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Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations

Authors:

Maneesh AgrawalaAuthors Info & Claims

CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1303 - 1312

https://doi.org/10.1145/1518701.1518897

Published: 04 April 2009 Publication History

Abstract

We investigate techniques for visualizing time series data and evaluate their effect in value comparison tasks. We compare line charts with horizon graphs - a space-efficient time series visualization technique - across a range of chart sizes, measuring the speed and accuracy of subjects' estimates of value differences between charts. We identify transition points at which reducing the chart height results in significantly differing drops in estimation accuracy across the compared chart types, and we find optimal positions in the speed-accuracy tradeoff curve at which viewers performed quickly without attendant drops in accuracy. Based on these results, we propose approaches for increasing data density that optimize graphical perception.

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Patel ABaxter WPorat T(2024)Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic ReviewJournal of Medical Internet Research10.2196/5808826(e58088)Online publication date: 20-Nov-2024
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Index Terms

Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2009

2426 pages

ISBN:9781605582467

DOI:10.1145/1518701

General Chairs:
Dan R. Olsen
Brigham Young University
,
Richard B. Arthur
Brigham Young University
,
Program Chairs:
Ken Hinckley
Microsoft Research
,
Meredith Ringel Morris
Microsoft Research
,
Scott Hudson
Carnegie Mellon University
,
Saul Greenberg
University of Calgary

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 April 2009

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April 4 - 9, 2009

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CHI '09 Paper Acceptance Rate 277 of 1,130 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Kusnick JLichtenberg SWiegreffe DHuber-Sannwald ENehren UJänicke S(2024)Visual analysis of diversity and threat status of natural materials for musical instrumentsFrontiers in Environmental Science10.3389/fenvs.2024.140637612Online publication date: 18-Dec-2024
https://doi.org/10.3389/fenvs.2024.1406376
Patel ABaxter WPorat T(2024)Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic ReviewJournal of Medical Internet Research10.2196/5808826(e58088)Online publication date: 20-Nov-2024
https://doi.org/10.2196/58088
Maçãs CCampos JLourenço NMachado P(2024)Visualisation of Random Forest classificationInformation Visualization10.1177/1473871624126074523:4(312-327)Online publication date: 24-Jun-2024
https://doi.org/10.1177/14738716241260745
Lee SChang MPark SSeo J(2024)Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness2024 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS55277.2024.00053(226-230)Online publication date: 13-Oct-2024
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