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L

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The Neighbourhood Wizard Cause and effect of changes in urban neighbourhoods L on van Berlo / Jos van Leeuwen Agenda Introduction Objective Approach (Experiencing ... – PowerPoint PPT presentation

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Title: L


1
Léon van Berlo / Jos van Leeuwen
  • The Neighbourhood Wizard
  • Cause and effect of changes in urban
    neighbourhoods

2
Agenda
  • Introduction
  • Objective
  • Approach
  • (Experiencing) Liveability
  • Data Collection
  • Knowledge representation
  • Prototype
  • Evaluation and testing
  • Conclusions and future work
  • Coffee break

3
Introduction
  • Quality of the neighbourhood (physical and
    social) ? Increasingly important
  • Local initiatives for neighbourhood improvement
  • Municipalities support these initiatives ?
    Citizen participation
  • Issues
  • Inhabitants focus on their own problems (not the
    ones from their neighbours)
  • Inhabitants dont see the complex dependencies of
    a decision
  • Inhabitants give concrete proposals for change in
    stead of their desire

4
Objective
  • Making citizens realise what the consequences are
    of their ideas for changes
  • By developing a tool that allows citizens to
  • propose changes to their neighbourhood
  • assess the quality of these changes

5
Approach
  • Find a set of indicators for experience of
    liveability of the neighbourhood
  • Find a set of characteristics that affect the
    liveability
  • Determine a BBN that represents the knowledge
  • Build a prototype
  • Narrowing its scope to the plaza type of habitat
  • Testing the prototype in the Dutch city of
    s-Hertogenbosch

6
Experiencing liveabilityLeidelmeijer and
Marsman 1999
7
Example experience by an individual
Appreciation Importance
Satisfaction
Liveability
Characteristics
8
Example experience by an individual
9
Example experience by an individual
10
Experience by another individual
11
Grouping individuals and their needs
  • Wishprofiles
  • Teenagers
  • Yuppies
  • Families
  • Elderly
  • Handicapped (elderly)
  • Aspects
  • Space
  • Liveliness
  • Security
  • Quality
  • Status
  • Traffic

12
Data Collection
  • Questionnaire of liveability regarding the city
    of s-Hertogenbosch
  • Experiences of characteristics such as
  • public furnishing
  • available facilities
  • public accessibility
  • status
  • appearance
  • ambiance
  • etc.
  • For plazas, over 40 characteristics were
    included.
  • Scale of seven possible values
  • Ranging from deficient, through moderate and
    neutral, to ample and excessive.

13
Data Collection
Example Form and function Incoherent Suitable s
urprising conflicting
14
Knowledge Representation
  • Bayesian Network
  • Can deal with uncertainty and interdependent
    variables
  • Determining the structure of a BN
  • 1) Knowledge expert who constructs a network
  • 2) Examining data from the particular domain
  • In this project 2 is used to come to a base
    network which was refined by 1.

15
Structural Learning
  • Hugin (www.hugin.com) was used with
  • PC algorithm (Peter Clark)
  • NPC algorithm (Necessary Path Condition)
  • Constraint-based learning algorithms
  • Derive conditional independence and dependence
    statements by performing statistical tests on
    pairs of variables in the data set

16
BN Structure (1)
17
Structural Learning
  • PC and NPC ? same results
  • Significance level 0.05 0.03 0.01
  • Difference in real relationships and
    relationships in the data
  • Defining relations that are not in the data no
    use

18
BN Structure (2)
19
Prototype
  • User-interaction focused on a task assigned to
    the user
  • Users can experience this like a game
  • Representing the effects of changes
  • Representing the desired states of the aspects
    for different sections of the population
  • Availability of the system on Internet
  • Easy to use interface and obvious navigation

20
Changing elements
  • Three ways
  • 1) Drawing
  • 2) Picking from a list
  • 3) Cheating

21
Changing elements 1 (drawing)
22
Changing elements 2 (picking from a list)
23
Changing elements 3 (cheating)
24
Presentation of Predicted Effects
  • Three levels
  • 1) Simple ? does not give desired effect
  • 2) Normal
  • 3) Expert

25
Presentation of Predicted Effects 2 (normal)
26
Presentation of Predicted Effects 2 (normal)
27
Presentation of Predicted Effects 3 (expert)
28
Presentation of Predicted Effects 3 (expert)
29
Evaluation
  • www.WijkWizard.nl (dutch)
  • Tested and evaluated by inhabitants of the city
    of s-Hertogenbosch.
  • Online evaluation form.
  • Thanks to the Neighbourhood Wizard, I now see
    that certain ideas are positive for me, but
    negative for other members of our community
    7.4
  • The Neighbourhood Wizard shows me that changes
    can have positive effects on one aspect, but
    negative effects on other aspects 7.0
  • Confirmed the educational function of the
    prototype!

30
Conclusions ()
  • The Neighbourhood Wizard helps users to see that
    certain ideas are positive for them, but negative
    for other sections of the population
  • The Neighbourhood Wizard shows users that changes
    can have positive effects on one aspect, but
    negative effects on other aspects
  • The Neighbourhood Wizard helps users to realize
    the complexity of a design task and as a result
    users will have a better informed view on plan
    proposals and probably a higher appreciation of
    plans.

31
Conclusions (-)
  • Design of the user interface
  • Navigation structure (too many clicks)
  • Abstract terms
  • Inclusion of more concrete elements (number of
    parking lots) can help take away long-living
    irritations that inhabitants may have
  • The data collection is restricted to physical
    characteristics

32
Future work
  • Investigate the relations between characteristics
    in depth
  • (developing a technique that) Includes
    explanations of the effects
  • In some cases the predictions are not so obvious
    and require further explanation
  • For example The creation of a quiet plaza has
    negative effects on the safety of the plaza. This
    is not a logical, though correct, prediction
    because the quietness of a plaza will attract
    criminal behaviour

33
Thank you
  • Questions or coffee break?

Leon.vanBerlo_at_tno.nl / WijkWizard.nl
j.p.v.leeuwen_at_tue.nl / www.ddss.nl
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