Knowledge about visualization tasks plays an important role in choosing or building suitable visual representations to pursue them. Yet, tasks are a multi-faceted concept and it is thus not surprising that the many existing task taxonomies and models all describe different aspects of tasks, depending on what these task descriptions aim to capture. This results in a clear need to bring these different aspects together under the common hood of a general design space of visualization tasks, which we propose in this paper. Our design space consists of five design dimensions that characterize the main aspects of tasks and that have so far been distributed across different task descriptions. We exemplify its concrete use by applying our design space in the domain of climate impact research. To this end, we propose interfaces to our design space for different user roles (developers, authors, and end users) that allow users of different levels of expertise to work with it.

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Visualization, Cluster Analysis, Climate Impact Research,

Abstract. Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

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