1. Using Sound to Represent Positional Accuracy of Address Locations Nick Bearman and Andrew Lovett PhD School of Environmental Science University of East Anglia n.bearman@uea.ac.uk; a.lovett@uea.ac.uk Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

2. Positional Accuracy of Address Locations Geo-coding is ‘address’ → ‘location’ Two main uses Spatial analysis & Routing Why is it important? Address Layer 2 is used for geo-coding not all addresses have correct locations assuming all entries are correct can impact the analysis or routing Merrifield Cottage TR16 5DA Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

3. OS MasterMap ® Address Layer 2 11B Clarendon Road Norwich NR2 2PN Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps ValueDescription SurveyedWithin the building that the address refers to. ApproximateUsually within 50m. Postcode Unit MeanMean position calculated from correctly located points within the postcode unit (e.g. NR4 6AA is a postcode unit). EstimateUsually within 100m. Postcode Sector MeanMean position calculated from correctly located points within the postcode sector (e.g. NR4 6__ is a postcode sector). 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

4. Vision can be saturated Alternatives to Vision Vision can be used more effectively – but there are limits Sound is the next most powerful sense (haptic/touch) Little Previous Research These were pilot studies, custom coded. Need to move these to a generic, easily usable environment (GIS) No user testing & no existing research frameworks Piano Notes Easy to understand – clear order (implicit assumption?) CEG Triad, preferred option Possibly could have chosen any sound 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 of Classification MacVeigh & Jacobson (2007) MacVeigh & Jacobson (2007) Harbour, Sea and Land Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

5. Value Surveyed Approximate Postcode Unit Mean Estimate Postcode Sector Mean Methods Created extension to ArcGIS Written in Visual Basic Prototype – tested and improved Users asked to choose proportion 25%, 50% or 75% (stratified random method) Four methods Demo Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

6. Proportion – (p < 0.005) – Logical, but no evidence of this in GI literature Presentation Method – (p < 0.05) – As expected Results ProportionMean Score 75%0.88 25%0.74 50%0.62 Presentation MethodMean Score Visual Sonic Same0.86 Visual0.82 Sonic0.67 Visual Sonic Different0.65 + - + - + - + Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

7. 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 LikelihoodCox & Snell R 2 Proportion182.010.043 Presentation Method169.5790.105 Knowledge of the Data167.3190.116 Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps

8. Summary Sound can work Significant Factors Proportion of Data and Presentation Method Knowledge of Data Improvements Task & Sounds Next case study UKCP09 web interface more focus on prior knowledge of data set VR Visualisations of Future Landscapes Introduction Positional Accuracy & AL2 Why Sound?MethodsResults Next Steps