Doctor's Theses (authored and supervised):
"Integration Strategies in the Visualization of Multifaceted Spatial Data";
Supervisor, Reviewer: I. Viola, E. Gröller, T. Möller, B. Kozlikova;
Institut für Computergraphik und Algorithmen,
oral examination: 2017-11-22.
Visualization designers have several visual channels at their disposal for encoding data into visual representations, e.g., position, size, shape, orientation, color, texture, brightness, as well as motion. The mapping of attributes to visual channels can be chosen by the designer. In theory, any data attribute can be represented by any of these visual channels or by a combination of multiple of these channels. In practice, the optimal mapping and the most suitable type of visualization strongly depend on the data as well as on the user's task. In the visualization of spatial data, the mapping of spatial attributes to visual channels is inherently given by the data. Multifaceted spatial data possesses a wide range of additional (non-spatial) attributes without a given mapping. The data's given spatial context is often important for successfully fulfilling a task. The design space in spatial data visualization can therefore be heavily constrained when trying to choose an optimal mapping for other attributes within the spatial context. To solve an exploration or presentation task in the domain of multifaceted spatial data, special strategies have to be employed in order to integrate the essential information from the various data facets in an appropriate representation form with the spatial context. This thesis explores visualization integration strategies for multifaceted spatial data. The first part of this thesis describes the design space of integration in terms of two aspects: visual and functional integration. Visual integration describes how representations of the different data facets can be visually composed within a spatial context. Functional integration, describes how events that have been triggered, for instance, through user interaction, can be coordinated across the various visually integrated representations. The second part of this thesis describes contributions to the field of visualization in the context of concrete integration applications for exploration and presentation scenarios. The first scenario addresses a set of challenges in the exploratory analysis of multifaceted spatial data in the scope of a decision making scenario in lighting design. The user's task is to find an optimal lighting solution among dozens or even hundreds of potential candidates. In the scope of a design study, the challenges in lighting design are addressed with LiteVis, a system that integrates representations of the simulation parameter space with representations of all relevant aspects of the simulation output. The integration of these heterogeneous aspects together with a novel ranking visualization are thereby the key to enabling an efficient exploration and comparison of lighting parametrizations. In presentation scenarios, the generation of insights often cannot rely on user interaction and therefore needs a different approach. The challenge is to generate visually appealing, yet information-rich representations for mainly passive observation. In this context, this thesis addresses two different challenges in the domain of molecular visualization. The first challenge concerns the conveying of relations between two different representations of a molecular data set, such as a virus. The relation is established via animated transitions - a temporal form of integration between two representations. The proposed solution features a novel technique for creating such transitions that are re-usable for different data sets, and can be combined in a modular fashion. Another challenge in presentation scenarios of multifaceted spatial data concerns the presentation of the transition between development states of molecular models, where the actual biochemical process of the transition is not exactly known or it is too complex to represent. A novel technique applies a continuous abstraction of both model representations to a level of detail at which the relationship between them can be accurately conveyed, in order to overcome a potential indication of false relationship information. Integration thereby brings the different abstraction levels and the different model states into relation with each other. The results of this thesis clearly demonstrate that integration is a versatile tool in overcoming key challenges in the visualization of multifaceted spatial data.
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.