Scientific visualization provides
graphical representations of numerical data for their qualitative and
quantitative analysis. In contrast to a fully automatic analysis (e.g.
with statistical methods), the final analytic step is left to the user, thus
utilizing the power of the human visual system. Scientific
visualization differs
from the related field of information visualization in that it focuses
on data that represent samples of continuous functions of space and time, as
opposed to
data that are inherently discrete.
The challenge in scientific visualization is
to cope with massive data, which cannot be presented to the user in an
unprocessed way for several reasons:
-
Volumetric data, i.e. data given on a three-dimensional domain, occlude each
other. This problem becomes even more severe if data are not scalars,
but vectors or even tensors.
-
Visualization should provide a global picture of the spatial and temporal behavior of
the data, but also allow for interactive exploration of details.
-
There can be multiple data (different physical quantities, multiple data
channels, etc.) at each point in the domain.
-
Visualization of scientific data should also include visualization of their
uncertainty.
-
The amount of raw data often exceeds limitations of processor speed,
transfer rates, memory size, and display resolution.
Project Members
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Past Members
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Collaborators
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- Dirk Bauer
- Mie Sato
- Christian Sigg
- Martin Roth
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- Yun Jang
- Jean Favre
- John Biddiscombe
- Raphael Fuchs
- Helwig Hauser
- Holger Theisel
- Gerik Scheuermann
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inf.ethz.ch