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Next generation bundling: tackling multivariate data and visualization errors

Grant number: 22/05036-2
Support Opportunities:Scholarships in Brazil - Master
Start date: July 01, 2022
End date: August 31, 2024
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Fabio Kon
Grantee:Lucas Pires Stankus
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:14/50937-1 - INCT 2014: on the Internet of the Future, AP.TEM
Associated scholarship(s):22/13481-6 - Next generation bundling: tackling multivariate data and visualization errors, BE.EP.MS

Abstract

Visualizing graphs and trajectory datasets is a key method to analyze such data, as it enables the identification of complex spatial or structural patterns. However, large datasets of such types are hard to visualize, as directly plotting them to images generates much clutter, obfuscating the patterns. Path bundling is a technique that aims to bundle paths in logical ways, minimizing clutter and highlighting the overall structure of a graph or network. Given its nature, bundling deforms the original drawing. Such errors could lead to misunderstandings of the data. Current methods fail to address displaying the distortion generically and insightfully. Also not adequately addressed by the existing literature, is the bundling of multivariate data. This master's research project aims to develop new methods for displaying (and controlling) bundle-generated errors and bundling multivariate data. The developed methods will be implemented on top of CUBu, currently the fastest and most feature-rich bundling framework in existence. Existing literature will be studied to position and motivate our proposed methods. This project also foresees an application to the Research Scholarship Abroad Program (BEPE) to spend six months in collaborative work with Prof. Alexandru Telea at Utrecht University (the Netherlands), the cosupervisor of the current research project and co-author of a significant amount of relevant bundling papers. (AU)

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