research-article

An optimization-based approach to dynamic data transformation for smart visualization

Authors:

Michelle. X. ZhouAuthors Info & Claims

IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces

Pages 70 - 79

https://doi.org/10.1145/1378773.1378784

Published: 13 January 2008 Publication History

Abstract

We are building a smart visual dialog system that aids users in investigating large and complex data sets. Given a user's data request, we automate the generation of a visual response that is tailored to the user's context. In this paper, we focus on the problem of data transformation, which is the process of preparing the raw data (e.g., cleaning and scaling) for effective visualization. Specifically, we develop an optimization-based approach to data transformation. Compared to existing approaches, which normally focus on specific transformation techniques, our work addresses how to dynamically determine proper data transformations for a wide variety of visualization situations. As a result, our work offers two unique contributions. First, we provide a general computational framework that can dynamically derive a set of data transformations to help optimize the quality of the target visualization. Second, we provide an extensible, feature-based model to uniformly represent various data transformation operations and visualization quality metrics. Our evaluation shows that our work significantly improves visualization quality and helps users to better perform their tasks.

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Cited By

Wu ZChen WMa YXu TYan FLv LQian ZXia J(2022)Explainable data transformation recommendation for automatic visualization面向自动可视化的可解释数据变换推荐Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.220040924:7(1007-1027)Online publication date: 23-Dec-2022
https://doi.org/10.1631/FITEE.2200409
Chen QSun FXu XChen ZWang JCao N(2022)VizLinter: A Linter and Fixer Framework for Data VisualizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311480428:1(206-216)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3114804
Yang HLi YZhou M(2014)Understand users’ comprehension and preferences for composing information visualizationsACM Transactions on Computer-Human Interaction10.1145/254128821:1(1-30)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1145/2541288
Show More Cited By

Index Terms

An optimization-based approach to dynamic data transformation for smart visualization
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces

January 2008

458 pages

ISBN:9781595939876

DOI:10.1145/1378773

General Chair:
Steffen Staab
Universitat Koblenz-Landau, Germany

Copyright © 2008 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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SIGAI: ACM Special Interest Group on Artificial Intelligence
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
AAAI: Association for the Advancement of Artifical Intelligence

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Association for Computing Machinery

New York, NY, United States

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Published: 13 January 2008

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IUI08

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IUI08: 13th International Conference on Intelligent User Interfaces

January 13 - 16, 2008

Gran Canaria, Spain

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Wu ZChen WMa YXu TYan FLv LQian ZXia J(2022)Explainable data transformation recommendation for automatic visualization面向自动可视化的可解释数据变换推荐Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.220040924:7(1007-1027)Online publication date: 23-Dec-2022
https://doi.org/10.1631/FITEE.2200409
Chen QSun FXu XChen ZWang JCao N(2022)VizLinter: A Linter and Fixer Framework for Data VisualizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311480428:1(206-216)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3114804
Yang HLi YZhou M(2014)Understand users’ comprehension and preferences for composing information visualizationsACM Transactions on Computer-Human Interaction10.1145/254128821:1(1-30)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1145/2541288
Botega LBerti CAraújo RAlmeida Neris V(2014)A Model to Promote Interaction between Humans and Data Fusion Intelligence to Enhance Situational Awareness16th International Conference on Human-Computer Interaction. Theories, Methods, and Tools - Volume 851010.1007/978-3-319-07233-3_37(399-410)Online publication date: 22-Jun-2014
https://dl.acm.org/doi/10.1007/978-3-319-07233-3_37
Crnovrsanin TLiao IWuy YMa K(2011)Visual recommendations for network navigationProceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization10.1111/j.1467-8659.2011.01957.x(1081-1090)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1111/j.1467-8659.2011.01957.x
Kasik DEbert DLebanon GPark HPottenger W(2009)Data transformations and representations for computation and visualizationInformation Visualization10.1057/ivs.2009.278:4(275-285)Online publication date: 1-Dec-2009
https://dl.acm.org/doi/10.1057/ivs.2009.27

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