8B_2_Using sound to represent uncertainty in address locations

Using Sound to Represent Uncertainty in Address Locations Nick Bearman and Andrew Lovett PhD School of Environmental Science University of East Anglia [email_address] ; [email_address]

Introduction
Using sound to represent uncertainty* in address locations
*positional accuracy
Created an extension to ArcGIS
Evaluated this using 49 users of spatial data (OS, UEA & LA)
Comparing Visual and Sonic methods
Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

OS MasterMap ® Address Layer 2 11B Clarendon Road Norwich NR2 2PN Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

Uncertainty can be very important
Depending on what you are doing with the data
Uncertainty in AL2
Contains 5 different status flags
Including Positional Accuracy
Which some users ignore
Why?
it's not relevant
users don't think it's relevant (when it is)
users can't access the information within the data
users can't display the information
the information isn't available
Why AL2 & Uncertainty? Merrifield Cottage TR16 5DA Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

Vision can be saturated
Alternatives to Vision
Vision can be used more effectively – but there are limits
Sound is the next most powerful sense
Little Previous Research
These were pilot studies, custom coded. Need to move these to a generic, easily usable environment
No user testing & no existing research frameworks
Piano Notes
Easy to understand – good order
CEG Triad, preferred option
Possibly could have chosen anything though
Why Sound? http://kbark.wordpress.com/2006/12/17/where-am-i/ (18/03/2009) Finnish Town http:// www.politics.co.uk /news/policing-and-crime/ new-police-crime-maps-confusing--$1272816.htm (18/03/2009) London Crime Fisher (1994) Fisher (1994) Uncertainty and Soil Type MacVeigh & Jacobson (2007) MacVeigh & Jacobson (2007) Harbour, Sea and Land Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

AL2 Positional Accuracy
Prototype the extension
Pilot studies & improvement
Reduce 5 categories (sounds) to 3
Methods Value Description Surveyed Within the building that the address refers to. Approximate Usually within 50m. Postcode Unit Mean Mean position calculated from correctly located points within the postcode unit (e.g. NR4 6AA is a postcode unit). Estimate Usually within 100m. Postcode Sector Mean Mean position calculated from correctly located points within the postcode sector (e.g. NR4 6__ is a postcode sector). Value Surveyed Approximate Postcode Unit Mean Estimate Postcode Sector Mean Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

Evaluation
Computer Based Questionnaire
Presentation Methods
Participants asked to choose proportion of values that had AL2 PQA Value of Surveyed (25%, 50%, 75%)
Demo
Discussion Session
Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps None AL2 Positional Accuracy Visual only AL2 Positional Accuracy Council Tax bands Visual and Sonic representing different variables AL2 Positional Accuracy AL2 Positional Accuracy Visual and Sonic representing the same variable AL2 Positional Accuracy Topography outlines only Sonic only Sonic Data Visual Data Presentation Method

Two main factors
Proportion of data (p < 0.005)
Logical, but no evidence of this in GI literature
Presentation method (p < 0.05)
As expected
Logistic Regression
Also Knowledge of the Data appeared to have an impact – but when this was added into the logistic regression, it wasn’t significant.
Discussion Sessions
Greater differences between sounds
Colour blind users
Results Factors added to Model -2 Log Likelihood Cox & Snell R 2 Proportion 182.01 0.043 Presentation Method 169.579 0.105 Knowledge of the Data 167.319 0.116 Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps 0.88 75% 0.62 0.74 Mean Score Proportion 25% 50% 0.82 Visual 0.65 0.67 0.86 Mean Score Presentation Method Visual Sonic Same Sonic Visual Sonic Different

Next Steps
Summary
Sound can work
Proportion of Data and Presentation Method
Knowledge of Data
Improvements
Task
Next data
UKCP09
VR Visualisations of Future Landscapes
Introduction Why AL2 & Uncertainty? Why Sound? Methods Results Next Steps

8B_2_Using sound to represent uncertainty in address locations

by GISRUK conference on Apr 22, 2010

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