Real World Application of Data and Vizualizers
After reading “What is Data?” and analyzing the three visulization examples, I have been noticing how most of the websites I visit utilize these charts to showcase data that easily translates the information to the user. This most prominent example of this in my life is the new Texas A&M COVID-19 Dashboard. The website uses a relatively simple bar graph and donut chart to showcase “Daily new cases self-reported of COVID-19 among Texas A&M University Faculty, Staff and Students” and “Overall COVID-19 Testing Positivity at Texas A&M University,” respectively.
Both of these graphs use scalar data that has been collected through the Curative Inc. testing tent, Student Health Services (Beutal Health Center), and through self-reported cases to the A&M portal. Now unfortunately, A&M does not use dictionary compound data, meaning they do not associate each test with an individuals university identification number . Instead, the university utilizes List compound data compiled of integers that represent a person’s test result along with the day the individual took the test. For the bar graph on the dashboard, the data is organized into the number of positive tests received on a specific day for either students or faculty and staff. The donut chart below it showcases the percentage of positive cases to negatives cases at A&M.
After seeing the visualizers used for the Demographics of Others website, I believe that A&M’s COVID-19 dashboard is severly lacking. If they utilized dictionary data and attached results to students’ UINs, the numbers would not included the possible duplicate tests if a student receives two tests within the same time period designated by the charts. The bar graph format also limits the amount of data that can be seen within the space. Using a line graph would help include a longer time period and a higher number of cases. Creating to separate lines for students and faculty/staff would make the distinction between them more prominent, as the current format makes it difficult to see while both grpups are displayed. A Texas A&M student has used Brazos County Health Department information and created a much more expansive chart that showcases how a line graph organizes more information while remaining readible by the every day usuer. The donut chart does seem to be the most effective way to display the data since it is only made up of two percentages.
With the use od dictionary compound data, the dashboard could show much more about what the tests mean in real life. The dashboard of the University of North Carolina-Chapel Hill has an extensive amount of information that utilizes many different visualizer. Using A&M community members UIN’s could provide specific info on duplicate tests within a time period, active and recovered cases, and clusters. A&M’s extensive Information Technology department and testing resources should be able to provide the community with more information. Using List compound data limits the use of the information A&M is collecting to simply a test identification number and a test result. Given the importance of this information for students, faculty, and staff, A&M should use dictionary compund data to create more visualizers if they want the community to stay informed.
Posted In: Reflections