research-article

The importance of tracing data through the visualization pipeline

Authors:

Aritra Dasgupta,

Robert KosaraAuthors Info & Claims

BELIV '12: Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization

Article No.: 9, Pages 1 - 5

https://doi.org/10.1145/2442576.2442585

Published: 14 October 2012 Publication History

Abstract

Visualization research focuses either on the transformation steps necessary to create a visualization from data, or on the perception of structures after they have been shown on the screen. We argue that an end-to-end approach is necessary that tracks the data all the way through the required steps, and provides ways of measuring the impact of any of the transformations. By feeding that information back into the pipeline, visualization systems will be able to adapt the display to the data being shown, the parameters of the output device, and even the user.

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Cited By

Smelser KMiller JKobourov S(2024)“Normalized Stress” is Not Normalized: How to Interpret Stress Correctly2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)10.1109/BELIV64461.2024.00010(41-50)Online publication date: 14-Oct-2024
https://doi.org/10.1109/BELIV64461.2024.00010
Cordero-Machuca DLima JOrellana M(2022)Improving with Metaheuristics the Item Selection in Parallel Coordinates PlotInformation and Communication Technologies10.1007/978-3-031-18272-3_13(186-200)Online publication date: 5-Oct-2022
https://doi.org/10.1007/978-3-031-18272-3_13
Heine C(2021)Towards Modeling Visualization Processes as Dynamic Bayesian NetworksIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.303039527:2(1000-1010)Online publication date: Feb-2021
https://doi.org/10.1109/TVCG.2020.3030395
Show More Cited By

Index Terms

The importance of tracing data through the visualization pipeline
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Visual analytics

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BELIV '12: Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization

October 2012

94 pages

ISBN:9781450317917

DOI:10.1145/2442576

Copyright © 2012 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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Microsoft Research: Microsoft Research

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New York, NY, United States

Publication History

Published: 14 October 2012

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BELIV '12

Sponsor:

Microsoft Research

BELIV '12: Beyond Time and Errors - Novel Evaluation Methods for Visualization

October 14 - 15, 2012

Washington, Seattle, USA

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Overall Acceptance Rate 45 of 64 submissions, 70%

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Cited By

Smelser KMiller JKobourov S(2024)“Normalized Stress” is Not Normalized: How to Interpret Stress Correctly2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)10.1109/BELIV64461.2024.00010(41-50)Online publication date: 14-Oct-2024
https://doi.org/10.1109/BELIV64461.2024.00010
Cordero-Machuca DLima JOrellana M(2022)Improving with Metaheuristics the Item Selection in Parallel Coordinates PlotInformation and Communication Technologies10.1007/978-3-031-18272-3_13(186-200)Online publication date: 5-Oct-2022
https://doi.org/10.1007/978-3-031-18272-3_13
Heine C(2021)Towards Modeling Visualization Processes as Dynamic Bayesian NetworksIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.303039527:2(1000-1010)Online publication date: Feb-2021
https://doi.org/10.1109/TVCG.2020.3030395
Reynoso MDivan M(2020)Applying Data Visualization Guideline on Forest Fires in Argentina2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)10.1109/Confluence47617.2020.9058174(617-622)Online publication date: Jan-2020
https://doi.org/10.1109/Confluence47617.2020.9058174
Dasgupta ALee JWilson RLafrance RCramer NCook KPayne S(2017)Familiarity Vs TrustIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2016.259854423:1(271-280)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1109/TVCG.2016.2598544
Schulz HAngelini MSantucci GSchumann H(2016)An Enhanced Visualization Process Model for Incremental VisualizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2015.246235622:7(1830-1842)Online publication date: 1-Jul-2016
https://doi.org/10.1109/TVCG.2015.2462356
Li XZhang XFu WLiu X(2015)E-Learning with visual analytics2015 IEEE Conference on e-Learning, e-Management and e-Services (IC3e)10.1109/IC3e.2015.7403499(125-130)Online publication date: Aug-2015
https://doi.org/10.1109/IC3e.2015.7403499

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