In this second part of my BSIS program review, I am going to take a look at two assignments that stuck out to me as the most significant in my BSIS degree. This is not to say that there were not other assignments that impacted me greatly, because I can think of a handful of others that I could have just as easily talked about, but it wanted to talk about one assignment that fundamentally changed my outlook and one assignment that remined me why I love this field.

Assignment 1:

r/Reddit: Has anyone else noticed the rise of social epistemic tendencies in

internet users lately?

 I have written a lot of essays while in undergrad, many papers I’m proud of and definently some I would rather not look at again. This, however, is one of the only papers I regularly think about even years later. I wrote this for LIS 3261: Introduction to Information Science after being given the prompt to explore epistemology, the theory and study of knowledge and how we know things. This paper has shaped my approach for so many other assignments in my BSIS and fundamentally shifted how I approach epistemic tasks like information dissemination and communication.

 I believe this paper will continue to be important to me, and my academic journey, as after having several meetings with several professors and discussing options with my family, I believe that I am going to work on applying for a PhD program this year. As I continue forward, this is one essay of many that I want to bring forward with me, not just with nostalgia, but with a sense of continuity. For me, this paper represented a turning point — an early sign of the kinds of questions that fascinated me within data science and the field of information, the kind of research that sparked my curiosity, and the kinds of problems I hope to potentially spend my career investigating.

 While it might not be this subject exactly, this was a paper I remember spending much more time on then I think my professor ever expected, simply because I was curious and had a burning question. Now that I am looking into a PhD program, I want to find a program that ignites the same feeling I got from writing and looking back on this paper.

Assignment 2:

The Road So Far: Planning a 16th season of Supernatural with Visual Analytic techniques

The title alone should tell you that I had a lot of fun with this project but let me explain this project a little more and why I think it was important to me. This project was for LIS 4317: Visual Analytics and involved me participating in every step of the data process: Data collection, cleaning, analysis, conclusions, and visualizations. For this project, I wasn’t given any guidelines, and in height of my finals week haze and partly fever induced ideations (I happened to catch the flu the week I worked on this), I decided to make a funny project theorizing what a 16th season of my favorite could look like according to data analytics.

 What resulted from this fever dream of a project was rewatching said favorite show, using my domain specific knowledge to analyze statistical results and construct visualization to support my wacky conclusions of what I thought the Winchester brothers could face in this entirely fictional season 16. This project was dumb, solved no real-world problems, and was only interesting to the small intersection of people who really like looking at numbers and watching campy TV shows.

But still, this project holds a dear place in my heart that I want to take with me into my PhD, even if my research at that level will be (should be) more serious than this: This project reminded me that research can be fun, and these things I am learning are not only applicable to medical diagnostic data, survivorship analysis, or other real serious problems. I think it was important to remind myself how much I like data analysis and coding, and that while there are so many important problems to solve, these same methods can be used to explore purely fun and loose topics with no high-stake conclusions. It also reminded me that data is everywhere, if you let yourself look for it, and you’ll be surprised at what you can find if you let yourself explore the funny datasets or inquiries.