Section: Overall Objectives
Introduction
A recent U.S. report to the funding agencies NIH and NSF [19] provides strong arguments in favor of the development of visualization as a research field.
“Visualization is indispensable to the solution of complex problems in every sector, from traditional medical, science and engineering domains to such key areas as financial markets, national security, and public health. Advances in visualization enable researchers to analyze and understand unprecedented amounts of experimental, simulated, and observational data and through this understanding to address problems previously deemed intractable or beyond imagination.”
[from the Executive summary of [19] ].
Visualization is becoming a critical issue in a number of areas. It is more and more seen as a complementary approach - not only as a tool - for data retrieval and exploration or strategic and competitive watch, for instance, where the structure of data is typically unknown and must be discovered and understood. It is also a reliable approach when navigating “already known” and structured information space such as large ontologies. Information Visualization usefully combines with Scientific Visualization to help expert users explore and understand complex models underlying large scale simulations.
In response to this challenge, GRAVITÉ aims at designing interactive visualization methods and tools to analyze and mine large datasets. Our emphasis is on the visualization of graph structures to help users gain insights from large datasets and large-scale simulations, to understand the data and/or the underlying model, and ultimately, to identify intrinsic properties or emergent phenomenon.
More than just being able to deal with large volume and inhomogeneous data, we are required to deal with constant changes in data, possibly making it ambiguous and uncertain. In the context of graph visualization, the challenge we face is thus to design methods and tools:
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to deal with large and dynamically changing graphs;
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to visually identify salient properties in changing substructures;
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identify the multiscale nature of data;
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to produce visual cues helping the user to track such changes in either one three different situations where dynamic graphs occur.
A clear priority for our research is to address the needs of expert users faced with interpreting dynamic data. Our agenda is based on the needs expressed by our research community [62] [19] [20] . Our collaborations with experts of other scientific fields as well as with industry contribute to the overall organization of this research agenda and serve a twofold objective:
