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Measures in Visualization Space

F. Bolte and S. Bruckner

Abstract

Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of individual visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.

F. Bolte and S. Bruckner, "Measures in Visualization Space," in Foundations of Data Visualization, Springer, 2020.
[BibTeX]

Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of individual visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.
@incollection {Bolte-2019-MVS,
author = {Bolte, Fabian and Bruckner, Stefan},
title = {Measures in Visualization Space},
booktitle = {Foundations of Data Visualization},
chapter = {3},
publisher = {Springer},
year = {2020},
pdf = {pdfs/Bolte-2019-MVS.pdf},
images = {images/Bolte-2019-MVS.png},
thumbnails = {images/Bolte-2019-MVS.png},
abstract = {Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of individual visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.},
note = {This is a preprint of a chapter for a planned book that was initiated by participants of the Dagstuhl Seminar 18041 ("Foundations of Data Visualization") and that is expected to be published by Springer. The final book chapter will differ from this preprint.},
url = {https://arxiv.org/abs/1909.05295},
project = "MetaVis"
}
projectidMetaVisprojectid

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