Multivariate graphs are an important data type in many high-impact application areas. Yet we know little about the underlying principles of how to effectively visualize them. Despite the plethora of techniques and methods for visualizing graphs, much of this work breaks down when attempting to visualize more than one or two additional attributes — there are simply not enough visual channels to succinctly show all aspects of a rich, complex multivariate graph. Compounding this challenge is the large design space of possible encodings, making it difficult for visualization practitioners to design effective visualizations of multivariate graphs using a top-down, problem-agnostic approach. This project will establish the first set of validated, foundational principles for visualizing multivariate graphs using a structured, methodological research approach. Several target application areas will drive the investigations using a design study approach. These areas were chosen to represent a wide spectrum of possible applications in which multivariate graphs play a central role, thus fostering generalizable results.
Assistant Professor, School of Computing, University of Utah
Nina McCurdy, PhD student
Sean McKenna, PhD student
Josh Dawson, MS student
The rod-cone crossover connectome of mammalian bipolar cells. J. Scott Lauritzen, Crystal Sigulinsky, James Anderson, Noah Nelson, Daniel Emrich, Christopher Rapp, Nicholas McCarthy, Michael Kalloniatis, Ethan Kerzner, Miriah Meyer, Bryan Jones, Robert Marc. Journal of Comparative Neurology, accepted.
Action Design Research for Visualization Design. Nina McCurdy, Jason Dykes, Miriah Meyer. Proceedings of the Workshop on BEyond time and errors: novel evaLuation methods for Information Visualization (BELIV), IEEE VisWeek 2016, accepted.
Poemage: Visualizing the Sonic Topology of a Poem. Nina McCurdy, Julie Lein, Katharine Coles, Miriah Meyer. IEEE Transactions on Visualization and Computer Graphics (Proceedings of InfoVis 2015), 22(1):439-448, 2016.
Each fall we teach a class on the fundamental concepts of visualization in the School of Computing at the University of Utah. This course is a mix of undergraduate and graduate students. The syllabus, lecture materials, and readings can be found on the course website.
We have conducted a number of events to teach high school girls about visualization and computer science. Through an annual collaboration with local high schools, we give short talks to girls about the power of visualization, and answer questions about being a computer scientist. We are also involved with the annual NCWIT Aspirations Awards that recognizes young women who are active and interested in computing and technology, and encourages them to pursue their passions.
Poemage: Poemage is a visualization system for exploring the the complex structures formed from a graph representing the interaction of words connected through some sonic or linguistic resemblance. The graph is generated using text-to-speach algorithms combined with our novel NLP approach for defining sonic similarities. The visualization tool allows the user to explore paths through the graph using several, linked views, and includes a novel technique for visualizing multiple paths directly in the text document itself. Poemage was developed at the University of Utah as part of an ongoing, highly exploratory collaboration between data visualization experts and literary scholars.
RhymeDesign: RhymeDesign is a novel NLP system for querying sets of words within a document connected through complex sonic patterns. RhymeDesign was developed at the University of Utah as part of an ongoing collaboration between researchers in data visualization, natural language processing, and literary studies.
last update July 28, 2016