This project investigates making visual analysis of data more effectively by using time-tested methods of visual artists to investigate, reframe and generally make sense of their world. Imagine if data-intensive computing could be a more innately human and creative process, like sculpting (visual, tangible, active, physical).
Finding inspiration in nature, combining disparate objects in new ways, understanding through hands-on experimenting and creating – these are the time-tested methods of visual artists; for centuries these methods have helped us investigate, reframe, and ultimately make sense of our world. In the next ten years, we know that major advances in science will increasingly come from a new "data exploration" paradigm of discovery, but how will humans move from data to actionable insight in this new paradigm? Imagine if data-intensive computing could be a more innately human and creative process, like sculpting (visual, tangible, active, physical).
Interactive exploratory visualization has advanced significantly in recent years, motivated in large part by the high potential impact of a more powerful approach to analyzing these data that aligns with human visual processing. Yet, major challenges remain in:
These open challenges are often most pronounced when working with 3D scientific datasets (e.g., brain structure and function, ocean currents and atmospheric changes across the globe). Therefore, we ask, what if the processes of creating and using visualizations were more like the most creative 3D task that humans engage in – rather than programming visualizations, what if we could sculpt them? Likewise, if we could look at, touch, and experience 3D datasets with the same physical acuity that we use to inspect a cast bronze sculpture, then we could understand complex spatial relationships in the wiring of the brain in ways that are even more intuitive than current virtual reality (VR) displays. Finally, if we could visualize and explore data in ways that do not require graduate-level programming skill and instead use rapid iterative experimentation with hands-on interfaces, then science would become radically more accessible to many members of society.
We anticipate a number of significant advances:
The new tools and techniques developed will be made available via open source. Results will be disseminated on the project webpage and via scientific publications. Broader impacts will come in part from museum exhibits that draw upon the Co-PIs' dual background in art and science.
Dan Keefe (PI) University of Minnesota
Francesca Samsel (Co-PI) Research Scientist, University of Texas at Austin
Greg Abram Research Scientist, University of Texas at Austin
Annie Barnes University of Texas at Austin
National Science Foundation, Information Integration and Informatics – Cyber-Human Systems