In this paper we describe a system for visualizing and analyzing worldwide research topics, rtopmap . We gather data from google scholar academic research profiles, putting together a weighted topics graph, consisting of over 35,000 nodes and 646,000 edges. The nodes correspond to self-reported research topics, and edges correspond to co-occurring topics in google scholar profiles. The rtopmap system supports zooming panning searching and other google-maps-based interactive features. With the help of map overlays, we also visualize the strengths and weaknesses of different academic institutions in terms of human resources (e.g., number of researchers in different areas), as well as scholarly output (e.g., citation counts in different areas). Finally, we also visualize what parts of the map are associated with different academic departments, or with specific documents (such as research papers, or calls for proposals). The system itself is available at this http URL .
Also related to our work are many of the graph visualization techniques and tools. Graph layout algorithms are also provided in several libraries, such as GraphViz @cite_34 , OGDF @cite_17 , MSAGL @cite_27 , and VTK @cite_30 , which however, do not support interaction, navigation, and data manipulation. Visualization toolkits such as Prefuse @cite_14 , Tulip @cite_42 , Gephi @cite_54 , and yEd @cite_6 support visual graph manipulation, and while they can handle large graphs, their rendering does not: even for graphs with a few thousand vertices, the amount of information rendered statically on the screen makes the visualization difficult to use.
@cite_30 @cite_14 @cite_54 @cite_42 @cite_6 @cite_27 @cite_34 @cite_17
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We introduce basic concepts behind the Visualization Toolkit (VTK). An overview of the system, plus some detailed examples, will assist in learning this system. The tutorial targets researchers of any discipline who have 2D or 3D data and want more control over the visualization process than a turn-key system can provide. It also assists developers who would like to incorporate VTK into an application as a visualization or data processing engine. Although information visualization (infovis) technologies have proven indispensable tools for making sense of complex data, wide-spread deployment has yet to take hold, as successful infovis applications are often difficult to author and require domain-specific customization. To address these issues, we have created prefuse, a software framework for creating dynamic visualizations of both structured and unstructured data. prefuse provides theoretically-motivated abstractions for the design of a wide range of visualization applications, enabling programmers to string together desired components quickly to create and customize working visualizations. To evaluate prefuse we have built both existing and novel visualizations testing the toolkit's flexibility and performance, and have run usability studies and usage surveys finding that programmers find the toolkit usable and effective. Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the context of interactive exploration and interpretation of networks. It provides easy and broad access to network data and allows for spatializing, filtering, navigating, manipulating and clustering. Finally, by presenting dynamic features of Gephi, we highlight key aspects of dynamic network visualization. Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. Based on a decade of research and development of this framework, we present the architecture, consisting of a suite of tools and techniques, that can be used to address a large variety of domain-specific problems. With Tulip, we aim to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing. The current framework enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualizations. The software model facilitates the reuse of components and allows the developers to focus on programming their application. This development pipeline makes the framework efficient for research prototyping as well as the development of end-user applications. yFiles is a Java-based library for the visualization and automatic layout of graph structures. Included features are data structures, graph algorithms, diverse layout and labeling algorithms and a graph viewer component. Cluster Layout Planarity testing Booth Lueker and Boyer Myrvold Cluster () Upward () Customizable planarization method Edge insertion (fixed & variable embedding) Crossing Minimization optimal, minor-monotone, simultaneous Orthogonal layout Compaction (constructive + improvement) Customizable Sugiyama layout Energy-based layout (FM, ...) Tree-, Circular-, Balloon-layout, ...