Network visualisation: a review

Withall, Mark S.; Phillips, Iain; Parish, David J.

doi:10.1049/iet-com:20060169

Cited by 21 publications

(14 citation statements)

References 15 publications

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“…Hadlak et al (2015) discuss the visual integration of multiple facets given with the networks, namely hierarchies/clusters on top of the network as well as network attributes, dynamics, and spatialisation, which are all relevant for climate networks, too. In particular, for net-works with given geo-references, overview articles/books are available from a graph drawing (Wolff, 2013), from an information visualisation (Withall et al, 2007;Rozenblat and Melançon, 2013), as well as from a cartography perspective (Rodgers, 2005).…”

Section: Techniques For Geo-referenced Network Visualisationmentioning

confidence: 99%

Review: visual analytics of climate networks

Nocke

Buschmann

Donges

et al. 2015

Nonlin. Processes Geophys.

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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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Section: Techniques For Geo-referenced Network Visualisationmentioning

confidence: 99%

Review: visual analytics of climate networks

Nocke

Buschmann

Donges

et al. 2015

Nonlin. Processes Geophys.

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“…The topology of agent interactions is commonly represented as a tree or cyclic graph and can therefore employ any of an array of network visualization strategies from other fields (e.g., see [53] in the context of communication networks, or [7] more generally). A graph is useful for representing It shows a grid containing two flower types (light and dark gray squares) and bees (text strings: agent id., type, and other statistics).…”

Section: Model Validationmentioning

confidence: 99%

The Practice of Agent-Based Model Visualization

Dorin

Geard

2014

Artificial Life

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We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

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“…Network visualization can be roughly classified as geographic, abstract, and plot-based topology visualizations [35]. Geographic network visualization provides physical location of the network components on a map.…”

Section: Internet Topology Visualizationmentioning

confidence: 99%