Thanks to an earlier fall deadline, we are already ready to announce the winners of our fourth year of the Duke Student Data Visualization Contest. The 14 visualizations submitted highlighted some very exciting visualization work being done by students of all ages here at Duke. The winners and other submissions to the contest will soon be featured on the Duke Data Visualization Flickr Gallery.
As in the past, the submissions were judged on the basis of five criteria: insightfulness, broad appeal, aesthetics, technical merit, and novelty. The three winning submissions this year exemplify all of these and tell rich stories about three very different types of research projects. The winning submissions will be converted to larger poster versions and hung in the Brandaleone Lab for Data and Visualization Services (in the Edge). Be on the look out later this semester for a reception to celebrate their hard work! The winners will also receive Amazon gift cards. We are very grateful to Duke University Libraries for their continuing support of the contest.
Global Flows of Agriculture and Forestry Feedstocks
Brandon Morrison, Ph.D. Candidate (Division of Earth & Ocean Sciences, NSOE)
Feature Interpretations from Ground Penetrating Radar at Vulci, Italy
Katherine McCusker, Ph.D. Student (Art History)
Simulated Sediment Deposition at Continental Margins
Candise Henry, Ph.D. Student (Division of Earth & Ocean Sciences, NSOE
Please join us in celebrating the outstanding work of these students!
2 thoughts on “2016 Student Data Visualization Contest Winners”
I think the biggest part of data visualization for me is the aesthetics. You can have a lot of really interesting data, but if you choose to present it in a boring way, it’s not going to be very interesting for the people watching. Thanks for sharing some great examples though.
Sure, I can understand that viewpoint, and I agree that user engagement is extremely important for the impact of the visualization. We don’t have that as our most important criterion because we hope to encourage students to focus on whether their visualization actually reveals something important about the data. Aesthetics can be improved on a visualization with a good core, but a flashy but deceptive visualization can be dangerous and unethical.
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