Interactive Visual Exploration and Analysis - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 161

±

with y -values beyond 2 are also considered as outliers (and brushed accordingly).

This brushing leads to their identification in the views Fig. 15.4 e, f, where each
ocean section is repeated 100 times (once for every computed simulation run). This
analysis resulted in an interesting deep-water pattern of some “outliers” in the north
of the simulation, translating from the Atlantic slice into the Arctic basin (which
actually look much more like a distinct pattern than just outliers) as well as some
surface-water outliers (warm water, half-way north in the Pacific, marked orange)
and some other outliers near Antarctica (circled red). More details about this study
have been presented by Kehrer et al. [ 16 ].

15.6 Conclusions and Future Directions

IVA has already proven valuable in a wide range of application areas, including engi-
neering, climate research, biomedical research and economy. The ability to define
features interactively and refine feature definitions based on insights gained during
visual and exploration and analysis provides an extremely powerful and versatile
tool for knowledge discovery. Future challenges lie in the integration of alternate
feature detection methods and their utilization in intelligent brushes. Furthermore,
integrating IVA and simulations, thus supporting computational steering, offers a
wide range of new possibilities for knowledge discovery.

Acknowledgments This work was supported by the Director, Office of Advanced Scientific
Computing Research, Office of Science, of the U.S. Department of Energy under Contract No.
DE-AC02-05CH11231. We thank the members of the LBNL visualization group and the Berkeley
Drosophila Transcription Network. Special thanks are extended to Helmut Doleisch and colleagues
from SimVis GmbH in Vienna, Austria, for the cooperation over many years. We thank Johannes
Kehrer and Peter Filzmoser as well as Thomas Nocke, Michael Flechsig, and colleagues from the
Potsdam Institute for Climate Impact Research in Germany for the collaboration on the climate
data analysis. We also thank Krešimir Matkovic and colleagues from the VRVis Research Center
in Vienna, Austria, for many years of fruitful collaboration on IVA research, as well as many others
from Vienna, Bratislava, Magdeburg, Zürich, and Bergen.

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