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Lookup NU author(s): Dr Sara Johansson Fernstad
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2024.
For re-use rights please refer to the publisher's terms and conditions.
The use of good-quality data to inform decision making is entirely dependent on robust processes to ensure it is fit for purpose. Such processes vary between organisations, and between those tasked with designing and following them. In this paper we report on a survey of 53 data analysts from many industry sectors, 24 of whom also participated in in-depth interviews, about computational and visual methods for characterizing data and investigating data quality. The paper makes contributions in two key areas. The first is to data science fundamentals, because our lists of data profiling tasks and visualization techniques are more comprehensive than those published elsewhere. The second concerns the application question “what does good profiling look like to those who routinely perform it?,” which we answer by highlighting the diversity of profiling tasks, unusual practice and exemplars of visualization, and recommendations about formalizing processes and creating rulebooks.
Author(s): Ruddle RA, Cheshire J, Johansson Fernstad S
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Visualization and Computer Graphics
Year: 2024
Volume: 30
Issue: 7
Pages: 3400-3412
Print publication date: 01/07/2024
Online publication date: 06/01/2023
Acceptance date: 20/12/2022
Date deposited: 28/02/2023
ISSN (electronic): 1941-0506
Publisher: IEEE
URL: https://doi.org/10.1109/TVCG.2023.3234337
DOI: 10.1109/TVCG.2023.3234337
ePrints DOI: 10.57711/fqms-wx43
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