Sketchy rendering for information visualization

We present and evaluate a framework for constructing sketchy style information visualizations that mimic data graphics drawn by hand. We provide an alternative renderer for the Processing graphics environment that redefines core drawing primitives including line, polygon and ellipse rendering. These primitives allow higher-level graphical features such as bar charts, line charts, treemaps and node-link diagrams to be drawn in a sketchy style with a specified degree of sketchiness. The framework is designed to be easily integrated into existing visualization implementations with minimal programming modification or design effort. We show examples of use for statistical graphics, conveying spatial imprecision and for enhancing aesthetic and narrative qualities of visual- ization. We evaluate user perception of sketchiness of areal features through a series of stimulus-response tests in order to assess users’ ability to place sketchiness on a ratio scale, and to estimate area. Results suggest relative area judgment is compromised by sketchy rendering and that its influence is dependent on the shape being rendered. They show that degree of sketchiness may be judged on an ordinal scale but that its judgement varies strongly between individuals. We evaluate higher-level impacts of sketchiness through user testing of scenarios that encourage user engagement with data visualization and willingness to critique visualization de- sign. Results suggest that where a visualization is clearly sketchy, engagement may be increased and that attitudes to participating in visualization annotation are more positive. The results of our work have implications for effective information visualization design that go beyond the traditional role of sketching as a tool for prototyping or its use for an indication of general uncertainty

How do texture and color communicate uncertainty in climate change map displays?

We report on an empirical study with over hundred online participants where we investigatedhow texture and color value, two popular visual variables used to convey uncertainty in maps,are understood by non-domain-experts. Participants intuit denser dot textures to mean greaterattribute certainty; irrespective of whether the dot pattern is labeled certain or uncertain. Withthis additional empirical evidence, we hope to further improve our understanding of how non-domain experts interpret uncertainty information depicted in map displays. This in turn willallow us to more clearly and legibly communicate uncertainty information in climate changemaps, so that these displays can be unmistakably understood by decision-makers and the generalpublic

Human-Centered Approaches in Geovisualization Design: Investigating Multiple Methods Through a Long-Term Case Study

Working with three domain specialists we investigate human-centered approaches to geovisualization following an ISO13407 taxonomy covering context of use, requirements and early stages of design. Our case study, undertaken over three years, draws attention to repeating trends: that generic approaches fail to elicit adequate requirements for geovis application design; that the use of real data is key to understanding needs and possibilities; that trust and knowledge must be built and developed with collaborators. These processes take time but modified human-centred approaches can be effective. A scenario developed through contextual inquiry but supplemented with domain data and graphics is useful to geovis designers. Wireframe, paper and digital prototypes enable successful communication between specialist and geovis domains when incorporating real and interesting data, prompting exploratory behaviour and eliciting previously unconsidered requirements. Paper prototypes are particularly successful at eliciting suggestions, especially for novel visualization. Enabling specialists to explore their data freely with a digital prototype is as effective as using a structured task protocol and is easier to administer. Autoethnography has potential for framing the design process. We conclude that a common understanding of context of use, domain data and visualization possibilities are essential to successful geovis design and develop as this progresses. HC approaches can make a significant contribution here. However, modified approaches, applied with flexibility, are most promising. We advise early, collaborative engagement with data – through simple, transient visual artefacts supported by data sketches and existing designs – before moving to successively more sophisticated data wireframes and data prototypes

