and creative method of
communication in different contexts, with clear instructions, and within a defined vocabulary.
The aim for this language is to allow users to manipulate creatively its ingredients to develop
an appropriate speech that is a design adequate to a given context. In planning, such
characteristics are particularly useful for enabling a creative and flexible process.
The third theoretical framework consists in the use of a computational data model – a
computational ontology (Gruber & others 1995) – to describe the semantic relational data of a
given domain in a systematic way, as well as the relations among such entities and their
instances. This framework will be used to describe both urban space and the urban planning
process, thereby defining the formulation model.
7.5. The Outcome
This research has provided the elaboration of the skeleton of the pre-design framework. This
means that its components were developed and combined, and the methods to define its
structure had also been implemented.
The product of this research is therefore the development of the basic concepts of the
formulation model, its methodology, its components, and the way data is manage to harness
good results upon its future implementation.
Other relevant and complimentary outcomes are the development of an ontology to
support urban descriptions and the development of a tentative pattern language, adequate to
the Western cultural context, that revises and complements Alexander’s pattern language.
Together, the proposed ontology and pattern language will constitute the basis for future
research, concerned with the inference of rules to link contextual features to programmatic
descriptions.
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7.6. Reflections for future research
A large part of this study is dedicated to the discovery of the most appropriate methodologies
and tools to intervene in urban space with the objective of producing better living conditions
for populations. However one cannot disregard that formulation in its primordial concept is
far ahead from the definition of methods and techniques. An important concern pointed out
in several chapters of this research is the necessity of taking into account places’ particularities
and citizen’s aspirations (inhabitants and visitors) as they are the users of cities. Emphasizing
this concern site interventions are increasingly more global and homogeneous both in terms of
program and design proposal. She refers that in addition to local and global marketing
strategies there is today an array of mandatory regulations and communitarian directives
concerning patrimonial values, accessibilities, security and public sanitation, among other
aspects, that are leading towards a gradual standardization of public spaces. One can also
argue that portions of cities are drawn as finished objects, places without a future anima, in a
sort of a perfect city scale model. In contrast, our research aims at urban planning strategies
that can incorporate the desires and expectations of citizens.
Quite often today, spaces are created where the urgency of consumption and the hyper-
programming constrain free choice. Urban programs will thus have to leave room for natural
processes of urban evolution to take place in order to avoid the excesses of prescriptive or
mandatory policies. They should be formulated in ways that define flexible rather than rigid
specifications to enable unexpected while creative transformations along time.
This goal constitutes a relevant focus of the developed model. Flexibility is considered,
since the beginning of this study, as a core feature of urban programs and design proposals
alike.
One fact seems to be clear. The ontological framework is essential to build the data
model. However crucial questions still require further clarification, namely: what quantity or
quality of information is necessary to embed in the model? Furthermore where does it come
from? In operational terms one can argue that the ontology editor will solve a large part of the
data structure. However, how does one detail the ontology93? Will one simply seat in front of
93. The development of the model.
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the computer and develop the model’s concepts and relations based on personal experience?
If such happens, where will one search for the information that one does not possess yet?
To answer to this question is, in summary, to explain the methodology of future
research. In fact, it is possible to collect a great amount of relevant data through literature
reviews or by undertaking additional methods and experiences.
The brief conclusion is that the use of an ontology editor seems to be insufficient to
eliminate all the expectable inconsistencies. The model has, thus, to be built using additional
sources and methods.
7.7. The Opportunity
There is one concept concerned with the description of building components and associated
information that can provide a useful reference of the development of the urban formulation
model.
This concept is known as BIM.
In summary, Building Information Models (BIM)94 comprise a system that aims at incorporating
all aspects of design from geographic information, to building geometry, to component
relationships, and finally, to the quantities and properties of the building components. BIM
requires a purpose-built foundation to manage the amount of data generated. Such a
description closely corresponds to the Urban Pattern Language (UPL) framework. The idea is
depart from this correspondence to build a similar relational model, comprising a wide range
of data to describe urban space and its properties. Such a City Information Model (CIM),
94 . Building Information Modeling is the process of generating and managing building data during its life cycle. Typically it uses three-dimensional, real-time, dynamic building modeling software to increase productivity in building design and construction. The process produces the Building Information Model (also abbreviated BIM), which encompasses building geometry, spatial relationships, geographic information, and quantities and properties of building components. Building information modeling covers geometry, spatial relationships, light analysis, geographic information, quantities and properties of building components (for example manufacturers' details). BIM can be used to demonstrate the entire building life cycle, including the processes of construction and facility operation. Quantities and shared properties of materials can be extracted easily. Scopes of work can be isolated and defined. Systems, assemblies and sequences can be shown in a relative scale with the entire facility or group of facilities. BIM can be seen as a companion to PLM as in the Product Development domain, since it goes beyond geometry and addresses issues such as Cost Management, Project Management and provides a way to work concurrent on most aspects of building life cycle processes. BIM goes far beyond switching to a new software. It requires changes to the definition of traditional architectural phases and more data sharing than most architects and engineers are used to. BIM is able to achieve such improvements by modeling representations of the actual parts and pieces being used to build a building. This is a substantial shift from the traditional computer aided drafting method of drawing with vector file-based lines that combine to represent objects.
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however, will have a wider semantic core and model hundreds of thousands of components
more, when compared to the BIM and so it will represent a significantly more complex
challenge. The goal of future research is to overcome such hurdles and develop such model.
Glossary
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Introduction
Towards building an ontology is crucial the access to a common and shared lexicon (part of the
aim of the ontology theory). The description of technical terms related with this specific field
facilitates the engagement of such framework.
This glossary presents hence an urban planning data synopsis (urban management, design,
language, and methods) based on sorted written documents, namely; ESRI's Dictionary of GIS
Terminology (Kennedy 2001), (Gann et al. 2003), (Evans et al. 2007), (Moughtin et al. 2003), among
other references.
This glossary is intended to provide general assistance, not authoritative definitions of terms
which are sometimes controversial or used with different meanings in different contexts, in
order to facilitate an application of specific technical terms.
Terms
ACCESSIBILITY: The ability of people to move round an area and to reach places and facilities, including elderly and disabled people, those with young children and those encumbered with luggage or shopping.
ACCESSORY USE (a) (GIS): The use of a building, structure or land that is subordinate to, customarily incidental to, and ordinarily found in association with, a principal use, which it serves.
ACCESSORY USE (b): A building or a usage of land that is additional to primary use. A garage apartment or granny flat located behind the main house is an example of an accessory use.
ACTIVITY CENTER (a) (GIS): A community focal point providing for the combination, rather than scatteration, of general retail, service commercial, professional office, higher density housing, and appropriate public/quasi-public uses.
ACTIVITY CENTER (b): A central area within a neighborhood or at the intersection of several neighborhoods, that serves as a formal and/or informal gathering place. An activity center can be a commercial area with a variety of different types of retail establishments, often with public open space, a formal park, or any area that promotes interaction with other people on a personal and impersonal level and is pedestrian-oriented.
ACTIVE FRONTAGE: This refers to ground floors with windows and doors onto the street which create interest and activity. This normally means shopfronts but can include atriums and foyers.
ACTION PLANNING: Participation techniques, including community planning weekends and Urban Design Action Teams (UDATs), which enable local people and invited teams of professionals to explore design ideas for particular areas over one or several days.
ACTIVITY SPINE: Street or streets along which activity is concentrated.
