Visualization of dynamic graphs using edge bundling

• Grant number: 14/18665-1
• Support Opportunities: Scholarships in Brazil - Master
• Start date: December 01, 2014
• End date: August 31, 2016
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Fernando Vieira Paulovich
• Grantee: Fábio Henrique Gomes Sikansi
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 11/22749-8 - Challenges in exploratory visualization of multidimensional data: paradigms, scalability and applications, AP.TEM

Abstract

Graphs are successfully applied to represent different datasets. They have being studied in different areas of discrete Mathematics and Computing in general. In particular, the dynamic graphs (i.e., time-varying graphs) are applied to model problems in which the temporal attributes have influence on the topology of the graph. In information visualization, there are different approaches to perform the visual representation of graphs. However, the visualization of a large number of elements in a limited area generates the visual-clutter problem. Among the techniques of graph visualization that attack this problem, there are the techniques that use Edge-bundling. These techniques present great success in improving the quality from the visual representation. However, many of them can only be applied to static graphs. In addition, existing techniques perform the bundle based only on visual space information, that discards the dataset information. In this project, we aim to develop a new technique for graph visualization using edge bundling. The proposed method is based on the use of similarity trees. We hope we can produce an Edge-bundling visualization through the similarity relations between the dataset, applicable to dynamic graphs. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SIKANSI, FABIO; DA SILVA, RENATO R. O.; CANTAREIRA, GABRIEL D.; ETEMAD, ELHAM; PAULOVICH, FERNANDO V.. Similarity-Driven Edge Bundling: Data-Oriented Clutter Reduction in Graphs Layouts. ALGORITHMS, v. 13, n. 11, NOV 2020. (14/18665-1, 11/22749-8)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SIKANSI, Fábio Henrique Gomes. A similarity-based approach to generate edge bundles. 2016. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.