Upload
carol-eaton
View
216
Download
0
Tags:
Embed Size (px)
Citation preview
Léon van Berlo / Jos van Leeuwen
The Neighbourhood Wizard
Cause and effect of changes in urban neighbourhoods
05 July 2006 2
Agenda
• Introduction• Objective• Approach• (Experiencing) Liveability• Data Collection• Knowledge representation• Prototype• Evaluation and testing• Conclusions and future work• Coffee break
05 July 2006 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 don’t see the complex dependencies of a decision• Inhabitants give concrete proposals for change in stead of
their desire
05 July 2006 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
05 July 2006 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
05 July 2006 6
Experiencing liveability:Leidelmeijer and Marsman 1999
Environment characteristic 1
Environment characteristic ..
Environment characteristic n
Appreciation 1
Appreciation n
Importance ..
Appreciation ..
Importance 1
Importance n
Satisfaction 1
Satisfaction ..
Satisfaction n
Experienced liveability
x
x
x
x
x
x
+
+
Infulenced by the habitat
OBJECTIVE SUBJECTIVE
05 July 2006 7
Example experience by an individual
Composition:simple
Status:popular
Security:safe
neutral
positive
none
negative
low+/-
++
++
xx
xx
xx
+
+
+
high
AppreciationImportance
Satisfaction LiveabilityCharacteristics
05 July 2006 8
Example experience by an individual
Composition:simple
Status:popular
Security:safe
neutral
positive
none
negative
low+/-
++
Exp.liveability
+
+
+
high
Charcteristic ..importance
appreciation+
Charcteristic ..importance
appreciation
--
Charcteristic ..importance
appreciation+
Charcteristic ..importance
appreciation+
05 July 2006 9
Example experience by an individual
ASPECT
ELEMENT
ASPECT
neutral
positive
low+/-
++
Exp.liveability
+
+
high
ELEMENT
ASPECTimportance
appreciation
-- +
ELEMENT
ELEMENT
05 July 2006 10
Experience by another individual
ASPECT
ELEMENT
ASPECT
neutral
positive
low+/-
+
Exp.liveability
+
+
normal
ELEMENT
ASPECTimportance
appreciation
-- +
ELEMENT
ELEMENT
05 July 2006 11
Grouping individuals and their needs
Wishprofiles:• Teenagers• Yuppies• Families• Elderly• Handicapped (elderly)
Aspects:• Space• Liveliness• Security• Quality• Status• Traffic
05 July 2006 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.
05 July 2006 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.
05 July 2006 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
05 July 2006 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
05 July 2006 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
05 July 2006 24
Presentation of Predicted Effects
• Three levels:• 1) Simple does not give desired effect• 2) Normal• 3) Expert
05 July 2006 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!
05 July 2006 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.
05 July 2006 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
05 July 2006 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
05 July 2006 33
Thank you
• Questions or coffee break?
[email protected] / WijkWizard.nl [email protected] / www.ddss.nl