Activity Node: Concentration of activity at a particular point.
ACRE (GIS): 43,560 square feet (about the size of a football field).
ADAPTABILITY: The capacity of a building or space to be changed so as to respond to changing social, technological and economic conditions.
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AGRICULTURAL ASSESSMENT (GIS): A state program in which land used for agricultural purposes is assessed based on its value as agricultural land as opposed to a higher valuation.
AREA APPRAISAL: An assessment of an area’s land uses, built and natural environment, and social and physical characteristics.
AREA MASTER PLAN OR AREA PLAN (GIS): Area Master Plans: Area master plans consist of a plan map along with supporting data, text and other maps. They provide specific recommendations on a planning area or sub-region basis on the environment, historic preservation, living areas, housing, commercial areas, employment areas, urban design, circulation, and transportation.
ARCHITECTURE AND PLANNING CENTRE (UK): An institution which provides a focus for a range of activities and services (such as discussions, information, exhibitions, collaboration and professional services) relating to architecture and planning.
ARTERIAL (GIS): A highway, usually within a 120-foot right-of-way, for through traffic with access controlled to minimize direct connections, usually divided and on a continuous route.
AT-GRADE (GIS): Level for a road, building or other structure at the same grade or level as the adjoining property (as opposed to a depressed or elevated road, building or other facility).
ATRIUM: A circulation space, normally in the centre of an office building. This is often a high space with a glass roof that is the reception space for the building and the vertical circulation
AVERAGE DAILY TRAFFIC (ADT): The average number of vehicles passing a specified point on a highway during a 24-hour period.
BASE DISTRICT: A zoning district that establishes regulations governing land use and site development in a specific geographic area. Example: - A minimum lot size of 10,000 square feet, - A minimum lot width of 60 feet, - That the house covers no more than 35% of the lot, - That all of the improvements (the house, driveway, sidewalk, etc.) cover no more than 40% of the lot, - That the house be no taller than 35 feet, - That the house be at least 25 feet from the street front.
BASIC PLAN: Phase 1 of the Comprehensive Design Zone process. It sets forth general land use relationships,
including the approximate number of dwelling units and building intensity. Proposed land uses are also described.
BERM: An earthen mound designed to provide visual interest on a site, screening of undesirable views, noise reduction, etc.
BEST MANAGEMENT PRACTICES (BMPs): Conservation practices or systems of practices and management measures that control soil loss and reduce water quality degradation caused by nutrients, animal waste, toxins and sediment.
BIKEWAY: A lane, path or other surface reserved exclusively for bikers.
BRIEF: This guide refers to site-specific briefs as development briefs. Site-specific briefs are also called a variety of other names, including urban programs, planning briefs and development frameworks.
BUILDING LINE: The primary front face of buildings along a street. Where all of the buildings share a common building line (which can be curved) there is continuous enclosure along the street.
BUILDING ELEMENTS: Doors, windows, cornices and other features which contribute to the overall design of a building.
BUILDING ENVELOPE GUIDELINES: Diagram(s) with dimensions showing the possible site and massing of a building.
BUILDING EXPLORATORY: A centre for explaining, interpreting and providing information on the built environment.
BUILDING LINE: The line formed by the frontages of buildings along a street. The building line can be shown on a plan or section.
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BUFFER (a): An area of land designed or managed for the purpose of separating and insulating two or more land areas whose uses conflict or are incompatible (trees separating homes from an expressway). BUFFER (b) OR BUFFER STRIP: Landscaped areas, open spaces, fences, walls, berms, or any combination of these, used to physically separate or screen one land use or piece of property from another. Buffers are often used to block light or noise.
BUFFERYARD: One of several specific combinations of minimum building setbacks, landscaped yard widths, and plant material requirements set forth in the Landscape Manual for use in buffering incompatible land uses.
BUILT ENVIRONMENT: The urban environment consisting of buildings, roads, fixtures, parks, and all other improvements that form the physical character of a city.
BULK: The combined effect of the arrangement, volume and shape of a building or group of buildings. Also called massing.
BUS RAPID TRANSIT (BRT) (GIS): A fixed guideway transit (FGT) system in which transit buses operate on rights-of-way that are physically or otherwise off-limits to regular vehicular traffic. These systems are often constructed so that they can be upgraded to light-rail vehicle operations when ridership grows beyond the operational capacity of transit buses.
CHARACTER: The image and perception of a community as defined by its built environment, landscaping, natural features and open space, types and style of housing, and number and size of roads and sidewalks.
CHARACTER ASSESSMENT: An area appraisal identifying distinguishing physical features and emphasising historical and cultural associations.
COMPATIBILITY STANDARDS: Development regulations established to minimize the effects of commercial, industrial, or intense residential development on nearby residential property. These standards usually include: - Regulation of building height - Minimum and maximum building setbacks - Buffers - Building design - Controls to limit the impact of lighting on adjacent properties
COMPREHENSIVE PLAN: A document, or series of documents, that serves as a guide for making land use changes, preparation of capital improvement programs, and the rate, timing, and location of future growth. It is based upon establishing long-term goals and objectives to guide the future growth of a city. It is also known as a Master or General Plan. Elements of a Comprehensive Plan include: - Economic Development - Environment - Housing - Land Use - Recreation and Open Space - Transportation.
CONTEXT: The setting of a site or area, including factors such as traffic, activities and land uses as well as landscape and built form.
CONTEXT CONDITION (Language): Constrains the syntax; it describes the set of wellformed expressions of a language.
CONTEXT (or site and area) APPRAISAL: A detailed analysis of the features of a site or area (including land uses, built and natural environment, and social and physical characteristics) which serves as the basis for an urban design framework, development brief, design guide or other policy or guidance.
COUNTRYSIDE DESIGN SUMMARY: Supplementary planning guidance prepared by a local authority to encourage a more regionally and locally based approach to design and planning.
CLUSTER DEVELOPMENT (GIS): An alternative development technique under zoning and subdivision regulations. A cluster subdivision is basically one in which a number of residential lots are grouped or clustered, leaving some land undivided for common use. Generally the same number of lots or dwelling units permitted under conventional subdivision procedures are clustered on smaller-than-usual lots. The land remaining from lot reduction is left undivided and is available as common area or open space.
COMMUNITY ACTIVITY CENTER (GIS) (as defined in Master Plans): A commercial center containing 10-25 acres of commercial development on a site area of 20-30 acres, serving a population of at least 50,000 and anchored by a
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general merchandise store and may also include a supermarket. A community activity center should also include other commercial, public/quasi-public and residential uses.
COMMUNITY CENTERS (GIS): Concentration of activities, services and land uses that serve, and are focal points for, the immediate neighborhoods.
COMMUNITY (as defined in some master plans): A grouping of neighborhoods and villages, the population of which may range from 23,000 to 30,000 in suburban areas and up to 40,000 in corridor communities. Most communities should have as their centers of focal points a Community Activity Center.
CONSTRAINED LONG-RANGE PLAN (CLRP) (GIS): The approved regional plan for highway, transit, and bikeway projects, as well as major jurisdictional and regional studies.
CORRIDOR(S) (GIS): An uninterrupted path or channel of developed or undeveloped land paralleling the route of a street or highway. b. The land within one-quarter mile of both sides of designated high-volume transportation facilities, such as arterial roads. If the designated transportation facility is a limited access highway, the corridor extends one-quarter mile from the interchanges.
