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.

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The visualization of geo-referenced information on a map has become an essential method to help the users to get the intended information. The adaptation of visualization techniques for mobile devices, such as, PDA and mobile phones make this type of applications ubiquitous. However, the context of mobility and the limitations of mobile devices, such as, the small screen, suggest that some visualization techniques may not be appropriate for those devices. In this work we intend to integrate filtering mechanisms, based on semantic criteria, and to use multiple representations with different levels of detail to generate intelligible representations as a result of geographic queries in mobile environments.

Applications that allow the users to search for nearby points of interest have, recently, become very popular amongst mobile device users. However, the increasing amount of available information and the limitations of current mobile devices can hinder an efficient and helpful user experience. It is fundamental that what is shown to the user is relevant. We propose an adaptive recommendation function that uses location and temporal contexts combined with the historical context of the previous searches to quantify the relevance of the points of interest shown to the user.

Education covers a range of sectors from kindergarten to higher education. In the education system, each grade has three possible outcomes: dropout, retention and pass to the next grade. In this work, we study the data from the Department of Statistics of Education and Science (DGEEC) of the Education Ministry. DGEEC maintains those outcomes for each school year, therefore, this study seeks a longitudinal view based on student flow. The document reports the data pre-processing, a stochastic model based on the pre-processed data and a data generation process that uses the previous model.

The evolution of mobile devices and the development of high speed wireless networks have supported a widespread use of these devices with increasingly more complex applications. This reality has fostered the research in the field of information visualization in mobile devices. However, the limited screen space, resource constraints and interaction restrictions impose difficulties to developers and users of these applications. An approach to address these problems is to adapt the visualization to the user context. However, these proposals are normally designed in an ad-hoc fashion and are difficult to generalize. In addition, existing solutions are focused only in some subset of possible characteristics of the user context or only address a very specific domain and related adaptations. The objective of this paper is to present the design of a framework for adaptive mobile visualization (AMV) applications, denominated Chameleon, and the development and evaluation of prototypes that use this conceptual-based framework.