Tiago Gonçalves

Evaluation of HaloDot: visualization of relevance of off-screen objects with over cluttering prevention on mobile devices

The complexity of presenting and exploring large amounts of graphical data, on mobile devices, increases due to their small screen size. To mitigate this problem several approaches have been proposed to give clues about objects that are located off-screen. In this paper we present a user study comparing the Halo off-screen visualization technique with HaloDot, our approach that aims to improve direction awareness, as well as, relevance of offscreen objects, and to avoid cluttering of Halos. The study shows that searching and pointing relevant Points of Interest (PoI) can be achieved faster than with Halo and that the proposed aggregation method is useful.

Cartographic visualization of human trajectory data: overview and analysis

With the prevalence of mobile computing systems and location based services, large amounts of spatio-temporal data are nowadays being collected, representing the mobility of people performing various activities. However, despite the increasing interest in the exploration of these data, there are still open challenges in various application contexts, e.g. related to visualisation and human–computer interaction. In order to support the extraction of useful and relevant information from the spatio-temporal and the thematic properties associated with human trajectories, it is crucial to develop and study adequate interactive visualisation techniques. In addition to the properties of the visualisations themselves, it is important to take into consideration the types of information present within the data and, more importantly, the types of tasks that a user might need to consider in order to achieve a given goal. The understanding of these factors may, in turn, simplify the development and the assessment of a given interactive visualisation. In this paper, we present and analyse the most relevant concepts associated to these topics. In particular, our analysis addresses the main properties associated with (human) trajectory data, the main types of visualisation tasks/objectives that the users may require in order to analyse that data and the high-level classes of techniques for visualising trajectory data. In addition, this paper also presents an overview on a user study, conducted in function of this analysis, to compare two classes of visualisation techniques, namely static maps and space-time cubes, regarding their adequacy in helping users completing basic visualisation tasks.

Solvency II – A BPM Application

Solvency II brings challenging requirements for insurance companies concerning the amount and periodicity of the reported information. Hence, it is difficult for an insurer to comply with such requirements without mapping and organizing the flow of information regarding the process of Solvency II.

Animated maps for analysis of personal performance in games

In recent years, the e-sports (electronic sports) phenomenon has been a growing trend and, with it, the interest in online videogames by players and spectators has also risen. One of the most popular genre of games is the MOBA (Multiplayer Online Battle Arena). Similarly to traditional sports, during a match there are several types of events that are of interest to players, coaches and analysts. These events can range from the position of a player at a particular moment, to game specific events, such as the position where a player died or the number of bullets fired in a certain zone. With the advancements in technology, it has become increasingly simpler to utilize telemetry techniques to collect data regarding the events that take place during a match. To analyze these data effectively and efficiently, it is necessary to explore which visualization techniques are better suited to the available data and the requirements of users. Regarding spatio-temporal data, the literature shows that although there are multiple visualization techniques available, the video game industry does not take full advantage of their potential. This article presents a prototype that explores several visualization techniques, namely animated maps, with the purpose of understanding their adequacy to display this type of information, while at the same time creating a tool for player performance analysis that satisfies the needs and expectations of users.

Trajectory data visualization on mobile devices with animated maps

With the increasing popularity of mobile devices (like smartphones and tablets) and georeferenced applications, more people record and analyse their own movement data. This pattern is noticeable with the increasing usage of mobile applications that, in addition to record the evolution of a persons location over time, also allow the visualization of that information, typically, in the form of 2D static maps, complemented with various representations to extract knowledge from the data. Despite the various studies addressing spatio-temporal data visualization, its application on mobile devices for the representation of personal trajectory data is still somewhat unexplored. Animated maps have been proposed as a potential intuitive and appealing technique for the visualization of information in a dynamic way, particularly for the detection of spatio-temporal data relations. We aim to address these issues by presenting a comparative study between static and animated representations of human movement on a mobile device context. Our results suggest that although it may not significantly improve user understanding of the data, the use of animated maps is a preferred and less interactively demanding option over static maps.

Improving Spatial Awareness for Human Trajectory Visualization in Space-Time Cubes

With the increasing evolution of computer graphics, 3D visualizations have become more common and are nowadays seen as a promising way to represent complex types of information. In particular, space-time cubes (STC) have been proposed as an alternative to 2D maps for the visualization of spatio-temporal data, and they have become increasingly used to explore the dynamics and patterns of human movement. However, previous research has pointed out perceptual limitations that can condition the use of 3D views for decoding locations and spatial properties. We aim to address those issues by presenting a comparative study between three variants of the STC technique, with different methods to improve spatial awareness. Our results support that the use of a movable plane or an additional 2D map view improve users’ accuracy when performing common tasks, and are preferred over simpler, yet less cluttered approaches. Additionally, it also supports the possible advantages of combining 2D and 3D views for human trajectory visualization.

Combining and assessing 2D maps and space-time cubes for trajectory data

Two dimensional static maps and three dimensional space-time cubes are among the most studied techniques to visualize human movement data. Previous research suggests that both techniques are useful in different types of tasks. However, the analysis of trajectory data may not be focused in just one type of task, motivating further studies to quantify the advantages of combining both types of techniques. This paper describes our work-in-progress addressing this issue, proposing the combination of 2D maps and 3D space-time cubes for human trajectory visualization, and overviewing possible metrics for its evaluation.