STEM Data Fellow Spotlight: Sahil Chugani

When I was in elementary school, I remember Googling various football statistics, running down to my parents, and telling them, for example,  “Ben Roethlisberger had 4,328 passing yards in 2009!” I played football for eight years from elementary school to high school, and I was good with working with numbers. I found that sports analytics was a great combination of the two. In high school, I entered a sports analytics competition, where my project was to determine what would happen if onside kicks in football would be replaced with a 4th down and 15, and I absolutely loved it. Now, I’m fascinated with data science as a whole– being able to make a computer do something that we could never imagine doing as humans is an amazing feeling for me.

Since the sports analytics competition, I’ve been doing anything and everything I could related to data science. Some of the research I’m currently working on includes sports team values, kickstarter data, and sportswashing (for example, Qatar holding the World Cup amidst some controversial political issues). I also had a job this year working for a company called Scouting Heroes, where I logged basic statistics for the FSU football team. (More information on what the data I collected was for can be found at https://simplebet.io/nfl.html.) I’ve also worked on creating data visualizations based on football data. For example, this past summer I created over 20 graphs that can be found at https://twitter.com/a_graph_a_day .

In one of my classes, one of my (now) coworkers, William-Elijah Clark, posted the opening for the STEM Libraries Data Fellowship in the class’s GroupMe, and I was eager to apply. Something I’m super excited for with this Data Fellowship is that I really want to translate my skills into some real-world experience. Instead of simply creating graphs or finding statistics on my own, I want to have a tangible impact with regard to data. I hope to be able to help students out with their needs or be able to have my data analysis translate into a decision being made that affects people. In a way, it would signify that my hard work on data analysis is paying off. 

One of the projects that I’m super interested in working on as a Data Fellow is the use of Jupyter Books to assist users in learning more about how to code and analyze data as a whole. By offering interactive code blocks and giving users the opportunity to run code on their own, they may be more willing to learn about the data analysis techniques used. Furthermore, I hope that by implementing sports analytics examples, specifically football, people who are interested in sports may be more willing to learn how to use data analysis techniques with respect to sports.

As a whole, I’m very excited to learn more about data analysis techniques here at the FSU libraries and as well as apply my skills to tangibly help others at Florida State as a whole. 

This blog post was written by Sahil Chugani, STEM Data Fellow at FSU Libraries.

STEM Data Fellow Spotlight: Reagan Bourne

Prior to my experience at Florida State University, I took a few research classes in high school. In these classes, I had assignments where I would have to collect and analyze data as part of a research project. These experiences sparked my interest in data science, and from that point forward I always knew that I was interested in data-related research. Furthermore, I have always been interested in a few different subjects, including computer science, biology, and mathematics. I never realized that I would be able to combine my interests before starting this data fellowship.

When I first found this fellowship during the summer of 2022, I felt that I was at an academic crossroads. I was unsure of what I wanted to study and my career goals. However, I was extremely interested in this opportunity, because it was unlike anything I had ever really known about. I thought that this position would be a great learning opportunity for me, and would  hopefully allow me to utilize my data skills and pursue some of my interests. So far, this fellowship has gone above and beyond what I was hoping for. 

As I am still in the beginning of my academic career, I have not had the opportunity to obtain much experience using my data skills before this fellowship. For this reason, I am so grateful to be participating in this fellowship. I have already learned so many different things in my few months here. One of my first assignments was to meet with many of the different librarians at FSU Libraries. I really enjoyed this task, because I liked hearing about all of the different paths that were taken until finding this career. It introduced me to a lot of different projects and areas of expertise in the library that I had never known about, such as the Health Data Sciences Initiative and open science. 

Another concept that I have recently learned a lot about is the importance of critically evaluating data. Working on a blog post about this topic has been a great learning experience for me. It has introduced me to so many ideas that I had never known about.  Specifically, I have learned about machine learning algorithms for data science. As a student currently pursuing a computer science degree with a minor in data analytics, this topic was extremely interesting to me, and is something that I am excited to explore further. 

As I take more classes related to my major, I am excited to apply the skills I learn towards this fellowship. In the future I hope to teach workshops about Unix, C#, SQL, and many more.  I am looking forward to continuing my work with the FSU Libraries.

This blog post was written by Reagan Bourne, STEM Data Fellow at FSU Libraries.

What is a Census Research Data Center and Why Should You Care?

This semester, FSU became the newest consortial member of Atlanta’s Census Research Data Center. Funded primarily by the College of Social Sciences and the Office of Research, the Florida State community can now use Census micro-data without paying lab fees, which can range upwards of $15,000 per project.  There are currently 18 Census Research Data Centers in the United States, and outside of North Carolina’s Research Triangle the only one located in the southeastern United States is The Federal Reserve Bank of Atlanta.

So, what is a Census Research Data Center? The Center for Economic Studies defines Census Research Data Centers (RDCs) as U.S. Census Bureau facilities, staffed by a Census Bureau employee, which meet all physical and computer security requirements for access to restricted–use data. At RDCs, qualified researchers with approved projects receive restricted access to selected non–public Census Bureau data files.

Where do college graduates work? Visualization based on 2012 Census data.

To understand the true value of doing research with non-public data from the RDC, it’s important to note the difference between micro data and macro data, which is often referred to as aggregate data. When most of us use datasets for research or analysis, we’re looking at summary figures. For example, if you extract Census data for analysis, you’re typically looking at some sort of summary or aggregation for a specific geographic unit. These geographic units range from state, county, city as well as much smaller units such as census tracts and block groups. Regardless of unit of analysis, the data itself is a summarization of individual survey responses for participants in that specific area.