There are some "Grand Challenges" of data visualization which scientists in every application domain confront
at one time or another. For example, how to access large volumes of data, how to isolate the "important"
pieces of information, how to map scientific data to primitives suitable for graphical algorithms, how to
achieve the speed of useful interaction, why won't off-the-shelf software do what I need it to do, how to
make hardcopy, etc., are just some of the common problems. This panel session addresses issues like these,
from the point of view of the scientist who uses visualization as a research tool. Each panelist was invited to
submit a short "position paper", which is reproduced here.