Visual Analysis of Multilayer Networks
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Visual Analysis of Multilayer Networks, Morgan & Claypool Publishers
Von Fintan McGee, Tatiana von Landesberger, Benjamin Renoust, Daniel Archambault, Mohammad Ghoniem, Andreas Kerren, Bruno Pinaud, Margit Pohl, Benoît Otjacques, Guy Melançon, im heise Shop in digitaler Fassung erhältlich
Produktinformationen "Visual Analysis of Multilayer Networks"
THIS IS AN OVERVIEW AND STRUCTURED ANALYSIS OF CONTEMPORARY MULTILAYER NETWORK VISUALIZATION. IT SURVEYS TECHNIQUES AS WELL AS TOOLS, TASKS, AND ANALYTICS FROM WITHIN APPLICATION DOMAINS. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them.
Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains.
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.
* 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
Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains.
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.
* 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
Artikel-Details
- Anbieter:
- Morgan & Claypool Publishers
- Autor:
- Andreas Kerren, Benjamin Renoust, Benoît Otjacques, Bruno Pinaud, Daniel Archambault, Fintan McGee, Guy Melançon, Margit Pohl, Mohammad Ghoniem, Tatiana von Landesberger
- Artikelnummer:
- 9781636391441
- Veröffentlicht:
- 10.06.21
- Seitenanzahl:
- 150