Sunday, February 3, 2013

Data Visualization MOOC: an Update

   I'm entering my fourth week as a student in the Data Visualization and Infographics course offered through the Knight School of Journalism, University of Texas. The course is a MOOC (massive, open, online course) with about 5000 students enrolled. The course has lived up to expectations in all ways.

   The professor, Alberto Cairo, has put together a well-ordered curriculum that builds on itself, week to week.  From an entry point where I knew only that I was fascinated by the data visualizations I had seen, I have quickly become familiar with some of the field's theorists. Through readings and videos, I now have a much clearer sense of what makes an infographic work and where the common pitfalls lay.  I also understand that every set of data allows for multiple visual expressions and the role of the designer is in part to choose the tools that will most clearly display the data. Finally, I understand that data visualizations are designed to tell a story and to raise questions.  Not all are successful, but the best meet both goals.

   During week 3, we began to move from theory to production. One of our assignments was to look over a data set and create an infographic.  This infographic did not need to be "polished;" rather, it could be read as a set of working notes that allowed others to see what we wanted to do with our infographic.  I should note here that there are specific software tools designers use to create the very sharp looking infographics we see in newspapers, magazines and websites. These tools can allow for an interactive experience where the viewer, by hovering a mouse cursor or using a drop-down menu, can change the data set and the resulting presentation.  We have been offered tutorials on two software tools (Adobe Illustrator and Tableau) but for right now, virtually everyone seems to be using other more limited tools to create projects.

   Our data set involved two sets of interconnected data. One set divided higher education faculty in the US into classes: professors, associate professors, assistant professors, instructors and lecturers. The other set examined how for each class, the percentage of tenured, tenure-track and non-tenured changed over time.  Our job as students was to get the data to tell a story and to allow it to raise questions. We could bring in additional data sets but we needed to work with the set of AFT-generated data from 2001 to 2009.

   The data set: http://www.highereddata.aft.org/instit/national/tenure_rank.cfm

   Here is the infographic I created: Faculty Tenure in Higher Education: A Changing Landscape

   During this upcoming week, my project submission will be critiqued by a few other students via website forums. I'll do the same for other projects.  Then, with feedback, I'll have a chance to make some changes. 

   If you have looked over the project and would like to offer any comments, please feel free to use the comment section of this post. I'm happy to hear from others as I try and learn how this new skill.

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