CRIME PATTERN ANALYSIS: Carried out by the Police and is available through liaison with the Architectural Liaison Officer/Crime Prevention Design Adviser. It comprises four components: crime series identification, trend identification, “hot-spot” analysis and general profile analysis. This last aspect includes an examination of demographic and social change and its impact on criminality and law enforcement.
DEFENSIBLE SPACE: Public and semi-public space that is “defensible” in the sense that it is surveyed, demarcated or maintained by somebody. Derived from Oscar Newman’s 1973 study of the same name, and an important concept in securing public safety in urban areas, defensible space is also dependent upon the existence of escape routes and the level of anonymity which can be anticipated by the users of the space.
DENSITY (a): dph - Dwellings per hectare.
DENSITY (b): The floorspace of a building or buildings or some other unit measure in relation to a given area of land. Built density can be expressed in terms of plot ratio (for commercial development); number of units or habitable rooms per hectare (for residential development); site coverage plus the number of floors or a maximum building height; or a combination of these.
DENSITY (c): A measure of the amount of housing in a particular area (acre or a hectare). The simplest measure of density is the number of residential units per hectare which ranges for 30u/ha in a suburban area to 200u/ha or more in a city centre. Density can also be measured using habitable rooms or bed spaces which takes account of the type of units.
DENSITY (d) (GIS): The number of dwelling units or persons per acre of land, usually expressed in units per gross acre. Single-family detached dwellings (range from less than 1 to 6 per acre) on a single lot. Townhouses (range from 6 to 12 per acre) attached in a row. Multifamily Apartments (range from 12 to 48 per acre) in one structure.
DESIGN ADVISORY PANEL: A group of people (often architects) with specialist knowledge, which advises a local authority on the design merits of planning applications or other design issues. Also known as an architect’s panel.
DESIGN ASSESSMENT: An independent assessment of a design usually carried out for a local authority by consultants, another local authority or some other agency.
DESIGN GUIDE: A document providing guidance on how development can be carried out in accordance with the design policies of a local authority or other organisation often with a view to retaining local distinctiveness.
DESIGN PRINCIPLE: An expression of one of the basic design ideas at the heart of an urban design framework, design guide, development brief or a development.
DESIGN STANDARDS: Specific, usually quantifiable measures of amenity and safety in residential areas.
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DESIGN STATEMENT (a): A pre-application design statement is made by a developer to indicate the design principles on which a development proposal in progress is based. It enables the local authority to give an initial response to the main issues raised by the proposal. (b) A planning application design statement sets out the design principles that the planning applicant has adopted in relation to the site and its wider context, as required by PPG1.
DESIRE LINE: An imaginary line linking facilities or places which people would find it convenient to travel between easily.
DEVELOPMENT BRIEF: A document, prepared by a local planning authority, a developer, or jointly, providing guidance on how a site of significant size or sensitivity should be developed. Site-specific briefs are sometimes known as planning briefs, urban programs and development frameworks.
DEVELOPMENT (as defined in Zoning Ordinance) (GIS): Any activity that materially affects the condition or use of dry land, land under water, or any structure.
DOWNZONING (GIS): A popular term for an action that changes a property to a lower density, in effect limiting development to less-intense uses than previously permitted.
DWELLING UNIT (GIS): A room or group of rooms, occupied or intended for occupancy as separate living quarters.
ELEVATION (a): The facade of a building, or the drawing of a facade.
ELEVATION (b): The front, back or side face of a building.
ENCLOSURE: The use of buildings to create a sense of defined space.
ENCLOSURE RATIO: A measure of the shape of a street expressed as a ratio in which the first number relates to the height of the buildings and the second to the width of the street. A street with an enclosure ratio of 1:2 is therefore twice as wide as the height of the buildings.
ENERGY EFFICIENCY: The extent to which the use of energy is reduced through the way in which buildings are constructed and arranged on site.
ENVIRONMENTAL IMPACT STATEMENT (EIS) (GIS): A document, prepared by a federal agency, on the environmental impact of its proposals for legislation and other major actions that significantly affect the quality of the human environment. Environmental Impact Statements are used as tools for decision making and are required by the National Environmental Policy Act. Similar environmental analyses are undertaken by state and local agencies.
EYES OF THE STREET: Refers to views out of building that provide surveillance of public areas.
EXPRESSION (Language): Is a meaningful, wellformed element of a language; the following are synonyms: word, statement, sentence, document, diagram, model, term, piece of data, clause, and module.
FAÇADE: The front wall of a building.
FEASIBILITY: The viability of development in relation to economic and market conditions.
FENESTRATION: The arrangement of windows on a facade.
DIAGRAM: A plan showing the relationship between built form and publicly accessible space (including streets) by presenting the former in black and the latter as a white background (or the other way round).
FIXED GUIDEWAY TRANSIT (FGT): Transit service provided on its own right-of-way: a rail track, physically restricted vehicle lanes, or a dedicated roadway in the road and highway system. Both the Metrorail regional rapid transit and MARC commuter rail systems that serve Prince George’s County are FGT systems.
FLAG LOT (GIS): A flag-shaped lot, created under the Optional Residential Design Approach provisions of Subtitle 24, which has a street frontage smaller than that other required for the zone in which it is located.
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FLOATING ZONE (GIS): A zone that is more flexible than euclidean zones in terms of permissible densities, intensities and land uses and overall development design opportunities. Most floating zones require the following findings by the District Council to be granted: 1) The proposed zone is in conformance with the Master Plan; 2) Is compatible with the surrounding community; and 3) Meets the purposes of the zone. Findings of change or mistake, required for granting a euclidean zone, are not required for floating zones. Some floating zones require Master Plan recommendation.
FLOODPLAIN (GIS): A relatively flat or lowland area adjoining a river, stream, or watercourse, which is subject to periodic, partial or complete inundation.
FLOOR AREA RATIO (FAR): The ratio of the gross floor area of a building to the area of the lot on wich it is located.
FORECAST (GIS): As defined for use in the Council of Governments (COG) Cooperative Forecasting Program, a projection tempered by stated policy considerations, including the reconciliation of past and current trends with current and future policies. Ideally, forecasts reflect the best professional judgment concerning the impact of trends and present conditions on the future trend of development and the likely effectiveness of policies to alter this trend. Therefore, forecasts should represent the most realistic assessment of the future.
FORM: The layout (structure and urban grain), density, scale (height and massing), appearance (materials and details) and landscape of development.
Frontage: Similar to facade - the front face of a building where it has its main door windows.
FRUIN ANALYSIS: A method of analysing pedestrian movement devised by Bernard Fruin. It applies a “level of service” concept to pedestrian flows. Fruin defined capacity and speeds of movement in various forms of corridors, pavements and other pedestrian routes.
FUTURE SEARCH: A participation technique enabling groups of people to identify common interests, discuss ideas and share information and experience. “Open space” is a similar technique.
GEOGRAPHIC INFORMATION SYSTEM (GIS): An organized collection of computer hardware, software and geographic data designed to efficiently capture, store, update, manipulate, analyze and display all forms of geographically referenced information.
GREEN AREA (GIS): An area of land associated with, and located on the same parcel of land as, a building for which it serves to provide light and air, or scenic, recreational, or similar purposes.
GREEN BUILDING: Practices that consider the impacts of buildings on the local, regional, and global environment, energy and water efficiency, reduction of operation and maintenance costs, minimization of construction waste, and eliminating the use of harmful building materials.
