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Lookup NU author(s): Dr Sara Fernstad
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2022.
For re-use rights please refer to the publisher's terms and conditions.
This paper contributes a novel visualization method, Missingness Glyph, for analysis and exploration of missing values in data. Missing values are a common challenge in most data generating domains and may cause a range of analysis issues. Missingness in data may indicate potential problems in data collection and pre-processing, or highlight important data characteristics. While the development and improvement of statistical methods for dealing with missing data is a research area in its own right, mainly focussing on replacing missing values with estimated values, considerably less focus has been put on visualization of missing values. Nonetheless, visualization and explorative analysis has great potential to support understanding of missingness in data, and to enable gaining of novel insights into patterns of missingness in a way that statistical methods are unable to. The Missingness Glyph supports identification of relevant missingness patterns in data, and is evaluated and compared to two other visualization methods in context of the missingness patterns. The results are promising and confirms that the Missingness Glyph in several cases perform better than the alternative visualization methods.
Author(s): Johansson Fernstad S, Johansson J
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Visualization and Computer Graphics
Print publication date: 01/10/2022
Online publication date: 10/03/2021
Acceptance date: 02/04/2018
Date deposited: 25/11/2020
ISSN (print): 1077-2626
ISSN (electronic): 1941-0506
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