Title: Visual Explorations of Objective Data: The Meaning of Unexpected Results
Stream: Design for Society
Presentation Type: Oral Presentation
Authors:
Rui Costa, Universidade de Aveiro, Portugal
Nina Costa, Universidade de Aveiro, Portugal
Afonso Borges, Universidade de Aveiro, Portugal
Vasco Branco, Universidade de Aveiro, Portugal
António Modesto, Universidade do Porto, Portugal
Raul Cunca, Universidade de Lisboa, Portugal
Ana Catarina Silva, Instituto Politécnico do Cávado e do Ave, Portugal
Marlene Ferreira Ribeiro, University of Aveiro, Portugal
Abstract:
Previous work developed within project DesignObs. - For a Design Observatory in Portugal, focused on producing data about the different vectors of the Portuguese design ecosystem (e.g. education, research, companies) and addressing its literacy. The collection of multiple evidence and the production of design-focused databases, available for anyone who wants to interpret them, was one of the main goals of the project — to create information that could support strategic decision-making in the area of design.
One of the main problems of science lies in the difficulty in transferring the knowledge generated to the social and economic fabric, severely limiting its expected impact. After producing the databases, 70 students design students and 9 professionals were invited to manipulate and interpret data, to produce visual and, sometimes, provocative communications about this data. The participation of young and experienced designers resulted in 41 posters that combine multiple approaches coming from the arts, illustration, cartoon, graphic design amongst others design-related disciplines. In this paper, we aim to address the nature of these visual representations, posters; to reflect on the limits of communication on research contexts and emphasize the pertinence of visually exploring objective data through multiple perspectives, as if interviews carried out in a natural language, eminently visual. They are, in this sense, like illustrations without the mandatory requirement of a unique meaning or explanation — impressions — which tell us as much about the data as about the authors, by merging content and container, message and author.
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