GraphTrials: Visual Proofs of Graph Properties

Fuente: arXiv
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Main Authors: Förster, Henry, Klesen, Felix, Dwyer, Tim, Eades, Peter, Hong, Seok-Hee, Kobourov, Stephen G., Liotta, Giuseppe, Misue, Kazuo, Montecchiani, Fabrizio, Pastukhov, Alexander, Schreiber, Falk
Format: Preprint
Published: 2024
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author Förster, Henry
Klesen, Felix
Dwyer, Tim
Eades, Peter
Hong, Seok-Hee
Kobourov, Stephen G.
Liotta, Giuseppe
Misue, Kazuo
Montecchiani, Fabrizio
Pastukhov, Alexander
Schreiber, Falk
author_facet Förster, Henry
Klesen, Felix
Dwyer, Tim
Eades, Peter
Hong, Seok-Hee
Kobourov, Stephen G.
Liotta, Giuseppe
Misue, Kazuo
Montecchiani, Fabrizio
Pastukhov, Alexander
Schreiber, Falk
contents Graph and network visualization supports exploration, analysis and communication of relational data arising in many domains: from biological and social networks, to transportation and powergrid systems. With the arrival of AI-based question-answering tools, issues of trustworthiness and explainability of generated answers motivate a greater role for visualization. In the context of graphs, we see the need for visualizations that can convince a critical audience that an assertion about the graph under analysis is valid. The requirements for such representations that convey precisely one specific graph property are quite different from standard network visualization criteria which optimize general aesthetics and readability. In this paper, we aim to provide a comprehensive introduction to visual proofs of graph properties and a foundation for further research in the area. We present a framework that defines what it means to visually prove a graph property. In the process, we introduce the notion of a visual certificate, that is, a specialized faithful graph visualization that leverages the viewer's perception, in particular, pre-attentive processing (e.g. via pop-out effects), to verify a given assertion about the represented graph. We also discuss the relationships between visual complexity, cognitive load and complexity theory, and propose a classification based on visual proof complexity. Finally, we provide examples of visual certificates for problems in different visual proof complexity classes.
format Preprint
id arxiv_https___arxiv_org_abs_2409_02907
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GraphTrials: Visual Proofs of Graph Properties
Förster, Henry
Klesen, Felix
Dwyer, Tim
Eades, Peter
Hong, Seok-Hee
Kobourov, Stephen G.
Liotta, Giuseppe
Misue, Kazuo
Montecchiani, Fabrizio
Pastukhov, Alexander
Schreiber, Falk
Human-Computer Interaction
Graph and network visualization supports exploration, analysis and communication of relational data arising in many domains: from biological and social networks, to transportation and powergrid systems. With the arrival of AI-based question-answering tools, issues of trustworthiness and explainability of generated answers motivate a greater role for visualization. In the context of graphs, we see the need for visualizations that can convince a critical audience that an assertion about the graph under analysis is valid. The requirements for such representations that convey precisely one specific graph property are quite different from standard network visualization criteria which optimize general aesthetics and readability. In this paper, we aim to provide a comprehensive introduction to visual proofs of graph properties and a foundation for further research in the area. We present a framework that defines what it means to visually prove a graph property. In the process, we introduce the notion of a visual certificate, that is, a specialized faithful graph visualization that leverages the viewer's perception, in particular, pre-attentive processing (e.g. via pop-out effects), to verify a given assertion about the represented graph. We also discuss the relationships between visual complexity, cognitive load and complexity theory, and propose a classification based on visual proof complexity. Finally, we provide examples of visual certificates for problems in different visual proof complexity classes.
title GraphTrials: Visual Proofs of Graph Properties
topic Human-Computer Interaction
url https://arxiv.org/abs/2409.02907