Visual Exploration in Visualization Space

Visualization is the transformation of data into readily comprehensible images, and has proven to be an indispensable part of the discovery process in many fields. Computer-based visualizations are ubiquitous in science, engineering, business, and many other disciplines. They are a powerful tools to elucidate complex phenomena, and provide users with essential information in important scenarios as diverse as cancer treatment, engine design, or financial investments. However, the space of possible visualizations is vast and it is often difficult for non-experts to decide which visualization is most suitable for their purpose. We were able present theoretical contributions on how to assess interactive visualization techniques as well as practical solutions on how to measure the relevance of a visualization for particular tasks. Furthermore, we developed an initial prototype of our meta visualization environment. We have also been able to extend our approach to the realm of automated computational art, and have presented several results related to how the underlying methods that have been developed can be applied to different applications.

All publications resulting from the project were driven by the PI's research vision, as is evident by his role as the senior/first author on all of them. However, in several instances we were able to establish new or intensify existing research collaborations. Of the total 20 papers published within the scope of the project, 15 were published in level-2 venues constituting the premier publication outlets in the field of visualization. We received a Best Paper Award at the 2017 Spring Conference on Computer Graphics and a Best Paper Honorable Mention at IEEE VIS 2018, the largest international scientific conference on visualization. Furthermore, work conducted in the scope of the project received the 2019 EuroVis Best PhD Award. Part of our was presented at the Christiekonferansen in 2019 and has received considerable attention outside academia and this has subsequently led to the establishment of a company focusing on the creation of algorithmic art.

Visualization is the transformation of data into readily comprehensible images, and has proven to be an indispensable part of the discovery process in many fields of contemporary science and engineering. A vast number of different visualization methods have been developed, some very general, some only applicable to specific types of data. This makes it increasingly difficult to chose between the many alternatives given a certain task. This project is devoted to the study of the space of visualizations itself and aims to develop means for its interactive exploration. A key realization of our approach is that by regarding the visualization process as a complex phenomenon, it becomes amenable to parameter space analysis techniques. Within the scope of this project, methods for systematically structuring this visualization space will be devised and embedded in an interactive web-based framework. In particular, we plan to investigate techniques to automatically infer the performance of individual visualizations for particular tasks based on a sparse user classification and to provide an environment for interactively presenting and refining these measures. The MetaVis project addresses an important challenge which affects visualization experts as well as users of visualization methods in their daily work. The project will be hosted by the Visualization Research Group at the university of Bergen and lead by Stefan Bruckner. The project team will collaborate with international leading researchers in visual data science and human-centered visualization (Torsten Möller and Michael Sedlmair at the University of Vienna), interactive biomedical data visualization (Timo Ropinski at the University of Ulm), as well as, nationally, with experts in cognitive psychology and visual perception (Marc Price at the Bergen Laboratory for the Study of Decision, Intuition, Consciousness and Emotion).