GREENWAYS: Areas of protected open space that follow natural and manmade linear features for recreation, transportation and conservation purposes and link ecological, cultural and recreational amenities. GRAIN (b): The complexity and coarseness of an urban area. Fine grained areas have a large number of different buildings and closely spaces streets. Course grained areas have large blocks and building and little architectural variety.
GROSS FLOOR AREA (GFA): The total number of square feet of floor area in a building.
HEIGHT: The height of a building can be expressed in terms of a maximum number of floors; a maximum height of parapet or ridge; a maximum overall height; any of these maximum heights in combination with a maximum number of floors; a ratio of building height to street or space width; height relative to particular landmarks or background buildings; or strategic views.
HIGH-OCCUPANCY VEHICLE (HOV): A passenger vehicle containing more than one person. HOV facilities—such as John Hanson Highway (US 50) in Prince George’s County—generally require a minimum number of occupants for a vehicle to be granted access to HOV lanes.
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HIGH STREET: Traditionally a high street is a road through the heart of an urban area that carries all of the through traffic and is also where the greatest number and most important shops are sited together with civic functions. These streets would once have been the “shopfront” of the town or city. Now bypasses often mean that they no longer carry traffic but they do still tend to be the focus for the shopping area.
HUMAN SCALE: The use within development of elements which relate well in size to an individual human being and their assembly in a way which makes people feel comfortable rather than overwhelmed.
IDENTITY: The memorability or sense of place on an urban area. An area with identity is recognisable and has a distinctive character created by the size, shape or design of the buildings.
IN-CURTILAGE PARKING: Parking within a building’s site boundary, rather than on a public street or space.
INDEPENDENT DESIGN AUDIT: An assessment of a design, carried out for a local authority by consultants, another local authority or some other agency.
INDICATIVE SKETCH: A drawing of building forms and spaces which is intended to convey the basic elements of a possible design.
INTERPRETATION (Language): Extracts the information from a piece of data; it is a mapping of data to a semantic domain.
LANDMARK: A building or structure that stands out from its background by virtue of height, size or some other aspect of design.
LANDSCAPE: The character and appearance of land, including its shape, form, ecology, natural features, colours and elements and the way these components combine. Landscape character can be expressed through landscape appraisal, and maps or plans. In towns “townscape” describes the same concept.
LAND USE (OR USE) (GIS): The types of buildings and activities existing in an area or on a specific site. Land use is to be distinguished from zoning, the latter being the regulation of existing and future land uses. LANGUAGE: Is a possibly infinite set of expressions used to communicate; it is a synonym to notation; a language allows us to syntactically represent information.
LAYOUT: The way buildings, routes and open spaces are placed in relation to each other.
LAYOUT STRUCTURE: The framework or hierarchy of routes that connect in the local area and at wider scales.
LEGIBILITY: The degree to which a place can be easily understood and traversed.
LIVE EDGE: Provided by a building or other feature whose use is directly accessible from the street or space which it faces; the opposite effect to a blank wall.
LOCAL DISTINCTIVENESS: The positive features of a place and its communities which contribute to its special character and sense of place.
LYNCHIAN ANALYSIS: The widely used method of context appraisal devised by the urban designer Kevin Lynch. It focuses on gateways to an area, nodes, landmarks, views and vistas, and edges and barriers.
MAJOR COMMUNITY ACTIVITY CENTER (as defined in master plans): A commercial center containing 20-50 acres of commercial development on a site area of 30-60 acres, serving a population of at least 150,000. A major community activity center typically includes uses listed under community activity center plus one or more general merchandise anchor stores. Can also be defined as a community focal point providing for a concentration of activities such as general retail, service commercial, professional office, higher-density housing, and appropriate public and open space uses easily accessible by pedestrians.
MANDATORY (LAND) DEDICATION (GIS): Land excluded from subdivision approved for residential development. The land is dedicated to M-NCPPC (or held in private ownership) for the purpose of providing suitable and adequate open space, light, and air to serve the recreational needs of the future occupants of the subdivision.
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MASTER PLAN: A document that guides the way an area should be developed. It includes a compilation of policy statements, goals, standards, maps and pertinent data relative to the past, present, and future trends of a particular area of the County including, but not limited to, its population, housing, economics, social patterns, land use, water resources and their use, transportation facilities, and public facilities.
MASSING (a): The size and height of a building.
MASSING (b): The combined effect of the height, bulk and silhouette of a building or group of buildings.
MIXED USE (MU): A type of development that combines residential, commercial, and/or office uses, within a commercial or office zoning district, into one development or building. For example, a mixed-use building could have several floors. On the bottom floor, the space could be dedicated to retail or offices. The remaining two or three floors could be for apartments or condominiums. A Mixed Use Combining District allows residential, commercial, retail, and office uses to be combined in a single development. Under the Smart Growth Infill Ordinance two types of Mixed Use development are now possible with adopted neighborhood plans that include these uses as part of their plans: - Neighborhood Urban Center allows a variety of residential types (condos, apartments, townhouses) and commercial, office, and retail uses clustered together in a development of less than forty acres. - A Neighborhood Mixed Use Building allows residential uses above ground floor commercial uses. - Multi-Family: A building that is designed to house more than one family.
MIXED USES: A mix of uses within a building, on a site or within a particular area. “Horizontal” mixed uses are side by side, usually in different buildings. “Vertical” mixed uses are on different floors of the same building.
MIXED-USE ZONING (GIS): Zoning that permits a combination of uses within a single development. Many zoning districts specify permitted combinations of, for example, residential and office/commercial uses. The term has also been applied to major developments, often with several high-rise buildings, that may contain offices, shops, hotels, apartments and related uses.
MODAL SPLIT: How the total number of journeys in an area or to a destination is split between different means of transport, such as train, bus, car, walking and cycling.
MODELLING LANGUAGE (Language): Is used for specifying and documenting properties of a system in different abstractions, and from different points of view.
MOVEMENT: People and vehicles going to and passing through buildings, places and spaces. The movement network can be shown on plans, by space syntax analysis, by highway designations, by figure and ground diagrams, through data on origins and destinations or pedestrian flows, by desire lines, by details of public transport services, by walk bands or by details of cycle routes.
NATURAL SURVEILLANCE (or supervision): The discouragement to wrong-doing by the presence of passers-by or the ability of people to be seen out of surrounding windows. Also known as passive surveillance (or supervision).
NEIGHBORHOOD: (As defined in some master plans) The smallest unit of community structure. Neighborhood population ranges from 3,000 to 6,000, depending on the ratio of single-family to multifamily housing. NEIGHBORHOOD CONVENIENCE CENTER (as defined in master plans): A commercial center containing 2-6 acres of commercial development on a site of 4-10 acres, serving a population of approximately 8,000 and anchored by a small grocery or drug store. It should also include a limited range of other commercial and residential uses.
NET LOT AREA (GIS): The total contiguous area included within a lot, excluding public ways (i.e., streets, alleys) and land with 100-year floodplain.
NODE (GIS): A location along a corridor at a major intersection or major transit stop (bus or rail) that consists of a concentration of high-intensity, mixed-use residential and commercial development. Nodes should be interspersed with stretches of lower intensity land uses or open space.
NODE: A place where activity and routes are concentrated often used as a synonym for junction.
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NOTATION (Language): Is a syntactic representation of information; a synonym to language; what the user deals with.
