Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations

Abstract

While previous work exists on how to conduct and disseminate insights from problem-driven visualization projects and design studies, the literature does not address how to accomplish these goals in transdisciplinary teams in ways that advance all disciplines involved. In this paper we introduce and define a new methodological paradigm we call design by immersion, which provides an alternative perspective on problem-driven visualization work. Design by immersion embeds transdisciplinary experiences at the center of the visualization process by having visualization researchers participate in the work of the target domain (or domain experts participate in visualization research). Based on our own combined experiences of working on cross-disciplinary, problemdriven visualization projects, we present six case studies that expose the opportunities that design by immersion enables, including (1) exploring new domain-inspired visualization design spaces, (2) enriching domain understanding through personal experiences, and (3) building strong transdisciplinary relationships. Furthermore, we illustrate how the process of design by immersion opens up a diverse set of design activities that can be combined in different ways depending on the type of collaboration, project, and goals. Finally, we discuss the challenges and potential pitfalls of design by immersion.

Professional Differences: A Comparative Study of Visualization Task Performance and Spatial Ability Across Disciplines

“…While domain-focused participatory methodologies imply that an individual's professional discipline can impact the right design for a given domain [28,60], previous visualization work [15,44,73] has demonstrated that spatial ability has a complex influence on visualization use and preference. For example, Chen & Czerwinski [15] found that people's strategies for exploring visualized data change as a function of their spatial abilities.…”

“…The literature on visualization design (e.g., [26,28,36,49,52,60,62]) emphasizes exploring different domains to inform design processes, asserting that domains might differ in their data, processes and challenges, but not in terms of the cognitive traits of their constituent members. For example, Munzner's Nested Model [52] identifies key threats to the visualization design process and strategies to mitigate these threats.…”

Implicit Error, Uncertainty and Confidence in Visualization: An Archaeological Case Study

“…We believe this trust and lack of criticality partially originates from estimating the perceived effort that is required from the visualization developer to recognize and then conscientiously account for implicit errors in the visualization. This effort not only testifies to the developer's commitment to engage in a transdisciplinary way [50], it also shows respect to the idiosyncrasies and mannerisms of the targeted domain. The reluctance to embrace visual analytical tools in the humanities is now well documented [31], [44] and is commonly attributed to visualization's reductionist handling of information that does not comply with the practices and mental models in the humanities.…”

“…During a one-year 'design by immersion' [50] collaboration, the first author investigated how these archaeologists collected, documented and represented their data and cautiously made interpretations. In practice, the first author worked on the project premises on a weekly basis, conducted preliminary workshops with archaeologists, as well as accompanied them during their field-work for two weeks.…”

An Interdisciplinary Model for Graphical Representation

“…In the field of graphical representation, interdisciplinary models have been proposed to cope with the limitations of both previous data-driven and problemdriven models. For instance, Hall et al [20] proposed a trans-disciplinary model which allow the experts in a particular domain to be supported by visualization experts. Their work is very interesting as the interaction between experts with skills in different domains could greatly influence the production of meaningful graphical representations to display cues for scientific findings.…”