Communicating qualitative uncertainty in data visualization Two cases from within the digital humanities

  • Panagiotidou G
  • Moere A
N/ACitations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

Qualitative uncertainty refers to the implicit and underlying issues that are imbued in data, such as the circumstances of its collection, its storage or even biases and assumptions made by its authors. Although such uncertainty can jeopardize the validity of the data analysis, it is often overlooked in visualizations, due to it being indirect and non-quantifiable. In this paper we present two case studies within the digital humanities in which we examined how to integrate uncertainty in our visualization designs. Using these cases as a starting point we propose four considerations for data visualization research in relation to indirect, qualitative uncertainty: (1) we suggest that uncertainty in visualization should be examined within its socio-technological context, (2) we propose the use of interaction design patterns to design for it, (3) we argue for more attention to be paid to the data generation process in the humanities, and (4) we call for the further development of participatory activities specifically catered for understanding qualitative uncertainties. While our findings are grounded in the humanities, we believe that these considerations can be beneficial for other settings where indirect uncertainty plays an equally prevalent role. © John Benjamins Publishing Company.

Cite

CITATION STYLE

APA

Panagiotidou, G., & Moere, A. V. (2022). Communicating qualitative uncertainty in data visualization Two cases from within the digital humanities. Information Design Journal, 27(1), 52–63. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147231166&doi=10.1075%2fidj.22014.pan&partnerID=40&md5=18455174a677e81a4476391e4e9100fc

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free