Ph.D
Group :

Physical and Tangible Information Visualization

Starts on 01/12/2010
Advisor : FEKETE, Jean-Daniel

Funding :
Affiliation : Université Paris-Saclay
Laboratory : LRI INRIA Saclay

Defended on 10/03/2014, committee :

Research activities :

Abstract :
Computers immensely increased the amount of data we can collect and process as well as diversified the ways we can represent it visually. Computer-supported visualization systems, studied in the field of information visualization (infovis), have become powerful and complex, and sophisticated interaction techniques are now necessary to control them. With the widening of technological possibilities beyond classic desktop settings, new opportunities have emerged. Not only display surfaces of arbitrary shapes and sizes can be used to show richer visualizations, but also new input technologies can be used to manipulate them. For example, tangible user interfaces are an emerging input technology that capitalizes on humans' abilities to manipulate physical objects. However, these technologies have been barely studied in the field of information visualization.

In this thesis, I establish embodiment as a design principle for infovis purposes, I demonstrate and validate the efficiency and usability of both embodied visualization controls and embodied visualization displays through three controlled user experiments. I then present a conceptual interaction model and visual notation system that facilitates the description, comparison and criticism of various types of visualization systems and illustrate it through case studies of currently existing point solutions. Finally, to aid the creation of physical visualizations, I present a software tool that supports users in building their own visualizations. The tool is suitable for users new to both visualization and digital fabrication, and can help to increase users' awareness of and interest in data in their everyday live. In summary, this thesis contributes to the understanding of the value of emerging physical representations for information visualization.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.