The Fundamental Role of Interactive Surfaces & Spaces in Human Sensemaking
In this presentation, we will examine the importance of large interactive surfaces and spaces (ISS) for enabling human sensemaking. If we are to make progress in a big data age, then sensemaking, AI analytics, and other data science activities are paramount tasks. Rapid advancements in the field of ISS offer new opportunities to design, develop, and evaluate large physical spaces, both 2D and 3D, within which humans can sensemake. The design of these spaces leads to a new emphasis on embodiment as an approach to supporting sensemaking activity. The rising field of Immersive Analytics is increasingly investigating such critical design issues.
But why is physical space so important to human sensemaking? How are large physical spaces fundamentally different from traditional displays for sensemaking? How do they help with analytical processes? What is the relationship between display space and computational AI analytics? How should we design large interactive spaces to maximize human+AI sensemaking performance?
In this presentation, we investigate these questions by examining how physical space plays fundamental roles at several levels of sensemaking: embodied visualization, embodied interaction, embodied cognition, embodied computing with AI/ML algorithms, and embodied collaboration. Our synthesis of these roles will illuminate a path forward for future research in ISS for sensemaking.
Dr. Chris North is a Professor of Computer Science at Virginia Tech in Blacksburg, VA, USA. He is Associate Director of the Sanghani Center for AI and Data Analytics (https://sanghani.cs.vt.edu), core member of the Center for Human-Computer Interaction (https://hci.icat.vt.edu), leads the Visual Analytics research group (http://infovis.cs.vt.edu), and was principle architect of the GigaPixel Display Laboratory. There he graduated 20 PhD students, was awarded over $17M in grants, and co-authored over 140 peer-reviewed publications (http://scholar.google.com/citations?user=yBZ7vtkAAAAJ) with h-index=59. As a leader in data science education at Virginia Tech, he founded the Graduate Certificate in Data Analytics and co-organized the Computation Modeling and Data Analytics undergraduate major. He has also served the community as General Co-Chair of IEEE VIS, and as Papers Co-Chair of the IEEE Information Visualization (InfoVis) and IEEE Visual Analytics Science and Technology (VAST) Conferences. His research and education agenda seeks to enable effective human-AI interaction in immersive analytics environments. For over two decades, he has led efforts to design and evaluate usability of large and immersive display spaces for interactive visualization and text analytics in data science.