Prototyping Interactive and Exploratory Visualizations for Interdisciplinary Dialogues

The visualization of interdisciplinary dialogues between design faculties and practitioners

Eugene Park
Associate Professor
University of Minnesota

Visualization of archives is a perennial challenge in the field of design that offers unique opportunities in storytelling in the context of big data. Recognizing the importance of data-driven experiences, this presentation will highlight the creative and educational opportunities as well as the challenges involving the visualization of interdisciplinary dialogues between design faculties and practitioners held over Zoom. By aggregating voice and chat transcripts into unified datasets, it becomes possible to transform them into a series of graphics that visualizes how these interdisciplinary discussions evolved across various topics.

Aided by Python scripts, the data was prepared and analyzed by design students who attended the zoom meetings and rewatched the video recordings. Instead of relying on unsupervised machine learning techniques, students discussed amongst themselves and determined the word groups for each Zoom session, which was the basis of visualizing the evolution of discussion topics over time. The intention behind this process was not to establish an efficient and scalable data pipeline, but to create a learning experience for students to disseminate what was discussed among design faculty and practitioners and become involved in the visualization process.

The outcomes of this project revealed how visualizing interdisciplinary discussions can unveil narratives and insights that otherwise might have been missed in other modalities. By observing how topics evolved over time, it was possible to see the collective areas of expertise of the dialogue participants as well as their knowledge gaps. Ultimately, this project raises questions on the assumptions behind data visualization outcomes and processes. What are the limitations of visualizations for topic modeling? How can animation and interactivity affect the experience of data-driven narratives? And how can students and algorithms work together to promote learning experiences? These are some of the major questions that will be explored through this presentation and subsequent discussion.