Insights From Experiments With Rigor in an EvoBio Design Study
This work addresses the need for more rigorous and interpretivist approaches in visualization design studies, offering practical tools and methods for researchers in the visualization community, though it is incremental in building on existing frameworks.
The researchers tackled the challenge of enhancing rigor in visualization design studies by experimenting with three criteria during a year-long collaboration with evolutionary biologists, resulting in two novel visualization techniques for multivariate phylogenetic datasets, three methodological recommendations, and two writing devices for reporting interpretivist design studies.
Design study is an established approach of conducting problem-driven visualization research. The academic visualizationcommunity has produced a large body of work for reporting on design studies, informed by a handful of theoretical frameworks, andapplied to a broad range of application areas. The result is an abundance of reported insights into visualization design, with anemphasis on novel visualization techniques and systems as the primary contribution of these studies. In recent work we proposeda new, interpretivist perspective on design study and six companion criteria for rigor that highlight the opportunities for researchersto contribute knowledge that extends beyond visualization idioms and software. In this work we conducted a year-long collaborationwith evolutionary biologists to develop an interactive tool for visual exploration of multivariate datasets and phylogenetic trees. Duringthis design study we experimented with methods to support three of the rigor criteria:ABUNDANT,REFLEXIVE, andTRANSPARENT. As aresult we contribute two novel visualization techniques for the analysis of multivariate phylogenetic datasets, three methodologicalrecommendations for conducting design studies drawn from reflections over our process of experimentation, and two writing devices forreporting interpretivist design study. We offer this work as an example for implementing the rigor criteria to produce a diverse range ofknowledge contributions.