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Visual quality metrics

Published: 23 May 2006 Publication History

Abstract

The definition and usage of quality metrics for Information Visualization techniques is still an immature field. Several proposals are available but a common view and understanding of this issue is still missing. This paper attempts a first step toward a visual quality metrics systematization, providing a general classification of both metrics and usage purposes. Moreover, the paper explores a quite neglected class of visual quality metrics, namely Feature Preservation Metrics, that allow for evaluating and improving in a novel way the effectiveness of basic Infovis techniques.

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cover image ACM Other conferences
BELIV '06: Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization
May 2006
89 pages
ISBN:1595935622
DOI:10.1145/1168149
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: 23 May 2006

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  • (2022)Effectiveness Error: Measuring and Improving RadViz Visual EffectivenessIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310487928:12(4770-4786)Online publication date: 1-Dec-2022
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