Abstract
In scientific visualization the key task of research is the provision of insight into a problem. Finding the solution to a problem may be seen as finding a path through some rugged terrain which contains mountains, chasms, swamps, and few flatlands. This path—an algorithm discovered by the researcher—helps users to easily move around this unknown area. If this way is a wide road paved with stones it will be used for a long time by many travelers. However, a narrow footpath leading through deep forests and deadly swamps will attract only a few adventure seekers. There are many different paths with different levels of comfort, length, and stability, which are uncertain during the research process. Finding a systematic way to deal with this uncertainty can greatly assist the search for a safe path which is in our case the development of a suitable visualization algorithm for a specific problem. In this work we will analyze the sources of uncertainty in heuristically solving visualization problems and will propose directions to handle these uncertainties.
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Acknowledgments
We would like to acknowledge the Bridge-Project SmartCT and the K-Project ZPT (http://www.3dct.at) of the Austrian Research Promotion Agency (FFG). We also acknowledge the ViMaL project supported by the Austrian Science Fund (FWF), grant no. P21695.
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Amirkhanov, A., Bruckner, S., Heinzl, C., Gröller, M.E. (2014). The Haunted Swamps of Heuristics: Uncertainty in Problem Solving. In: Hansen, C., Chen, M., Johnson, C., Kaufman, A., Hagen, H. (eds) Scientific Visualization. Mathematics and Visualization. Springer, London. https://doi.org/10.1007/978-1-4471-6497-5_5
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