Data visualization is very often viewed as an equivalent of statistical representation of data in all its forms. This representation serves effectively certain objectives such as abstraction, reduction, standardization, or legibility, of interest to some disciplines and use cases, namely business, engineering, and science. Numerous tools and programming languages allow to visualize data according to these principles. Other disciplines and areas of knowledge, such as history, literature, art, journalism, or education, are confronted with the need to use the same tools ignoring some fundamental principles of their own disciplines, to program from scratch new visual vocabularies and functionalities, or to use design tools that are disconnected from the data.
As part of my research, I study the needs of the different disciplines and areas of knowledge, based on their own definitions of data and data visualization, the relationship between the two of them, and the user interaction; but I also experiment with transforming the visualizations from one paradigm to another, so that they can be used in interdisciplinary projects, or to open new approaches to data visualization within the disciplines themselves. During this presentation of my early research, I will present the initial description of the paradigms with a visual gallery of examples. And the first ideas of transformation of the visualizations between paradigms.
Wednesday, 19 January 2022
14.00 - 15.00
Online - Webex
If you want to participate, please send an e-mail to email@example.com to receive the link.