Quantitative Ecologist, Minnesota Aquatic Invasive Species Research Center
Often, the culmination—and distillation—of an entire project ends up being one or more graphs. Yet despite that central role, we seem to not discuss graph design as deeply as topics like study design or methodology. In this seminar, Alex, MAISRC’s quantitative ecologist, explores how to bring accessibility, intentionality, and evidence-based practice to scientific graph design. Using a single graph as a case study, he models how to evaluate and improve a graph using principles from data visualization, psychology, and Universal Design. Topics include appropriately defining a graph’s purpose, weeding elements to reduce complexity, designing for how people actually see and read, and bolstering captions so graphs can stand alone. Rather than prescribe a “correct” method, Alex encourages the audience to develop their own, more thoughtful and deliberate design process to maximize research impact.
Alex Bajcz is the staff quantitative ecologist for the Minnesota Aquatic Invasive Species Research Center (MAISRC) at the University of Minnesota, where he supports the center's research teams in all things "data," including study design, data collection, cleaning, and storage, analysis, visualization, and computation. He's also the lead developer of MAISRC's suite of R Shiny web applications. With a background in science pedagogy, Alex aims to create tools and resources that make adopting data science best practices easier, especially for graduate students and practitioners. In his free time, Alex enjoys cooking, video and board games, crosswords, and trivia.