Important Future Research Areas for Information Visualization (and Visual Analytics)

Abstract

In looking at current papers in Information Visualization, one does not see many striking new topics (there are some). Many papers describe an application of visualization. Most others describe either an incremental change in a technique to a classic problem or an improved algorithm reducing computational complexity. There are papers on user interfaces, on interaction, on usability, on representation, on aesthetics, on graph drawing algorithms. There are papers on a wide variety of interdisciplinary topics. There are papers on a new discipline's role in visualization. Finally there are papers describing something of relevance to the author but not to the field.

What are the exciting problems to be solved? This is an important question for a field to identify. Self-introspection is a necessity for a field to continue to grow.

There have been grand challenge panels, papers, and pamphlets (in the 70s). I, as a youngster (I am still young), participated in several of these as far back as 1992 (IEEE Conference panel on “Grand Challenge Problems in Visualization Software”). These are valuable. However in my view many of these are driven by the timely political nature of funding (see for example the excellent "Illuminating the Path: Research and Development Agenda for Visual Analytics").

In this talk I will present five areas which are extremely important for our field and identify key problems in these five areas. Five areas which can provide for rapid new growth and which need researchers. And I will identify one in particular which is my favorite.

These areas are:

1. Measuring Information Visualization (information, accuracy, uncertainty, insight)
2. High-dimensional Visualization (hundreds and thousands of variables)
3. Real Time Massive Data Set Visualization (sensors, networks)
4. Interactive Collaborative Information Visualization (Web 5.0)
5. Modeling Data Exploration (where is the user going?)

I will suggest a number of key problems, hints to some solutions, possible impact and future scenarios.

Bio:

Georges Grinstein is Professor of Computer Science at the University of Massachusetts Lowell, head of its Bioinformatics and Cheminformatics Program, Co-director of its Institute for Visualization and Perception Research, and of its Center for Biomolecular and Medical Informatics. He received his Ph.D. in Mathematics from the University of Rochester in 1978.

His work is broad and interdisciplinary, ranging from the perceptual foundations of visualization to techniques for very high-dimensional data visualization to a theory of visualization, with the emphasis on the modeling, visualization, and analysis of complex information systems.

He has over 30 years in academia with extensive private consulting, over 100 research grants, products in use nationally and internationally, several patents, numerous publications in journals and conferences, a new book on interactive data visualization, founded several companies, and has been the organizer or chair of national and international conferences and workshops in Computer Graphics, in Visualization, and in Data Mining. He has mentored over 25 doctoral students and hundreds of graduate students. He has been on the editorial boards of several journals in Computer Graphics and Data Mining, a member of ANSI and ISO, a NATO Expert, and a technology consultant for various public agencies.

For the last seven years he has co-chaired the InfoVis and VAST contests in visual analytics leading to new research areas; has taught Radical Design, a course teaching students how to innovate with "radical" new products instead of evolutionary ones; is a member of the new Homeland Security Center CCICADA; and is co-director of the new Open Indicators Consortium that has developing a web-based interactive collaborative visualization system.