TimeLighting: Guided Exploration of 2D Temporal Network Projections

Fuente: arXiv
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Autori principali: Filipov, Velitchko, Ceneda, Davide, Archambault, Daniel, Arleo, Alessio
Natura: Preprint
Pubblicazione: 2023
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author Filipov, Velitchko
Ceneda, Davide
Archambault, Daniel
Arleo, Alessio
author_facet Filipov, Velitchko
Ceneda, Davide
Archambault, Daniel
Arleo, Alessio
contents In temporal ( event-based ) networks, time is a continuous axis, with real-valued time coordinates for each node and edge. Computing a layout for such graphs means embedding the node trajectories and edge surfaces over time in a 2D+t space, known as the space-time cube. Currently, these space-time cube layouts are visualized through animation or by slicing the cube at regular intervals. However, both techniques present problems such as below-average performance on tasks as well as loss of precision and difficulties in selecting timeslice intervals. In this paper, we present TimeLighting , a novel visual analytics approach to visualize and explore temporal graphs embedded in the space-time cube. Our interactive approach highlights node trajectories and their movement over time, visualizes node "aging", and provides guidance to support users during exploration by indicating interesting time intervals ("when") and network elements ("where") are located for a detail-oriented investigation. This combined focus helps to gain deeper insights into the temporal network's underlying behavior. We assess the utility and efficacy of our approach through two case studies and qualitative expert evaluation. The results demonstrate how TimeLighting supports identifying temporal patterns, extracting insights from nodes with high activity, and guiding the exploration and analysis process.
format Preprint
id arxiv_https___arxiv_org_abs_2308_12628
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle TimeLighting: Guided Exploration of 2D Temporal Network Projections
Filipov, Velitchko
Ceneda, Davide
Archambault, Daniel
Arleo, Alessio
Human-Computer Interaction
In temporal ( event-based ) networks, time is a continuous axis, with real-valued time coordinates for each node and edge. Computing a layout for such graphs means embedding the node trajectories and edge surfaces over time in a 2D+t space, known as the space-time cube. Currently, these space-time cube layouts are visualized through animation or by slicing the cube at regular intervals. However, both techniques present problems such as below-average performance on tasks as well as loss of precision and difficulties in selecting timeslice intervals. In this paper, we present TimeLighting , a novel visual analytics approach to visualize and explore temporal graphs embedded in the space-time cube. Our interactive approach highlights node trajectories and their movement over time, visualizes node "aging", and provides guidance to support users during exploration by indicating interesting time intervals ("when") and network elements ("where") are located for a detail-oriented investigation. This combined focus helps to gain deeper insights into the temporal network's underlying behavior. We assess the utility and efficacy of our approach through two case studies and qualitative expert evaluation. The results demonstrate how TimeLighting supports identifying temporal patterns, extracting insights from nodes with high activity, and guiding the exploration and analysis process.
title TimeLighting: Guided Exploration of 2D Temporal Network Projections
topic Human-Computer Interaction
url https://arxiv.org/abs/2308.12628