Assessing the quality of geoscientific simulation models with visual analytics methods – a design study

Abstract

Originally published as:Dransch, D., Köthur, P., Schulte, S., Klemann, V., Dobslaw, H. (2010): Assessing the quality of geoscientific simulation models with visual analytics methods -a design study. -International Journal of Geographical Information Science, 24, 10, 1459-1479 DOI: 10.1080/13658816.2010 Assessing the quality of geoscientific simulation models with visual analytics methods -a design study Simulation models are essential means of scientific knowledge building and also the basis for decision-making. Because of their relevance, they have to be assessed thoroughly with respect to their quality. Simulation model assessment comprises two challenges: (a) modelers have to create a comprehensive mental image of the model's quality despite the massive multidimensional, multivariate, and often heterogeneous data; and (b) the model assessment process should be as efficient as possible. We face these challenges with a visual analytics approach. We aim at developing interactive visual representations which, in combination with present computational analysis methods, support the scientist's reasoning process to enhance the assessment of simulation models. In a design study, we analyzed two exemplary reasoning processes which cover the main model assessment procedures: the evaluation of the internal coherence of the model's structure and behavior and the assessment of its empirical validity. The analysis was conducted by means of a user-and task-centered approach which combines several knowledge elicitation techniques and task analysis concepts. We derived domain tasks as well as cognitive actions and developed and implemented interactive visualization components which supplement the statistical analysis methods already used. An informal qualitative user study shows that our visual analytics approach and tools help gain a more detailed mental image and hence a better understanding of the data and the underlying simulation model and allow for a faster and more comprehensive assessment of the simulation model.

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Visual Analytics for Comparison of Ocean Model Output with Reference Data: Detecting and Analyzing Geophysical Processes Using Clustering Ensembles

“…We adopted a user-and task-centered approach [14] in our collaboration with ocean modelers at the German Research Center for Geosciences GFZ. This involved frequent meetings and discussions with our partners to obtain a detailed understanding of the model assessment process and the associated challenges.…”