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Visualization and Analysis of Multifields using Pareto Sets

  • The focus of this work is to provide and evaluate a novel method for multifield topology-based analysis and visualization. Through this concept, called Pareto sets, one is capable to identify critical regions in a multifield with arbitrary many individual fields. It uses ideas found in graph optimization to find common behavior and areas of divergence between multiple optimization objectives. The connections between the latter areas can be reduced into a graph structure allowing for an abstract visualization of the multifield to support data exploration and understanding. The research question that is answered in this dissertation is about the general capability and expandability of the Pareto set concept in context of visualization and application. Furthermore, the study of its relations, drawbacks and advantages towards other topological-based approaches. This questions is answered in several steps, including consideration and comparison with related work, a thorough introduction of the Pareto set itself as well as a framework for efficient implementation and an attached discussion regarding limitations of the concept and their implications for run time, suitable data, and possible improvements. Furthermore, this work considers possible simplification approaches like integrated single-field simplification methods but also using common structures identified through the Pareto set concept to smooth all individual fields at once. These considerations are especially important for real-world scenarios to visualize highly complex data by removing small local structures without destroying information about larger, global trends. To further emphasize possible improvements and expandability of the Pareto set concept, the thesis studies a variety of different real world applications. For each scenario, this work shows how the definition and visualization of the Pareto set is used and improved for data exploration and analysis based on the scenarios. In summary, this dissertation provides a complete and sound summary of the Pareto set concept as ground work for future application of multifield data analysis. The possible scenarios include those presented in the application section, but are found in a wide range of research and industrial areas relying on uncertainty analysis, time-varying data, and ensembles of data sets in general.

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Author:Lars Stefan Huettenberger
URN (permanent link):urn:nbn:de:hbz:386-kluedo-54710
Advisor:Christoph Garth
Document Type:Doctoral Thesis
Language of publication:English
Publication Date:2019/01/22
Date of first Publication:2019/01/22
Publishing Institute:Technische Universität Kaiserslautern
Granting Institute:Technische Universität Kaiserslautern
Acceptance Date of the Thesis:2018/12/20
Date of the Publication (Server):2019/01/29
Tag:Multifield Data; Pareto Optimality; Topology
Number of page:XXIV, 153
Faculties / Organisational entities:Fachbereich Informatik
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):Creative Commons 4.0 - Namensnennung (CC BY 4.0)