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

Dynamic Design Documents for supporting applied visualization

A common characteristic of applied visualization is collaboration between visualization researcher and domain expert – where the vi- sualization researcher attempts to assimilate sufficient detail around data, task and requirements to design a visualization tool that is manifestly useful. We report on a method for enabling such a col- laboration that can be used throughout the design process to gather and develop requirements and continually evaluate and support iter- ative design. We do so using highly interactive web-pages that we term dynamic design documents. Applied during a four-year visual data analysis project for crime research, these documents enabled a series of data mappings to be explored by our collaborators (crime analysts) remotely – in a flexible and continuous way. We argue that they engendered a level of engagement that is qualitatively dis- tinct from more traditional methods of feedback elicitation, offered a solution to limited and intermittent contact between analyst and visualization researcher and speculate that they provided a means of partially addressing certain intractable deficiencies, such as so- cial desirability-bias, that are common to evaluation in applied data visualization

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

Design Exposition Discussion Documents for Rich Design Discourse in Applied Visualization

We present and report on Design Exposition Discussion Documents (DExDs), a new means of fostering collaboration between visualization designers and domain experts in applied visualization research. DExDs are a collection of semi-interactive web-based documents used to promote design discourse: to communicate new visualization designs, and their underlying rationale, and to elicit feedback and new design ideas. Developed and applied during a four-year visual data analysis project in criminal intelligence, these documents enabled a series of visualization re-designs to be explored by crime analysts remotely – in a flexible and authentic way. The DExDs were found to engender a level of engagement that is qualitatively distinct from more traditional methods of feedback elicitation, supporting the kind of informed, iterative and design-led feedback that is core to applied visualization research. They also offered a solution to limited and intermittent contact between analyst and visualization researcher and began to address more intractable deficiencies, such as social desirability-bias, common to applied visualization projects. Crucially, DExDs conferred to domain experts greater agency over the design process – collaborators proposed design suggestions, justified with design knowledge, that directly influenced the re-redesigns. We provide context that allows the contributions to be transferred to a range of settings

Multi-Perspective Synopsis with Faceted Views of Varying Emphasis

Many datasets have multiple perspectives – e.g. time, space and description – and often summaries are required for these multiple perspectives concurrently. A design challenge is to provide such a concurrent summary of perspectives in ways that neither clutter nor visually overload. We report on a framework that helps us do this. We demonstrate its use with an implementation based on a Crime Pattern Analysis case study that produces synoptic summarises of spatial, temporal and descriptive information in crime reports. Our work with crime analysts suggests that the framework offers some potential for Crime Pattern Analysis

Age-related Effects on Social Cognition in Adults with Autism Spectrum Disorder: A Possible Protective Effect on Theory of Mind

Impaired social cognition has been suggested to underlie the social communication difficulties that define autism spectrum disorder (ASD). In typical development, social cognition may deteriorate in older age, but age effects in ASD adults have been little explored. In the present study, we compared groups of younger and older adults with and without ASD (n = 97), who completed a set of social cognition tasks assessing theory of mind (ToM), and self‐report measures of empathy and alexithymia. While typically developing (TD) younger adults outperformed elderly TD and younger ASD participants, younger and older ASD adults did not differ in their ToM performance, and the elderly ASD and TD groups performed equivalently. By contrast, ASD adults reported lower empathy scores and higher levels of alexithymia symptoms compared to TD adults regardless of age. The difference between ASD and TD groups in self‐reported empathy scores was no longer significant when alexithymia was covaried (with the exception of the Perspective Taking subscore). Results suggest a possible age‐protective effect on ToM in the ASD group. In addition, empathy difficulties appear to be associated with alexithymia rather than ASD per se. Possible interpretations are discussed, and future directions for autism aging research are proposed

Map LineUps: effects of spatial structure on graphical inference

Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.’s ‘Visual Line-up’ method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n = 361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran’s I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people’s abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference

Meeting local information needs with ASCS and PSS SACE data

Blog summarising the key findings from the case study of further analysis, conducted with three local authorities during the fact-finding phase of the MAX project, which identified three local practices that maximised the local relevance and value of survey data: adding questions to the surveys, conducting further analysis and drawing on supplementary sources of data

Further analysis of ASCS and PSS SACE data: Case studies of local authority (LA) practice

The Maximising the value of survey data in adult social care (MAX) project aims to develop toolkits, with local authority (LA) staff where possible, to encourage and support LAs to make more use of data drawn from the ASCS and PSS SACE1 to inform local policy and practice. The initial fact-finding phase (MAX Phase 1) activities aimed to:learn more about how LAs currently use ASCS and PSS SACE data, including identifying local practices and barriers; identify potential uses of the data to inform local decision-making; and inform the development of a toolkit to support LAs to make better local use of the data. Along with two analysis and interpretation consultation panel workshops conducted early in the second phase of the project, 139 staff from 95 LAs have so far taken part in MAX. In summary, the findings from these activities demonstrate that LAs generally seem to value the ASCS and PSS SACE and, to some extent, are using the views of service users and carers to inform local service planning and delivery. However, there were several challenges. One of these, identified by just over half of the LAs, concerned analysing the survey data and interpreting the findings to address local questions. A number of barriers seem to underlie this challenge, including difficulties with: identifying local information needs; managing and analysing ASCS and PSS SACE data; and being allocated sufficient time to conduct further analysis. While some LAs find analysing ASCS and PSS SACE data challenging, others are carrying out local statistical analysis, over and above those required for national (ASCOF) reporting. The case studies reported here describe how three local authorities have used and analysed the ASCS and PSS SACE data to support local decision-making. In turn, the case studies will be used to inform the development of ‘how to’ guides and tools to help LAs analyse and interpret survey data, as well as report and interpret analysis finding