VizUM Visualization Competition Idea Checkpoint 3/9/2018

Idea Checkpoint | Please RSVP

Friday, March 9, 2018  |  3:00-6:00 PM
Gables One Tower, Training Room 639

Checkpoint #1, the “Idea Checkpoint”,  will give you the opportunity to get feedback on your project from the Organizing Committee. It’s also an excellent opportunity to meet the other participants! We will have 10-minute consultation slots available for you to book.  The gathering will take place at the Center for Computational Science, at 1320 S Dixie Highway, in Training Room 639 (turn left off the elevators and it’s on the right), and the consultations will take place in conference rooms inside the CCS Suite (600).

This is the first of two checkpoints, designed to keep you on track, and, particularly if you are a beginner, to give you a little bit of guidance on the typical process of a data analysis. Attendance is voluntary, not required, but the checkpoint provides an opportunity to reflect on how your project is coming along by having to summarize all the details for someone else to consume. This perspective is a valuable tool and it can help you deliver your best.  You can come for any portion of the gathering that works for your schedule.

  • By this point you should have a clear idea of what your project will be about, and of whether you will design a data-driven visual essay/story/infographic or an exploratory data visualization.
  • You don’t yet need to have a detailed plan of what your final product will look like, but you do need to know what information you will use to make it.
  • The purpose behind this checkpoint is to ensure that the dataset does in fact contain the information that you need in order to answer your question of interest. A common pitfall in data analysis is thinking that you are asking one question, when the information available to you lends itself to answering something (slightly or more than slightly) different.
  • Are you able to refine your question after having taken a closer look at the data and the metadata? What are some possible sources of bias and is there any way that you can avoid them without spending time and resources collecting more data?

Deliverable: A paragraph describing the question that drives your visualization, emailed to, or, bring it with you. You may describe the issue that you care about, why it is important to you to raise awareness about this issue, some limitations of the data to answer your question and what you plan to do about these limitations (if anything can be done).

Organizing Committee Members

Alberto Cairo PhD, Professor of Professional Practice / Knight Chair in Visual Journalism | UM School of Communication
Maria Galli Stampino PhD, Professor of French and Italian | College of Arts & Sciences
Mahsa Mirazargar PhD, Assistant Professor | Department of Computer Science | UM College of Arts & Sciences
Athina Hadjixenofontos PhD, Director of Engagement | UM Center for Computational Science


For questions regarding the contest, please don’t hesitate to email

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