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Visual Analysis of Multilayer Networks [electronic resource] / by Fintan McGee, Benjamin Renoust, Daniel Archambault, Mohammad Ghoniem, Andreas Kerren, Bruno Pinaud.

By: McGee, Fintan [author.].
Contributor(s): Renoust, Benjamin [author.] | Archambault, Daniel [author.] | Ghoniem, Mohammad [author.] | Kerren, Andreas [author.] | Pinaud, Bruno [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Visualization: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2021Edition: 1st ed. 2021.Description: XV, 134 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031026089.Subject(s): Information visualization | Data structures (Computer science) | Information theory | Data mining | Data and Information Visualization | Data Structures and Information Theory | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 001.4226 Online resources: Click here to access online
Contents:
Preface -- Figure Credits -- Introduction and Overview -- Multilayer Networks Across Domains -- The Layer as an Entity -- Task Taxonomy for Multilayer Networks -- Visualization of Nodes and Relationships Across Layers -- Interacting with and Analyzing Multilayer Networks -- Attribute Visualization and Multilayer Networks -- Evaluation of Multilayer Network Visualization Systems and Techniques -- Conclusions -- Bibliography -- Authors' Biographies -- List of Figures.
In: Springer Nature eBookSummary: The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.
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Preface -- Figure Credits -- Introduction and Overview -- Multilayer Networks Across Domains -- The Layer as an Entity -- Task Taxonomy for Multilayer Networks -- Visualization of Nodes and Relationships Across Layers -- Interacting with and Analyzing Multilayer Networks -- Attribute Visualization and Multilayer Networks -- Evaluation of Multilayer Network Visualization Systems and Techniques -- Conclusions -- Bibliography -- Authors' Biographies -- List of Figures.

The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.

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