Vers plus d'expressivité dans les représentations graphiques du territoire

International audienceThis paper addresses the issue of expressivity conveyed by the graphical representations of territory. In order to improve the relevancy between graphical representations and effective uses of those representations, expressivity should be enhanced in map and geovisualisation design. Based on knowledge and methods coming from expressive rendering, a sub-domain of computer graphics, we proposed specific rendering techniques for map and geovisualisation design, from the specification of styles. Two stylisation projects, in map design (MapStyle) and in 3D geovisualisation design (Plu++), provide a high diversity of graphical representations of the territory, aiming at making them relevant for many uses. Exploring the space of possible graphical representations is also a way to approach the issue of perception and cognition of complex phenomena on the territory.Cet article questionne la notion d'expressivité dans les représentations graphiques du territoire. Afin d'améliorer l'adéquation entre représentations graphiques du territoire et usages de ces représentations pour mieux comprendre le territoire, une approche consiste à rendre les représentations plus expressives. S'inspirer des techniques de rendu expressif, un domaine de l'informatique graphique, a permis de proposer des techniques de rendu spécifiques pour la cartographie et la géovisualisation, à partir de la spécification de styles. Deux projets de stylisation en cartographie (MapStyle) et en géovisualisation 3D (Plu++) ont permis de construire différentes représentations graphiques visant à répondre à des usages variés des représentations graphiques du territoire. Pouvoir explorer l'espace des possibles dans les représentations graphiques est ainsi une façon d'approcher le problème de la perception et de la compréhension de phénomènes complexes sur le territoire

Supporting Web-based and Crowdsourced Evaluations of Data Visualizations

User studies play a vital role in data visualization research because they help measure the strengths and weaknesses of different visualization techniques quantitatively. In addition, they provide insight into what makes one technique more effective than another; and they are used to validate research contributions in the field of information visualization. For example, a new algorithm, visual encoding, or interaction technique is not considered a contribution unless it has been validated to be better than the state of the art and its competing alternatives or has been validated to be useful to intended users. However, conducting user studies is challenging, time consuming, and expensive. User studies generally requires careful experimental designs, iterative refinement, recruitment of study participants, careful management of participants during the run of the studies, accurately collecting user responses, and expertise in statistical analysis of study results. There are several variables that are taken into consideration which can impact user study outcome if not carefully managed. Hence the process of conducting user studies successfully can take several weeks to months. In this dissertation, we investigated how to design an online framework that can reduce the overhead involved in conducting controlled user studies involving web-based visualizations. Our main goal in this research was to lower the overhead of evaluating data visualizations quantitatively through user studies. To this end, we leveraged current research opportunities to provide a framework design that reduces the overhead involved in designing and running controlled user studies of data visualizations. Specifically, we explored the design and implementation of an open-source framework and an online service (VisUnit) that allows visualization designers to easily configure user studies for their web-based data visualizations, deploy user studies online, collect user responses, and analyze incoming results automatically. This allows evaluations to be done more easily, cheaply, and frequently to rapidly test hypotheses about visualization designs. We evaluated the effectiveness of our framework (VisUnit) by showing that it can be used to replicate 84% of 101 controlled user studies published in IEEE Information Visualization conferences between 1995 and 2015. We evaluated the efficiency of VisUnit by showing that graduate students can use it to design sample user studies in less than an hour. Our contributions are two-fold: first, we contribute a flexible design and implementation that facilitates the creation of a wide range of user studies with limited effort; second, we provide an evaluation of our design that shows that it can be used to replicate a wide range of user studies, can be used to reduce the time evaluators spend on user studies, and can be used to support new research

Probabilistic Interval Forecasts: An Individual Differences Approach to Understanding Forecast Communication

Predictive interval forecasts, showing a range of values with specified probability, have the potential to improve decisions compared to point estimates. The research reported here demonstrates that this advantage extends from college undergraduates to a wide user group and does not depend on education. In two experiments, participants made decisions based on predictive intervals or point estimates and answered questions about them. In Experiment 1, they also completed numeracy and working memory span tests. Those using predictive intervals were better able to identify situations requiring precautionary action. Nonetheless, two errors were noted: (1) misinterpreting predictive intervals as diurnal fluctuation (deterministic construal errors) and (2) judging the probability of events within and beyond the interval, when asked about them separately, as greater than 100%. These errors were only partially explained by WMS and numeracy. Importantly, omitting visualizations eliminated deterministic construal errors and overestimation of percent chance was not consistently related to decision quality. Thus, there may be important benefits to predictive interval forecasts that are not dependent on a full understanding of the theoretical principles underlying them or an advanced education, making them appropriate for a broad range of users with diverse backgrounds, weather concerns, and risk tolerances