OPEN SPACE (a) (land use, not zoning) (GIS): Areas of land not covered by structures, driveways, or parking lots. Open space may include homeowners association common areas, parks, lakes, streams and ponds, etc.
OPEN SPACE (b): An area set aside or reserved for public or private use with very few improvements. Types of open space include include:- Golf Courses- Agricultural Land- Parks- Greenbelts- Nature Preserves. In many cases, land designated as open space lies within the 100-year flood zone, has sensitive environmental features such as wetlands or aquifer recharge features such as caves and fault lines, or has unstable slopes.
PASSIVE SURVEILLANCE: See “natural surveillance”.
PEDESTRIAN-ORIENTED DESIGN (GIS): Land use activities that are designed and arranged in a way that emphasizes travel on foot rather than by car. The factors that encourage people to walk are often subtle, but they most regularly focus upon the creation of a pleasant environment for the pedestrian. Elements include compact, mixed-use development patterns with facilities and design that enhance the environment for pedestrians in terms of safety, walking distances, comfort, and the visual appeal of the surroundings. Pedestrian-friendly environments can be created by locating buildings close to the sidewalk, by lining the street with trees, and by buffering the sidewalk with planting strips or parked cars, small shops, street-level lighting and signs, and public art or displays.
PERFORMANCE CRITERION (pl. criteria): A means of assessing the extent to which a development achieves a particular functional requirement (such as maintaining privacy). This contrasts with a standard, which specifies how a development is to be designed (by setting out minimum distances between buildings, for example). The art of urban design lies in balancing principles which may conflict. Standards may be too inflexible to be of use in achieving a balance. Performance criteria, on the other hand, make no prior assumptions about the means of achieving a balance.
PERMEABILITY (a): The degree to which an area has a variety of pleasant, convenient and safe routes through it.
PERMEABILITY (b): The ease with which people can move around an urban area. A permeable neighbourhood has plenty of streets and it is possible to move through the area by a variety of routes.
PERSPECTIVE: Illustration showing the view from a particular point as it would be seen by the human eye.
PLACECHECK: A type of urban design audit advocated by the Urban Design Alliance, based on the Connected City approach. A local collaborative alliance or partnership uses checklists to investigate the connections in the built environment, in its movement network and among the people who shape it. The Placecheck becomes the first step in a continuing collaborative process of urban design.
PLANNING: The process of setting development goals and policy, gathering and evaluating information, and developing alternatives for future actions based on the evaluation of the information.
PLANNING BRIEF: This guide refers to site-specific briefs as development briefs. Other names, including planning briefs, urban programs and development frameworks are also used.
PLANNING FOR REAL: A participation technique (pioneered by the Neighbourhood Initiatives Foundation) that involves residents and others with an interest coming together to make a model of their area and using it to help them determine their priorities for the future.
PLANNING POLICY GUIDANCE NOTES (PPGs): Documents embodying Government guidance on general and specific aspects of planning policy to be taken into account in formulating development plan policies and in making planning decisions.
PLOT RATIO (a): A measurement of density generally expressed as gross floor area divided by the net site area.
PLOT RATIO (b): A measure of density for non-residential used. This is expressed as a ratio in which the first number relates to the floor area of the building and the second to the area of the site. A 2:1 ratio therefore denotes a
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building that has two times the floor area of the site. This could be a two storey building covering the entire site or a four storey building covering half of the site.
PRIVACY DISTANCE: The distance between the habitable windows of a dwelling necessary to ensure privacy. This is normally 20-23m but can be reduced to 15m in city centres. Where a dwelling has a front on a back the privacy distance relates to the back. On double-loaded flats (see above) it relates to the front.
PROACTIVE DEVELOPMENT CONTROL: Any process by which a local authority works with potential planning applicants to improve the quality of development proposals as early as possible before a planning application is submitted.
PROGRAMMING LANGUAGE (Language): Is used for programming software systems.
PUBLIC ART: Permanent or temporary physical works of art visible to the general public, whether part of the building or free-standing: can include sculpture, lighting effects, street furniture, paving, railings and signs.
PUBLIC DOMAIN: The parts of a village, town or city (whether publicly or privately owned) that are available, without charge, for everyone to use or see, including streets, squares and parks. Also called public realm.
PUBLIC/PRIVATE INTERFACE: The point at which public areas
PUBLIC REALM: The public spaces of an urban area. This includes streets, squares and parks where people are free to walk. It does not include private gardens or courtyards or shopping malls.
SEMANTICS (Language): Defines the meaning of a notation; what information do the expressions in the notation describe.
SEMANTIC DOMAIN (Language): Is a well understood domain of elements. Elements of the semantic domain describe the important properties of what we are trying to define using a language in our context; this means software and hardware systems, and components of such systems.
SEMANTIC MAPPING (Language): Is a mapping that relates each syntactic construct to a construct of the semantic domain; it usually explains new constructs in terms of known constructs.
SETBACK: The distance between a building or structure (not including ground-level parking lots or other paved surfaces) from property lines or from other buildings.
SEVERE SLOPES: Those slopes that are greater than 25 percent. (Example: a 25-foot change in elevation in a 100-foot horizontal distance.)
SITING: The positioning of a building on the ground.
SMART GROWTH: A perspective, method, and goal for managing the growth of a community. It focuses on the long-term implications of growth and how it may affect the community, instead of viewing growth as an end in itself. The community can vary in size; it may be as small as a city block or a neighborhood, or as large as a city, a metropolitan area, or even a region. Smart Growth promotes cooperation between often diverse groups to arrive at sustainable long-term strategies for managing growth. It is designed to create livable cities, promote economic development, and protect open spaces, environmentally sensitive areas, and agricultural lands.
SMART HOUSING: An initiative of the City of Austin to promote sustainable and equitable housing development for low- to moderate-income households. Housing developed under this program would serve the needs of a variety of income levels and be accessible to people with disabilities. The SMART Housing Initiative also requires that housing developed under the program have ready access to transit. SMART stands for:
S afe
M ixed-Incom
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A accessible
R easonably Priced
T ransit-oriented
SPECIFIC DESIGN PLAN (SDP): Phase III of the Comprehensive Design Zone process. It is a precise site plan that includes exact locations of lots, buildings and streets, etc., architectural plans, exterior building elevations and detailed landscaping plans.
SPRAWL: A haphazard and disorderly form of urban development. There are several elements that characterize sprawl: - Residences far removed from stores, parks, and other activity centers, - Scattered or “leapfrog” development that leaves large tracts of undeveloped land between developments, - Commercial strip development along major streets, - Large expanses of low-density or single use development such as commercial centers with no office or residential uses, or residential areas with no nearby commercial centers, - Major form of transportation is the automobile, - Uninterrupted and contiguous low- to medium-density (one to six du/ac) urban development, - Walled residential subdivisions that do not connect to adjacent residential development.
STAR BUILDING: This relates to a building that is special by virtue of its role. Traditionally this would include churches, town halls and other public institutions. These buildings should be commissioned by public competition but are not subject to the same rules as other buildings.
STREET HIERARCHY: The relative importance of different streets. This traditionally includes high streets that carry most through traffic and have the greatest number of shops, secondary streets that take traffic into each neighbourhood and have fewer shops and local streets that give access to each of the buildings. Today high streets are often pedestrianised and through traffic is carried on a new level of the hierarchy - the boulevard.
