I have pursued several projects in information and data visualization over the past couple of years, which I have documented here. The Information Visualization course that I took at the University of Michigan School of Information entailed two projects for the course over the final 10 weeks of the semester.
In addition to this I also pursued a passion project which explored to what degree does player transfers in Football really impact the club's performance in order to justify the fees involved.
The group project allowed us to explore a dataset and create a visualization which affords different types of tasks based on the role of an user that we identified. The project is to investigate how Americans engage in different artformss (such as opera, jazz etc.) using the Survey of Public Participation in the Arts 1982-2012 (ICPSR 35596).
We created a visualization which allowed the user understand the relationships between demographic variables and art forms, as well as the relative popularity of the different artforms.
The individual project explored the topic of Explorable Explorations - the use of interactive visualizations to support a learning task. Here, I explored how this can be used to better understand mathematical paradoxes such as the St. Petersburg Paradox.
I was inspired to pursue this due to my own fascination with the Monty Hall paradox and Paul Erdos's disbelief in the correct solution
Why? To encourage active reading, several ideas have been proposed: A reactive document allows the reader to play with the author's assumptions and analyses, and see the consquences. An explorable example makes the abstract concrete, and allows the reader to develop an intuition for how a system works. Contextual information allows the reader to learn related material just-in-time, and cross-check the author's claims. (Bret Victor; Explorable Explations)
I began this project due to my strong interest in Football and my curiosity to understand and analyse player transfers. Due to constraints of collecting data, I focused on the top 5 clubs in the Premier League and gathered data of each club's transfer activity.
This data included players bought, sold or released, player performance data (appearances and goals) and team event data such as trophies won, managers changed, ownership change etc. The goal was to identify the factors which determine the success of a club in the long run. I analysed the player transfer fees and their corresponding impact at the club to find a correlation.