# Measures in Visualization Space

arXiv: https://arxiv.org/abs/1909.05295 · HTML: https://mlsanity.com/paper/1909.05295/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2019.

## Built on by (most cited first, 2 of 2)

- [The Truth, the Whole Truth, and Nothing but the Truth: Automatic Visualization Evaluation from Reconstruction Quality](https://mlsanity.com/paper/2603.16873/) (2026)
- [Semantic Snapping for Guided Multi-View Visualization Design](https://mlsanity.com/paper/2109.08384/) (2021)

## Abstract (arXiv)

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.