PhD Defense: Media for Data-Driven Storytelling: Evidence, Taxonomy, and guidelines
The emerging practice of data-driven storytelling is framing data using familiar mechanisms such as slideshows, videos, and comics to make even highly complex phenomena understandable, but current data stories are still not utilizing the full potential of the storytelling domain. One reason for this is that current data-driven storytelling practice does not leverage the full repertoire of media that can be used for storytelling, such as oral speech, e-learning, and video games. In this paper, we propose a taxonomy focused specifically on media types for the purpose of widening the purview of data-driven storytelling simply by putting more tools in the hands of designers.Using our taxonomy as a generative tool, we also explored two novel storytelling mechanisms, including for live-streaming (DataTV) and textual reports that dynamically incorporate visual representations (DataComic). We have collected examples for data-driven storytelling by finding, reviewing, and classifying about one hundred evidences. Meanwhile, we widened the genres we explored to fill the gaps of the literature. We also finished evaluation for DataComic and DataTV with user studies and expert review.
Chair: Dr. Niklas Elmquist Dean's rep: Dr. Alan Sussman Members: Dr. Hector Corrada Bravo Dr. Matthias Zwicker Dr. Ben Bederson