Scalable Data Visualization Systems for Broad Audiences

Two recent trends have brought opportunities and challenges in data visualization research. First, data are increasing in size and complexity across problem domains, demanding interpretable and performant visualization systems. In addition, more diverse users, such as scientists, analysts, journalists, and designers, need to work with data as an integral part of their jobs. They require visualization tools that offer low barriers of entry without sacrificing analytic or expressive power. I will present research projects that address these two challenges from a human-centered perspective. To support exploratory analysis of large multivariate and event sequence datasets, I use perceptual and interactive scalability as the driving principle to propose new interaction techniques. To make visualization tools accessible to a broader range of users, novel visualization process models can power the design and construction of natural language interfaces and visualization authoring systems.