// Invited Speakers
// Keynote: Paul A. Navrátil
Let Me Tell You a Story: Enabling Effective and Scalable Communication of Scientific Insights
From time before history, humans have used imagery to shape ideas and communicate important concepts to their communities. Visualization harnesses this fundamental mode through transforming raw data into images that present actionable insights and discoveries to advance human understanding. Yet, even as techniques in scivis, infovis, and vis analytics progress, the effective application of these techniques to solve analysis problems remains very much an art plied by specialized visualization experts who understand both the tools and how to best wield them. As our data sources multiply, and the commensurate need for analysis of those data expand, relying solely on vis experts will not scale. The visualization community will need to provide simple, reliable, and expressive tools so that domain scientists can generate high-quality visualizations sooner in their discovery pipelines, challenging visualization experts to expand the state of the art in translating research to practice. This talk will present challenges to this vision and potential transformative solutions in the context of work at the Texas Advanced Computing Center and peer institutions world-wide.
// Short Bio
Dr. Paul A. Navrátil is a Research Scientist and Director of Visualization at the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. He is an expert in high-performance visualization technologies, accelerator-based computing and advanced rendering techniques. His research seeks to improve analytic capacity and insight communication across scientific workflows, including efficient algorithms for large-scale parallel visualization and data analysis (VDA) and innovative design for immersive VDA systems. Dr. Navrátil’s recent work includes algorithms for large-scale distributed-memory ray tracing, including the GraviT and Galaxy ray tracing frameworks, which enable photo-realistic rendering of the largest datasets produced on supercomputers today. His team provisions TACC’s two visualization labs and the remote visual analytic environments on TACC’s advanced computing systems, including the US NSF leadership-class systems Stampede2 and Frontera. Dr. Navrátil’s work has been featured in numerous venues, both nationally and internationally, including the New York Times, Discover, and PBS News Hour. He holds BS, MS and Ph.D. degrees in Computer Science and a BA degree in Plan II Interdisciplinary Honors from the University of Texas at Austin.
// Capstone: Jeffrey Heer
Visualization is Not Enough
We are witnessing both increased application and public skepticism of data-driven methods for decision making and automation. Within this regime, data visualization — as a technology — seems well-poised to provide valuable insight and oversight. Though arguably a *necessary* component in the appropriate use of data, visualization by itself is far from *sufficient*. Data visualization — as a community of practice — sits at the confluence of many “source” disciplines, including cartography, computer science, graphic design, psychology, and statistics. The practice of principled interdisciplinary thinking is perhaps our greatest asset, suggesting avenues for our community to have outsized, beneficial impact in the world. In this talk I will consider the obvious yet potentially contrarian view that *visualization is not enough* — and why this realization is liberating for both research and practice. I will point to vanguards and future prospects in “visualization” research that I believe exemplify real-world relevance and require rich intellectual integration: accessibility, interactive visualization systems, reasoning under uncertainty, and interactions with machine learning models. One guiding heuristic we might consider is the degree to which we not only benefit from, but successfully contribute back to, the adjacent disciplines that fuel our endeavors. Our community is uniquely positioned to contribute to issues of critical importance to society. Let’s consider how we should rise to the challenge!
Jeffrey Heers’ Capstone “Visualization is Not Enough” slides are available here.
// Short Bio
Jeffrey Heer is a Professor of Computer Science & Engineering at the University of Washington, where he directs the Interactive Data Lab and conducts research on data visualization, human-computer interaction and social computing. The visualization tools developed by Jeff and his collaborators (Vega, D3.js, Protovis, Prefuse) are used by researchers, companies, and data enthusiasts around the world. Jeff’s research papers have received awards at the premier venues in Human-Computer Interaction and Visualization (ACM CHI, UIST, CSCW, IEEE InfoVis, VAST, EuroVis). Honors include MIT Technology Review’s TR35 (2009), a Sloan Fellowship (2012), an Allen Distinguished Investigator Award (2014), a Moore Foundation Data-Driven Discovery Investigator Award (2014), the ACM Grace Murray Hopper Award (2016), and the IEEE Visualization Technical Achievement Award (2017). Jeff received B.S., M.S., and Ph.D. degrees in Computer Science from UC Berkeley, whom he then “betrayed” to join the Stanford faculty (2009–2013). He is also a co-founder of Trifacta, a provider of interactive tools for scalable data transformation.