STREETSCAPE: The space between the buildings on either side of a street that defines its character. The elements of a streetscape include: - Building Frontage/Façade, - Landscaping (trees, yards, bushes, plantings, etc.), - Sidewalks, - Street Paving, - Street Furniture (benches, kiosks, trash receptacles, fountains, etc), - Signs, - Awnings, - Street Lighting. SUB-LANGUAGE (Language): Is a subset of the syntactic elements, together with an appropriate adaptation projection.
SUSTAINABILITY: A concept and strategy by which communities seek economic development approaches that benefit the local environment and quality of life. Sustainable development provides a framework under which communities can use resources efficiently, create efficient infrastructures, protect and enhance the quality of life, and create new businesses to strengthen their economies. A sustainable community is achieved by a long-term and integrated approach to developing and achieving a healthy community by addressing economic, environmental, and social issues. Fostering a strong sense of community and building partnerships and consensus among key stakeholders are also important elements.
SUPPORTING CAST BUILDING: This relates to the majority of buildings in an urban area - all of the housing, shops and offices. These create the urban form of an urban area and should be subject to urban design rules.
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TEXTUAL LANGUAGE (Language): Is a language consisting of linear strings of characters and symbols; words, sentences, etc.
TRADITIONAL NEIGHBORHOOD CORRIDOR: The combination of an activity center and the transportation connections linking it to the rest of city. These links may be made by frequent public transit service, walking, cycling, or by car. The major throughway into a traditional neighborhood corridor should be wide enough to accommodate all modes of vehicular transportation, on-street parking, as well as provide space for safe and inviting sidewalks for pedestrians. A Traditional Neighborhood Corridor is characterized by a mixture of various uses and densities such as stores, offices, and different types of housing.
TRANSIT-ORIENTED DEVELOPMENT (TOD): A form of development that emphasizes alternative forms of transportation other than the automobile - such as walking, cycling, and mass transit - as part of its design. Transit-Oriented Development locates retail and office space around a transit stop. This activity center is located adjacent to a residential area with a variety of housing options such as apartments, townhouses, duplexes, and single family houses. Similar to a Traditional Neighborhood Development.
TRANSIT NODES: Stops along a public transportation route where people board and disembark, often where one or more routes intersect with each other. These sites can provide ideal locations for mixed use development as well as transit-oriented development.
URBAN BLOCK: This is an area bounded by streets and occupied by buildings. Sometimes called a perimeter block, the buildings face outwards onto the streets often with a private courtyard in the centre. For housing development this courtyard is often used by residents (sometimes for gardens) for shops it is where servicing takes place and of offices it is often an atrium.
VISUAL/DIAGRAMMATIC LANGUAGE (Language): Is a language based mainly on graphic (topological geometric) elements; it can employ textual elements too.
VISUAL FORMALISM (Language): Is a diagrammatic language that has formal syntax and semantics.
ZONING (a) (GIS): The classification of land by types of uses permitted and prohibited in a district and by densities and intensities permitted and prohibited, including regulations regarding building location on lots. ZONING (b): The method used by cities to promote the compatibility of land uses by dividing tracts of land within the city into different districts or zones. Zoning ensures that a factory is not located in the middle of a residential neighborhood or that a bar is not located next to an elementary school.
ZONING CATEGORY or DISTRICT (GIS): An area designated (zoned) for a type of land use and for a certain density or intensity of development within that type.
ZONING MAP (GIS): The official 1"=200' scale map showing the location of all zoning categories in a given area.
Conventions
Some Conventions of Abbreviated terms in GIS, in Computer Aided Design, and in other languages.
2D: Two Dimensional
3D: Three Dimensional
AEC: Architecture, Engineering, Construction
ALKIS: German National Standard for Cadastral Information
ATKIS: German National Standard for Topographic and Cartographic Information
B-Rep: Boundary Representation
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CAD: Computer Aided Design
CAAD: Computer Aided Architectural Design
DTM: Digital Terrain Model
DXF: Drawing Exchange Format
FM: Facility Management
GDF: Geographic Data Files
GML: Geography Markup Language
IAI: International Alliance for Interoperability
IETF: Internet Engineering Task Force
IFC: Industry Foundation Classes
ISO: International Organization for Standardisation
LOD: Level of Detail
NBIMS: National Building Information Model Standard
OASIS: Organisation for the Advancement of Structured Information Standards
OGC: Open Geospatial Consortium
OSCRE: Open Standards Consortium for Real Estate
SIG 3D: Special Interest Group 3D of the GDI NRW
TC211: ISO Technical Committee 211
TIC: Terrain Intersection Curve
TIN: Triangulated Irregular Network
UML: Unified Modeling Language
URI: Uniform Resource Identifier
VRML: Virtual Reality Modeling Language
W3C: World Wide Web Consortium
XML Extensible Markup Language
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Annexes
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Annex 1 A rule case-study edited by the Protégé rules editor Distance between buildings (Trento 2009)
“Using an existing ontology and rules editor (Protegé2000 + PAL Constraints), authors
implemented a design rule which states that each single family house (denominated
“building”) must not be closer than 15 meters to another building (Figure). (...) By means of the
purposed Knowledge Modelling level, this rule can be linked to the building entities involved in
the design process and formalized in order to support the designers with some inferred
suggestions. (...) The Goals and Constraints editing, through the described mechanism, allow
the coherence of the design to be verified vis-à-vis the objective sets. The research in progress
is revealing the potential of the approach adopted for the preliminary design phase
representing a first-step validation of the illustrated software system implementation.”
9. Design rule formalization on Protégé Axiom Language
Annex 2
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An example of an ontological class edition and its exported XML format
Protégé ontologies can be exported into a XML Schema. In the bottom is shown the class
hierarchy of climatic patterns ontology. At its bottom is shown the the XLM related Shema.
