Seeing what is not shown
Open Access
- 7 November 2022
- journal article
- Published by John Benjamins Publishing Company in Identifying Information and Tenor in Texts
- Vol. 27 (1), 64-75
- https://doi.org/10.1075/idj.22006.hen
Abstract
Critical studies of data visualization often highlight how the reductive nature of visualization methods excludes data limitations and qualities that are crucial to understanding those data. This case study explores how a data visualization could express contingent, situated, and contextual facets of data. We examine how such data limitations might be surfaced and represented within visualizations through an interplay between the critique of an existing data visualization and the development of alternative designs. Based on a case study of urban tree data, we interrogate data limitations in relation to four different types of missingness: Incompleteness, Emptiness, Absence, and Nothingness. Our study enables reflections on how data limitations can be investigated using visualizations and considers the development of a critical visualization practice.Keywords
This publication has 27 references indexed in Scilit:
- Exploring Qualitative Displays and InterfacesPublished by Association for Computing Machinery (ACM) ,2017
- A place for Big Data: Close and distant readings of accessions data from the Arnold ArboretumBig Data & Society, 2016
- The work that visualisation conventions doInformation, Communication & Society, 2016
- ggplot2Published by Springer Science and Business Media LLC ,2016
- Critical visualization: a case for rethinking how we visualize risk and securityJournal of Cybersecurity, 2015
- Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendationsCartography and Geographic Information Science, 2015
- The real-time city? Big data and smart urbanismGeoJournal, 2013
- Critical InfoVisPublished by Association for Computing Machinery (ACM) ,2013
- Revealing Uncertainty for Information VisualizationInformation Visualization, 2009
- State of the Art: Coordinated & Multiple Views in Exploratory VisualizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007