Visual Editing and Comparison of Multivariate Graphs Using Multiple Interactive Displays (GEMS 2.0)

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Data is everywhere. Nowadays, an increasing amount of intellectual work is based on measured, collected, modeled, synthesized, or simulated data. This proposal focuses on a particularly important class of data: graphs. Graphs are universally relevant in many application domains, such as communication, transportation, biology, and climatology. In these domains, there is an increasing demand for methods and tools that do not only support working with a graph's structure, that is, its nodes and edges, but also with numerous data attributes that may be associated with the graph. Understanding such multivariate graphs comprehensively is a significant challenge for the people working with them.Working with data usually means analyzing them. Interactive visual analysis has proved to be an effective mean to gain insight into data. Yet, there is more to working with graphs than understanding basic information of their structure and attributes. In this proposal, we plan to study how classic exploratory graph analysis can be advanced to include comparative analysis of multiple graphs and the possibility to directly edit a graph's nodes and edges as well as its associated attributes when necessary.Such a combined visual exploration, comparison, and editing of multivariate graphs is a complex endeavor, because it involves various linked visual representations of the data and diverse ways of interacting with them. The typical data workplace, however, still consists of classic desktop interfaces with mouse plus keyboard interaction, which proved to be ineffective for complex graph analysis. To support smooth and seamless work on multivariate graphs, better and more natural user interfaces are needed. Therefore, in this proposal we will investigate natural forms of interaction, such as touch, body-centric, and gaze-based interaction in concert with multi-display environments consisting of large and mobile interactive displays.In summary, this project focuses on developing novel and fundamental concepts, methods, and tools for comparing and editing multiple multivariate graphs with novel interaction modalities in multi-display environments.