[Zurück]

A. Amirkhanov, S. Bruckner, Ch. Heinzl, E. Gröller:
"The Haunted Swamps of Heuristics: Uncertainty in Problem Solving";
in: "Scientific Visualization - Uncertainty, Multifield, Biomedical, and Scalable Visualization", Springer, London, 2014, ISBN: 978-1-4471-6496-8, S. 51 - 60.

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.