Node-attribute Graph Layout for Small-World Networks

Gibson, Helen; Faith, Joe

doi:10.1109/iv.2011.64

Cited by 4 publications

(5 citation statements)

References 27 publications

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“…Force‐based approaches have been extended in various ways to further enforce the implicit grouping of nodes for disjoint flat groups [BC01, DKM06, DM14b, Noa07]. In general graph layout algorithms, a generic approach to consider disjoint or overlapping groups / is to use pseudo (dummy) vertices that represent sets of vertices and are connected to all contained vertices [EFN99, EH00, GF11]. For disjoint groups , another method is based on a divide‐and‐conquer strategy [ACJM03, AMA07b, EF97, FT04]: first, a meta‐layout is derived for an aggregated graph with collapsed groups; then, the vertices of each group are laid out independently.…”

Section: Implicit Encodings Of Vertex Groupsmentioning

confidence: 99%

Visualizing Group Structures in Graphs: A Survey

Vehlow

Beck

Weiskopf

2016

Computer Graphics Forum

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Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still needs to be represented for analyzing the data in more depth. This work surveys research in visualizing group structures as part of graph diagrams. A particular focus is the explicit visual encoding of groups, rather than only using graph layout to indicate groups implicitly. We introduce a taxonomy of visualization techniques structuring the field into four main categories: visual node attributes vary properties of the node representation to encode the grouping, juxtaposed approaches use two separate visualizations, superimposed techniques work with two aligned visual layers, and embedded visualizations tightly integrate group and graph representation. The derived taxonomies for group structure and visualization types are also applied to group visualizations of edges. We survey group-only, group-node, group-edge and group-network tasks that are described in the literature as use cases of group visualizations. We discuss results from evaluations of existing visualization techniques as well as main areas of application. Finally, we report future challenges based on interviews we conducted with leading researchers of the field.

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Section: Implicit Encodings Of Vertex Groupsmentioning

confidence: 99%

Visualizing Group Structures in Graphs: A Survey

Vehlow

Beck

Weiskopf

2016

Computer Graphics Forum

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“…Two recent methods which also use the idea of dimension reduction are EdgeMaps by Dork et al Targeted projection pursuit for graphs 134 also considers multiple node-attributes and relates each one to a dimension. Initially, nodes are laid out using a PCA projection based on the nodeattributes.…”

Section: Mapping Attributes Directly To Two-dimensional Spacementioning

confidence: 99%

“…Two recent methods that also use the idea of dimension reduction are EdgeMaps by Dork et al 133 and Gibson and Faith’s 134 application of targeted projection pursuit (TPP) to graph layout. The aim of EdgeMaps was to unite the visualisation of node–link diagrams that show the explicit relationships between nodes in the graph and multi-dimensional scaling techniques used to visualise implicit relationships, i.e.…”

Section: Constraint-based Layoutsmentioning

confidence: 99%

A survey of two-dimensional graph layout techniques for information visualisation

Gibson

Faith

Vickers

2012

Information Visualization

Self Cite

159

104

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Many algorithms for graph layout have been devised over the last 30 years spanning both the graph drawing and information visualisation communities. This article first reviews the advances made in the field of graph drawing that have then often been applied by the information visualisation community. There then follows a discussion of a range of techniques developed specifically for graph visualisations. Graph drawing algorithms are categorised into the followings approaches: forcedirected layouts, the use of dimension reduction in graph layout and computational improvements including multi-level techniques. Methods developed specifically for graph visualisation often make use of node-attributes and are categorised based on whether the attributes are used to introduce constraints to the layout, provide a clustered view or used to define an explicit representation in 2D space. The similarities and distinctions between these techniques are examined and the aim is to provide a detailed assessment of currently available graph layout techniques, specifically how they can be used by visualisation practitioners and to motivate further research in the area.

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“…Users can then use a table on the right-hand side of the tool to identify which attributes are contributing most significantly to the projection. An extension to this where the user is able to show a set of edges in a graph, thus positioning the nodes in the projection becomes a graph layout method, has already been published [2].…”

Section: Extending Tppmentioning

confidence: 99%

“…The task, through the use of firewall and intrusion detection system logs, is to identify the noteworthy events in the system, any security trends, the root causes of the problems and, following this, to recommend actions to prevent this happening again in the future. The approach taken has been to adapt this data into a node-attribute graph and to use an extended version of targeted projection pursuit (TPP) [1,2] to analyse this data as a graph.…”

Section: Introductionmentioning

confidence: 99%

Network infrastructure visualisation using high-dimensional node-attribute data

Gibson

Vickers

2012

2012 IEEE Conference on Visual Analytics Science and Technology (VAST)

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We present an extended version of targeted projection pursuit, a high dimensional data exploration tool adapted for producing graph layouts using node-attributes. Attributes are generated based on detected events in the intrusion detection system and firewall logs and how often they occur for each IP address. Edges are the directed links between source and destination IPs. The layout is interactive and users can manipulate the points in order to find interesting layouts and then further analyse how these layouts are related to the events in the logs. Thus, they first allow the user to detect anomalies and then gives them a platform to investigate why they occur.

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Node-attribute Graph Layout for Small-World Networks

Cited by 4 publications

References 27 publications

Visualizing Group Structures in Graphs: A Survey

Visualizing Group Structures in Graphs: A Survey

A survey of two-dimensional graph layout techniques for information visualisation

Network infrastructure visualisation using high-dimensional node-attribute data

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