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VIEW: Visual Interactive Effective Worlds
When To Walk Away: Questions To Ask In Infovis Projects
I will discuss several questions that I recommend asking before an
infovis project starts, and re-asking at intervals throughout the
lifetime of the project. In this talk, I will not focus on technique
questions, such whether a technique is novel or whether a chosen
visual representation actually communicates the desired structure.
Instead, these questions are concerned with process issues. What
flavor of collaborators do I have - real users, or fellow tool
builders? Is the problem solveable: Is there a real need for my new
approach/tool? Am I addressing a real task? Does real data exist and
can I have it? I will give examples of several past projects, with
outcomes along the range from successful to not so successful, where
these questions mattered. In many cases, it did not occur to me to ask
these questions when starting the projects, even if they seem obvious
Visualization of Diffusion Image Data and its Models
3D Visualization of Vasculature
Virtual Reality & Presence
Ecole Polytechnique Federale
images than on the quality of the relation between the user and digital contents. An
estimator of the quality of such relation is the level of presence which could be seen as a
evaluation of the feeling to be in a virtual worlds. This presentation aims to explain the
links between presence and virtual worlds and discuss some strategies, methods and
techniques reinforcing the personal involvement of the users. Several research
examples will presented as support for the discussion.
Some Aspects of Optimal Sampling
In this talk I will briefly derive the main idea behind optimal sampling distributions. This
leads to the body-centered cubic (BCC) lattice in 3D. I will then summarize our research
on the BCC lattice and highlight its advantages. We found it to have better numerical
accuracy, as well as better perceptual accuracy. Further, it performs twice as fast as the
ubiquitous cartesian lattice for comparable ray-casting implementations.
I will conclude my talk with some startling observations about optimal sampling in high-
Experimental Research in Visualization?! Creating a Common Research Focus
There is a growing awareness that research in visualization could profit
from more experimental (also called empirical) research. This talk
addresses three related issues:
1. Why should researchers in visualization bother about experimental
research in the first place? It is argued that experimental research is
not a goal in itself but follows naturally from a wish for a more common
research focus, in which there is an agreement on important tasks and
ways of measuring performance in these tasks.
2. What are the main pitfalls when doing experimental research?
Especially the threats posed to reaching valid conclusions (also known
as the validity of a test) are discussed in more details.
3. Does one really need statistics and what is the (lack of) meaning of
a statistically significant effect? It is explained how statistical
modeling and visualization can support a more intuitive interpretation
of experimentally obtained measurements.