Visualizing Uncertainty on Maps

All maps are uncertain, but rarely is this evident in their design. The seminar will first introduce common ways that cartographers conceptualize and represent uncertainty, then discuss the mixed methods research on the implications of communicating uncertainty on maps, conclude with future research opportunities for visualizing uncertainty on maps.

August 4, 2022, 11:00am Eastern Time – August 4, 2022, 1:00pm Eastern Time

Webinar Ended

Speaker

Robert RothRobert Roth, University of Wisconsin-Madison

Dr. Robert Roth is a Professor of Geography in the University of Wisconsin-Madison and is the Director of the UW Cartography Lab and UW GIS Professional Programs. Roth received a National Science Foundation CAREER award to study the design and teaching of interactive, online, and mobile maps, which resulted in three free and open source books including, one coauthored and published by the United Nations and International Cartographic Association, and for which he was named the AAG GISS Specialty Group 2021 Waldo Tobler Distinguished Lecturer in GIScience. Roth’s students have gone on to work at Apple, Esri, Google, Mapbox, National Geographic, The New York Times, Stamen Design, The Wall Street Journal, The Washington Post, Uber, and many federal, state, and municipal agencies.


Audience and capacity

This seminar is open to graduate students who are interested to learn about (1) Uncertainty is a fact of all information, geospatial or otherwise, but rarely is communicated on maps. As a result, map users ranging from decision makers to the general public often do not question the information represented in maps; (2) Common uncertainties found in geospatial data that can be represented in maps include accuracy or error, precision or resolution, and other data dimensions that influence “trustworthiness”, such as completeness, consistency, credibility, currency, interrelatedness, lineage, and subjectivity; (3) Design matters! Some uncertainty visualizations emphasize the certain information while others emphasize the uncertain information, and different symbolization solutions are more or less metaphorically congruent when paired with different kinds of uncertainty in geospatial data; (4) Empirical research, including both quantitative controlled experiments and qualitative social science methods, can help us understand how to design and use maps that include representations of uncertainty.

We can welcome up to 300 members to participate in this seminar.