Discovery exhibition: using spatial treemaps in local authority decision making and reporting

At Leicestershire County Council we are using spatial treemaps to analyse labour markets and commuting behaviour. This novel visualization technique, presented at InfoVis 2008, has resulted in a number of insights and discoveries. Transport planners in our organization indicate that the graphics are effective and have advantages over alternatives. As researchers in the local authority we report upon using these graphics to inform decision makers and residents in the county’s evidence base for sustainable transport planning

Monitoring the Health of Computer Networks with Visualization - VAST 2012 Mini Challenge 1 Award: "Efficient Use of Visualization"

The complex computer networks of large organisations contain many machines of many types, used in many geographic locations. Although system administrators should monitor the health of each machine, they need to do so within the context of the whole computer network. Our visualization presents the health of a fictitious financial institution's computer network at a snapshot in time and over a time range, and preserves the important aspects of each facility's administrative and geographic context. Using the "Bank of Money" VAST Challenge dataset, our visualization allowed us to correctly identify several areas of concern, as well as hypothesise about their causes

Characterising labour market self-containment in London with geographically arranged small multiples

We present a collection of small multiple graphics that support analysis and understanding of the geography of labour-market self-containment across London’s 33 boroughs. Ratios describing supply-side self-containment, the extent to which working residents access jobs locally, and demand-side self-containment, the extent to which local jobs are filled by local resident workers, are first calculated for professional and non-professional occupations and encoded directly through geographically-arranged bar charts. The full distribution of workers into-and out-of- boroughs that underpins these ratios is then revealed via Origin-Destination flows maps (OD maps) – sets of geographically-arranged choropleths. In order to make relative and absolute comparison of borough-to-borough frequencies between occupation types, these OD maps are coloured according to signed chi-square residuals: for every borough-to-borough pair, we compare the observed number of flows to access professional versus non-professional jobs against the number that would be expected given the distribution of those jobs across London boroughs. Our geographically-arranged small multiples demonstrate potential for spatial analysis: a rich, multivariate structure is depicted that reflects London’s economic geography and that would be difficult to expose using non-visual means

Locally-varying explanations behind the United Kingdom’s vote to the Leave the European Union

Explanations behind area-based (Local Authority-level) voting preference in the 2016 referendum on membership of the European Union are explored using aggregate-level data. Developing local models, special attention is paid to whether variables explain the vote equally well across the country. Variables describing the post-industrial and economic ‘successfulness’ of Local Authorities most strongly discriminate variation in the vote. To a lesser extent this is the case for variables linked to ‘metropolitan’ and ‘big city’ contexts, which assist the Remain vote, those that distinguish more traditional and ‘nativist’ val- ues, assisting Leave, and those loosely describing material outcomes, again reinforcing Leave. Whilst variables describing economic competitiveness co-vary with voting pref- erence equally well across the country, the importance of secondary variables – those dis- tinguishing metropolitan settings, values and outcomes – does vary by region. For certain variables and in certain areas, the direction of effect on voting preference reverses. For ex- ample, whilst levels of European Union migration mostly assist the Remain vote, in parts of the country the opposite effect is observed

Stormwater sand filters in water-sensitive urban design

This paper investigates the suitability of sand filters for harvesting and treating stormwater for non-potable reuse purposes. A stormwater sand filtration device was constructed in a small urban catchment in Sydney, Australia. A sand filter is typically used in water-sensitive urban design (WSUD) as a component of a treatment train to remove pollution from stormwater before discharge to receiving waters, to groundwater or for collection and reuse. This paper describes an 18 month field study undertaken to determine the effectiveness and pollutant removal efficiency of a sand filter, and the differences in the pollutant removal efficiency of two grades of sand. A comparison of pollutant removal with previous literature on sand filters showed similar efficiencies but nutrient removal was higher than expected. A further unexpected result was that the coarse filter media performed as well as the fine media for most pollutant types and was superior in suspended solids removal. Improved modelling equations for predicting suspended solids and total phosphorus removal in sand filters are also presented in this paper

Regionally-structured explanations behind area-level populism: An update to recent ecological analyses

Heavy geographic patterning to the 2016 Brexit vote in UK and Trump vote in US has resulted in numerous ecological analyses of variations in area-level voting behaviours. We extend this work by employing modelling approaches that permit regionally-specific associations between outcome and explanatory variables. We do so by generating a large number of regional models using penalised regression for variable selection and coefficient evaluation. The results reinforce those already published in that we find associations in support of a ‘left-behind’ reading. Multivariate models are dominated by a single variable—levels of degree-education. Net of this effect, ‘secondary’ variables help explain the vote, but do so differently for different regions. For Brexit, variables relating to material disadvantage, and to a lesser extent structural-economic circumstances, are more important for regions with a strong industrial history than for regions that do not share such a history. For Trump, increased material disadvantage reduces the vote both in global models and models built mostly for Southern states, thereby undermining the ‘left-behind’ reading. The reverse is nevertheless true for many other states, particularly those in New England and the Mid-Atlantic, where comparatively high levels of disadvantage assist the Trump vote and where model outputs are more consistent with the UK, especially so for regions with closer economic histories. This pattern of associations is exposed via our regional modelling approach, application of penalised regression and use of carefully designed visualization to reason over 100+ model outputs located within their spatial context. Our analysis, documented in an accompanying github repository, is in response to recent calls in empirical Social and Political Science for fuller exploration of subnational contexts that are often controlled out of analyses, for use of modelling techniques more robust to replication and for greater transparency in research design and methodology

Supporting crime analysis through visual design

We describe and discuss a visual analysis prototype to support volume crime analysis, a form of exploratory data analysis that aims to identify and describe patterns of criminality using historical and recent crime reports. Analysis requirements are relatively familiar: analysts wish to identify, define and compare sets of crime reports across multiple attributes (space, time and description). A challenge particular to the domain, identified through workshops with Police analysts in Belgium and the UK, is in developing exploratory data analysis software that offers some sophistication in data selection, aggregation and comparison, but with interaction techniques and representations that can be easily understood, navigated and communicated. In light of ongoing discussion with Police analysts, we propose four visual design and interaction maxims that relate to this challenge and discuss an early visual analysis prototype that we hope conforms to these maxims