Data and Visualization Services is now accepting submissions to its 3rd annual student data visualization contest.  If you are a current Duke student and are undertaking a data analysis project in your classes or free time, start working on your submission now!

The purpose of the contest is to highlight outstanding student data visualization work at Duke University. Data and Visualization Services wants to give you a chance to showcase the hard work that goes into your visualization projects.

Data visualization here is broadly defined, encompassing everything from charts and graphs to 3D models to maps to data art.  Data visualizations may be part of a larger research project or may be developed specifically to communicate a trend or phenomenon. Some are static images, while others may be animated simulations or interactive web experiences.  Browse through previous years' submissions to get an idea of the range of work that counts as visualization.

The Student Data Visualization Contest is sponsored by Data and Visualization Services, Perkins Library, Scalable Computing Support Center, Office of Information Technology, the Office of the Vice Provost for Research, and the Sanford School for Public Policy.


To be eligible to submit to the contest, you must have been a Duke student (undergraduate, graduate, or professional, excluding post-docs) during the spring or fall semesters in 2014, submitting work completed before you graduated.

Submission instructions:

Full submissions will be due on Sunday, December 14. To submit, students should add themselves to the 2015 DataVis Contest Sakai site.  (First, log in to Sakai. Inside Sakai, you should click on "Membership" on the menu on the left.  Then you can click on the "Joinable Sites" button and search for "DataVis" in the search box on that page.)  Inside the Sakai contest site, you will click on Submissions to upload the files for your submission.

The full submission must include:

  • an image file of the visualization, suitable for the Duke Visualization Flickr gallery
    • Format: JPG, GIF, PNG, SVG, PDF, or TIFF
    • Size: no larger than 1200px x 800px, 72ppi preferred
    • Text: Please make sure the image itself includes a title and some sort of caption or descriptive text that contextualizes the visualization. The image file should stand alone and be understandable without any supporting documentation. (If you are not sure how to add text to visualizations, please contact
    • Also note: This is not a full poster version of the project. Instead, it should constitute a single data visualization, or a few screenshots from an interactive visualization website.  Again, see the gallery of last year's submissions for examples.
  • a document containing both a brief description of visualization process and short biography for each member of the visualization team
    • Length: at most two pages, including bios
    • Visualization description: This should focus on the visualization techniques used, and it should not contain tangential material about the larger research project. Make sure to outline the basic methods used to create the visualization, the reasoning behind the design choices, and the potential insights revealed by the visualization. If the visualization comes from an interactive website, feel free to include the URL in the description.
    • Bios: at most 50 words for each creator


A panel of five judges from across campus will review submissions. The submissions will be judged based on:

  • ability of the visualization to generate insights
  • ability of the visualization to tell a story that reaches broad audiences
  • aesthetics and design
  • technical merit
  • novelty


The judging panel will select the top three submissions, each of which will be converted into a poster and displayed in the Data and Visualization Services lab.  The three finalists will also receive Amazon gift cards - $250 for the top submission, $150 for the second place submission, and $100 for the third place submission.  Appropriate submissions will also be recommended as exhibits for the LINK Media Wall.

Additional information:

Please address all questions to Angela Zoss (, Data Visualization Coordinator, 226 Perkins Library.