Ontology Class Hierarchy
10. Class edition on Protégé 2000
Ontology XML Schema
<?xml version="1.0" ?>
- <knowledge_base xmlns="http://protege.stanford.edu/xml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://protege.stanford.edu/xml http://protege.stanford.edu/xml/schema/protege.xsd">
- <class> <name>:THING</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value>
</own_slot_value> </class>
- <class> <name>:STANDARD-CLASS</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>:CLASS</superclass> <template_slot>:ROLE</template_slot> <template_slot>:DOCUMENTATION</template_slot>
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<template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:ROLE</template_slot> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot>
</class> - <class> <name>:STANDARD-SLOT</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>:SLOT</superclass> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:SLOT-MAXIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-MINIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-NUMERIC-MAXIMUM</template_slot> <template_slot>:SLOT-NUMERIC-MINIMUM</template_slot> <template_slot>:SLOT-INVERSE</template_slot> <template_slot>:SLOT-DEFAULTS</template_slot> <template_slot>:SLOT-VALUES</template_slot> <template_slot>:ASSOCIATED-FACET</template_slot> <template_slot>:DIRECT-SUBSLOTS</template_slot> <template_slot>:DIRECT-SUPERSLOTS</template_slot> <template_slot>:DOCUMENTATION</template_slot> <template_slot>:SLOT-CONSTRAINTS</template_slot> <template_slot>:SLOT-MAXIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-MINIMUM-CARDINALITY</template_slot> <template_slot>:SLOT-NUMERIC-MAXIMUM</template_slot> <template_slot>:SLOT-NUMERIC-MINIMUM</template_slot> <template_slot>:SLOT-INVERSE</template_slot> <template_slot>:SLOT-DEFAULTS</template_slot> <template_slot>:SLOT-VALUES</template_slot> <template_slot>:ASSOCIATED-FACET</template_slot> <template_slot>:DIRECT-SUBSLOTS</template_slot> <template_slot>:DIRECT-SUPERSLOTS</template_slot>
</class> - <class> <name>Cold Region</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>:THING</superclass>
</class> - <class> <name>Election of the location</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Slopes</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value>
</own_slot_value> <superclass>Election of the location</superclass>
</class>
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- <class> <name>Urban structure</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Public Spaces</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Landscape</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Perish vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value>
</own_slot_value> <superclass>Vegetation</superclass>
</class> - <class> <name>Persistent vegetation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Abstract</value>
</own_slot_value> <superclass>Vegetation</superclass>
</class> - <class> <name>House Type</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>General distribution</name>
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<type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Distribution Plan</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Form and volume</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass> <template_slot>Bioclimatic Pattern_Slot_0</template_slot>
</class> - <class> <name>Orientation</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <class> <name>Color</name> <type>:STANDARD-CLASS</type> - <own_slot_value> <slot_reference>:ROLE</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> <superclass>Cold Region</superclass>
</class> - <slot> <name>Bioclimatic Pattern_Slot_0</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">String</value>
</own_slot_value> </slot>
- <slot> <name>:ASSOCIATED-FACET</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference>
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<value value_type="slot">:ASSOCIATED-SLOT</value> </own_slot_value>
- <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:FACET</value>
</own_slot_value> </slot>
- <slot> <name>:DIRECT-SUBSLOTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:DIRECT-SUPERSLOTS</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value>
</own_slot_value> </slot>
- <slot> <name>:DIRECT-SUPERSLOTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:DIRECT-SUBSLOTS</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value>
</own_slot_value> </slot>
- <slot> <name>:DOCUMENTATION</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:DOCUMENTATION-IN-FRAME</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">String</value>
</own_slot_value> </slot>
- <slot> <name>:ROLE</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-DEFAULTS</slot_reference> <value value_type="string">Concrete</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Symbol</value> <value value_type="string">Abstract</value> <value value_type="string">Concrete</value>
</own_slot_value> </slot>
- <slot>
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<name>:SLOT-CONSTRAINTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:CONSTRAINTS</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:CONSTRAINT</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-DEFAULTS</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:DEFAULTS</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-INVERSE</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-INVERSE</slot_reference> <value value_type="slot">:SLOT-INVERSE</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Instance</value> <value value_type="class">:SLOT</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-MAXIMUM-CARDINALITY</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-DEFAULTS</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:MAXIMUM-CARDINALITY</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Integer</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-MINIMUM-CARDINALITY</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value>
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<slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:MINIMUM-CARDINALITY</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Integer</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-NUMERIC-MAXIMUM</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:NUMERIC-MAXIMUM</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Float</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-NUMERIC-MINIMUM</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:SLOT-MAXIMUM-CARDINALITY</slot_reference> <value value_type="integer">1</value>
</own_slot_value> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:NUMERIC-MINIMUM</value>
</own_slot_value> - <own_slot_value> <slot_reference>:SLOT-VALUE-TYPE</slot_reference> <value value_type="string">Float</value>
</own_slot_value> </slot>
- <slot> <name>:SLOT-VALUES</name> <type>:STANDARD-SLOT</type> - <own_slot_value> <slot_reference>:ASSOCIATED-FACET</slot_reference> <value value_type="facet">:VALUES</value>
</own_slot_value> </slot> </knowledge_base>
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Annex 3
PEST Analysis Template
Urban plan analyzed: ___________________________________________________________________
PEST analysis (political, economical, social, and technological) assesses a standpoint of a particular plan’s
proposition.
criteria examples
a) Ecological/environmental
current legislation b) Future legislation c) International legislation d) Regulatory bodies and
processes e) Government policies f) Government term and
change g) Urban codes h) Initiatives i) Home pressure- groups j) International pressure-
groups k) Conflicts
political economical criteria examples
a) Home economy b) Economy trends c) Overseas related
economies d) General taxation e) Seasonality issues f) Market cycles g) Specific industry factors h) Interest
criteria examples
a) Lifestyle trends b) Demographics c) Social attitudes and
opinions d) Media views e) Law changes affecting
social factors f) Brand, company,
technology image g) Fashion and role models h) Major events and
influences i) Buying access j) Ethnic/religious factors k) Ethical issues
social technological criteria examples
a) Competing technology
development b) Research c) Associated/dependent
technologies d) Replacement
technology/solutions e) Maturity of technology f) Information and
communications g) Technology legislation h) Innovation potential i) Technology access,
licencing j) Intellectual property issues k) Global communications
11. PEST analysis
Note: PEST analysis can be useful before SWOT analysis because PEST helps to identify SWOT factors. PEST and
SWOT are two different perspectives but can contain common factors. SWOT stands for strengths, weaknesses,
opportunities, threats.
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SWOT Analysis Template
Urban plan analyzed: ___________________________________________________________________
This SWOT example is for a new urban plan. Many criteria can apply to more than one quadrant. Identify criteria
appropriate to each specific SWOT situation.
criteria examples
Advantages of proposition? Capabilities? Competitive advantages? Resources, Assets? Knowledge, data? Innovative aspects? Location and geographical? Value, quality? Processes, systems, IT? Cultural, attitudinal, behavioural? Management? Philosophy and values?
strengths weaknesses criteria examples
Disadvantages of proposition? Gaps in capabilities? Lack of competitive strength? Reputation, presence and reach? Financials? Own known vulnerabilities? Timescales, deadlines and pressures? Continuity, supply chain robustness? Effects on core activities, distraction? Reliability of data, plan predictability? Processes and systems? Management?
criteria examples
Territory developments? Social cohesion? Industry and lifestyle trends? Technology development and innovation? Economic development? Environmental concerns? Global influences? Competitors' vulnerabilities? Tactics: e.g., surprise? Information and research? Partnerships? Seasonal, weather, fashion influences?
opportunities threats criteria examples
Social unsteadiness? Political frame? Legislative effects? Environmental effects? Competitor intentions? IT developments? Market demand? New technologies, services, ideas? Obstacles faced? Insurmountable weaknesses? Sustainable financial backing? Economy? Seasonality, weather effects?
12. PEST analysis
Initially develop by Alan Chapman 2005-09 (www.businessballs.com/swotanalysisfreetemplate.htm)
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Regulations and contextual data attributes, proposed codes, types, reference values, data sources, and related calculations (Gil 2009).
