Enthusiast versus Antagonist: Exploring the perceptions of data experts on the visualisation of uncertainty

Autor: Joel Pinney, Fiona Carroll, Esyin Chew
Rok vydání: 2022
Předmět:
Zdroj: Human Interaction & Emerging Technologies (IHIET-AI 2022): Artificial Intelligence & Future Applications.
ISSN: 2771-0718
DOI: 10.54941/ahfe100893
Popis: Despite the copious number of reasons to visualise uncertainty in visualisations, there is still a reluctance to actively represent uncertainties. This paper explores the perceptions of data experts considering uncertainty visualisation and their reasoning behind lacking engagement. By documenting a series of interviews with data experts, the authors uncover the perceptions and constraints faced when contemplating uncertainty visualisation. Through several industries, the authors reveal numerous perceived benefits of uncertainty visualisation but also the strong influence end-users have on the decision to incorporate the additional information. Finally, the paper reflects on a lack of experience but also the commitment from the data experts to the use of aesthetics in developing intuitive uncertainty visualisations. Whilst also highlighting their perceived benefits around what the aesthetic could bring to both visualisation development and uncertainty visualisation design. The study documented in this paper feeds into a larger body of research on aesthetic uncertainty visualisation.
Databáze: OpenAIRE