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Dynamic Opacity Optimization for Scatter Plots

Authors:

Justin Matejka,

Fraser Anderson,

George FitzmauriceAuthors Info & Claims

CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

Pages 2707 - 2710

https://doi.org/10.1145/2702123.2702585

Published: 18 April 2015 Publication History

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Abstract

Scatterplots are an effective and commonly used technique to show the relationship between two variables. However, as the number of data points increases, the chart suffers from "over-plotting" which obscures data points and makes the underlying distribution of the data difficult to discern. Reducing the opacity of the data points is an effective way to address over-plotting, however, setting the individual point opacity is a manual task performed by the chart designer. We present a user-driven model of opacity scaling for scatter plots built from crowd-sourced responses to opacity scaling tasks using several synthetic data distributions, and then test our model on a collection of real-world data sets.

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Cited By

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Strain GStewart AWarren PJay C(2024)Effects of Point Size and Opacity Adjustments in ScatterplotsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642127(1-13)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642127
Liu SMiao HLi ZOlson MPascucci VBremer P(2024)AVA: Towards Autonomous Visualization Agents through Visual Perception‐Driven Decision‐MakingComputer Graphics Forum10.1111/cgf.1509343:3Online publication date: 10-Jun-2024
https://doi.org/10.1111/cgf.15093
Xue YPaetzold PKehlbeck RChen BKwan KWang YDeussen O(2024)Reducing Ambiguities in Line-Based Density Plots by Image-Space ColorizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332714930:1(825-835)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3327149
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Index Terms

Dynamic Opacity Optimization for Scatter Plots
1. Human-centered computing

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Published In

CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

April 2015

4290 pages

ISBN:9781450331456

DOI:10.1145/2702123

General Chairs:
Bo Begole
Huawei, USA
,
Jinwoo Kim
Yonsei University, Korea
,
Program Chairs:
Kori Inkpen
Microsoft Research, USA
,
Woontack Woo
KAIST, Korea

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 April 2015

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Conference

CHI '15

Sponsor:

SIGCHI

CHI '15: CHI Conference on Human Factors in Computing Systems

April 18 - 23, 2015

Seoul, Republic of Korea

Acceptance Rates

CHI '15 Paper Acceptance Rate 486 of 2,120 submissions, 23%;

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

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CHI '25

Sponsor:
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CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

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Strain GStewart AWarren PJay C(2024)Effects of Point Size and Opacity Adjustments in ScatterplotsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642127(1-13)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642127
Liu SMiao HLi ZOlson MPascucci VBremer P(2024)AVA: Towards Autonomous Visualization Agents through Visual Perception‐Driven Decision‐MakingComputer Graphics Forum10.1111/cgf.1509343:3Online publication date: 10-Jun-2024
https://doi.org/10.1111/cgf.15093
Xue YPaetzold PKehlbeck RChen BKwan KWang YDeussen O(2024)Reducing Ambiguities in Line-Based Density Plots by Image-Space ColorizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332714930:1(825-835)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3327149
Yang FMa YHarrison LTompkin JLaidlaw D(2023)How Can Deep Neural Networks Aid Visualization Perception Research? Three Studies on Correlation Judgments in ScatterplotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581111(1-17)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581111
Correll M(2023) Teru Teru Bōzu : Defensive Raincloud Plots Computer Graphics Forum10.1111/cgf.1482642:3(235-246)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14826
Strain GStewart AWarren PJay C(2023)Adjusting Point Size to Facilitate More Accurate Correlation Perception in Scatterplots2023 IEEE Vis X Vision10.1109/VisXVision60716.2023.00006(1-5)Online publication date: 22-Oct-2023
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Quadri GNieves JWiernik BRosen P(2023)Automatic Scatterplot Design Optimization for Clustering IdentificationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.318988329:10(4312-4327)Online publication date: 1-Oct-2023
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Strain GStewart AWarren PJay C(2023)The Effects of Contrast on Correlation Perception in ScatterplotsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2023.103040176:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.ijhcs.2023.103040
Wagner LLimberger DScheibel WDöllner J(2022)Hardware-accelerated Rendering of Web-based 3D Scatter Plots with Projected Density Fields and Embedded ControlsProceedings of the 27th International Conference on 3D Web Technology10.1145/3564533.3564566(1-5)Online publication date: 2-Nov-2022
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Li ZShi RLiu YLong SGuo ZJia SZhang J(2022)Dual Space Coupling Model Guided Overlap-Free ScatterplotIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.3209459(1-11)Online publication date: 2022
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Using Animation to Alleviate Overdraw in Multiclass Scatterplot Matrices

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