Table of Building related attributes
Attributes Codes Types Refs Sources Calculations
Number of inhabitants HABN Socio-economic
1 Census/Plan integer
Gross Floor Area GFA Socio-economic
5 Composite BA * F
Built-up area BA General 1,5 Geometry m2
Number of Floors F General 1,5 Survey/Plan integer
Dwellings area DWEA Socio-economic
7 Survey/Plan m2
Number of Dwellings DWEN Socio-economic
1 Survey/Plan integer
Retail units area RETA Socio-economic
7 Survey/Plan m2
Number of Retail units RETN Socio-economic
4,7 Survey/Plan integer
Construction date COND Cultural 3,4 Census year
Population Ethnic origin POPE Cultural 4 Census % share
Population age POPA Socio-economic
4 Census % share
Population Socio-economic status POPS Socio-economic
4,6 Census % share
Exposure to prevailing winds WNDE Bioclimatic 2,3 Composite m2
Shaded area SHDA Bioclimatic 2 Composite m2
Solar Exposure SOLE Bioclimatic 2,3 Composite SOLO - DIR
Dwellings proximity DWEP Socio-economic
7 Composite SUM DWEN (or DWEA)
Number of parking spaces per dwelling
PRKD Socio-economic
1 Composite PRKN/DWEN
Retail units proximity RETP Socio-economic
7 Composite SUM RETN (or RETA)
Compactness COM Bioclimatic 2 Geometry A/LEN
Length LEN General 2,4,6 Geometry m
Proportion PROP Bioclimatic 2 Geometry LEN/W
Orientation DIR General 2,4 Geometry degrees
Exposure EXP General 2 Geometry integer
Width W General 1,2,4 Geometry m
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State of Conservation CONS Cultural 3,4 Survey/Plan Attribute
Construction type CONT Cultural 3,4 Survey/Plan Attribute
Typology TYP General 2 Survey/Plan Attribute
Ground Floor use GFU Socio-economic
4,6,7 Survey/Plan %share
Upper floors use UFU Socio-economic
6,7 Survey/Plan %share
Surface quality SURF Bioclimatic 2 Survey/Plan Attribute
Solar Orientation SOLO Bioclimatic 2,3 Weather Data
N,S,E,W
Table of Plot related attributes
Attributes Codes Types Refs Sources Calculations
Green area GREA Bioclimatic 2 Attribute/Geometry m2
Common space area COMA Socio-economic 1,4 Attribute/Geometry m2
Private space area PRVA Socio-economic 1,4 Attribute/Geometry m2
Public space area PUBA Socio-economic 1,4 Attribute/Geometry m2
Shaded area SHDA Bioclimatic 2 Composite m2
Dwellings density DWED Socio-economic 1 Composite DWEN/A
Floor Area Ratio or Floor Space Index
FAR or FSI
Socio-economic 5 Composite GFA / TA
Mean number of floors FAVG Socio-economic 1 Composite FSUM/BLDN
Mode number of floors FMOD Socio-economic 1 Composite Mode F
Ground Space Index GSI Socio-economic 1,5 Composite BA / TA
Layers L Socio-economic 5 Composite GFA/BA
Open Space Ratio OSR Socio-economic 5 Composite (TA - BA) / GFA
Retail units density RETD Socio-economic 7 Composite RETN/A
Exposure EXP General 2 Geometry integer
Width W General 1,2,4 Geometry m
Area TA General 1,5 Geometry m2
Table of Block related attributes
Attributes Codes Types Refs Sources Calculations
Length LEN General 2,4,6 Geometry m
Orientation DIR General 2,4 Geometry degrees
Width W General 1,2,4 Geometry m
Area TA General 1,5 Geometry m2
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Floor Area Ratio or Floor Space Index
FAR or FSI
Socio-economic 5 Composite GFA / TA
Mean number of floors FAVG Socio-economic 1 Composite FSUM/BLDN
Mode number of floors FMOD Socio-economic 1 Composite Mode F
Ground Space Index GSI Socio-economic 1,5 Composite BA / TA
Layers L Socio-economic 5 Composite GFA/BA
Open Space Ratio OSR Socio-economic 5 Composite (TA - BA) / GFA
Number of Buildings BLDN Socio-economic 1 Geometry integer
Built-up area BA General 1,5 Geometry m2
Proportion PROP Bioclimatic 2 Geometry LEN/W
Solar Orientation SOLO Bioclimatic 2,3 Geometry N,S,E,W
Green area GREA Bioclimatic 2 Attribute/Geometry m2
Common space area COMA Socio-economic 1,4 Attribute/Geometry m2
Private space area PRVA Socio-economic 1,4 Attribute/Geometry m2
Public space area PUBA Socio-economic 1,4 Attribute/Geometry m2
Dwellings total RETT Socio-economic 6 Composite SUM DWEN (or DWEA)
Retail units total RETT Socio-economic 6 Composite SUM RETN (or RETA)
Dwellings density DWED Socio-economic 1 Composite DWEN/A
Retail units density RETD Socio-economic 7 Composite RETN/A
Number of inhabitants HABN Socio-economic 1 Census/Plan integer
Exposure to prevailing winds WNDE Bioclimatic 2,3 Composite m2
Shaded area SHDA Bioclimatic 2 Composite m2
Pavement width PAVW Socio-economic 1 Geometry m
Vegetation type VEG Bioclimatic 2 Survey/Plan %share
Number of parking spaces PRKN Mobility 1 Survey/Plan integer
Table of Street related attributes
Attributes Codes Types Refs Sources Calculations
Orientation DIR General 2,4 Geometry degrees
Length LEN General 2,4,6 Geometry m
Width W General 1,2,4 Geometry m
Solar Orientation SOLO Bioclimatic 2,3 Weather Data N,S,E,W
Solar Exposure SOLE Bioclimatic 2,3 Composite SOLO - DIR
Number of Buildings BLDN Socio-economic 1 Geometry integer
Pavement width PAVW Socio-economic 1 Geometry m
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Proportion PROP General 2 Geometry LEN/W
Pedestrian area PEDA Mobility 1 Attribute/Geometry m2
Common space area COMA Socio-economic 1,4 Attribute/Geometry m2
Private space area PRVA Socio-economic 1,4 Attribute/Geometry m2
Public space area PUBA Socio-economic 1,4 Attribute/Geometry m2
Vehicular area VEHA Mobility 1 Attribute/Geometry m2
Dwellings total RETT Socio-economic 6 Composite SUM DWEN (or DWEA)
Retail units total RETT Socio-economic 6 Composite SUM RETN (or RETA)
Number of parking spaces per dwelling
PRKD Socio-economic 1 Composite PRKN/DWEN
Slope S Bioclimatic 2,3 Geometry degrees
Global accessibility rank ACCG Mobility 4,6 Network Closeness
Local accessibility rank ACCL Mobility 6 Network Closeness
Global movement flow rank MOVG Mobility 4,6 Network Betweenness
Local movement flow rank MOVL Mobility 6 Network Betweenness
Dwellings proximity DWEP Socio-economic 7 Composite SUM DWEN (or DWEA)
Pedestrian surface share PEDR Socio-economic 1 Composite ?
Retail units proximity RETP Socio-economic 7 Composite SUM RETN (or RETA)
Shaded area SHDA Bioclimatic 2 Composite m2
Exposure to prevailing winds WNDE Bioclimatic 2,3 Composite m2
Viewshed area VWA General 3 Isovist m2
Viewshed compactness VWC General 3 Isovist L/A
Number of parking spaces PRKN Mobility 1 Survey/Plan integer
Surface quality SURF Bioclimatic 2 Survey/Plan Attribute
Vegetation type VEG Bioclimatic 2 Survey/Plan %share
13. Attributes applicable to urban formulation (Gil et al 2009)
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Annex 4
The diagram shows the main classes of pre-design phase. The core ontology (Blocks, Focal Points,
Networks, and Zones) is located in the purple boxes of the diagram entities. Its shared super-
class is Design Core (light purple and dark green boxes).
34. Syntax class hierarchical tree (above left), exported piece of XML Schema (above centre), CPL diagram
classes, subclass-superclass hierarchy, and slots (middle right), CPL diagram zoom - the design core -
Networks, Zones, Blocks, and Landmarks (at the bottom).