Reflections by Lynn Huang
1. What would you like to tell readers about yourself?
Hello! I have a B.S. in statistics and soon will have an M.S. in statistics too! I grew up in Des Moines, Iowa and went to Iowa State for both undergrad and graduate school. I got to spend a wonderful seven years in Ames coming into myself and meeting so many new people. I love to read when I can find the time. When I was younger, I loved to go to the public library whenever I could. During my undergrad, I volunteered at the Ames Public Library for three years so it seemed natural to apply to Parks when the job listing went up. I’ve spent a lot of time surrounded by books, and I hope that doesn’t end with my journey here!
2. When did you start working at Parks Library?
I started working at Parks in the summer of 2019. I was originally in the Stacks department shelving books and working on the shift. I transferred to DSI when our work went online for the pandemic in the spring semester of 2020.
3. What were some of the projects you worked on here in DSI (a quick list is fine!)?
• OCR correction for The Aurora and The Iowa Homemaker
• Uploading and entering metadata for Iowa Farm Science and ICM News
• Designing and implementing an R script that finds the most accurate crowdsourced transcription for each page in the Bomb
• Data visualizations for the materials in the University Library Digital Collections
4. Are there any specific projects which stand out, and why?
Writing a script to find the most accurate Bomb transcriptions and working on data visualizations of our digital collections. When I first applied to work at Parks, I was just looking to make some extra money. I never expected to be able to do something so relevant to my major or my interests. Both projects have involved cleaning and working with pretty large datasets and came with their own sets of challenges. Different yearbook pages vary vastly, so designing an algorithm that could be accurate across those required a lot of problem solving. With the digital collections visualizations, I’ve been looking at metadata that’s been preserved through several migrations and isn’t always consistent by nature. They’ve been really fun projects to tackle.
5. What did you find most valuable about your experience?
Getting to exercise some of the data science skills I’ve picked up in my coursework has been awesome. All data comes with its own unique quirks, and the library’s was no different. Being one of the first people to explore this data made me a stronger data scientist. In addition to that, the work I did will help make the University’s digital collections more accessible. Text analytics for digital collections is a really small area, so the work I’ve done has the potential to benefit not just Parks but other libraries seeking to analyze transcriptions on a large scale for their own digital collections, and that’s really awesome.
6. What would you like to tell other students about your experience if they’re thinking about applying for a DSI student assistant position?
Being open about what technical skills you have and what you’d be interested in learning can go a long way. There are so many projects varying from data analysis to engineering to research within this department, and the responsibilities are flexible. I don’t think any of the student assistants while I was working here were working on the exact same project in the exact same way. My role wasn’t very technical until I talked to one of my supervisors about knowing how to use R. After that, I got assigned to projects that were aligned more with my major and the experience I gained here helped me get a full-time job. The staff here is also very kind and helpful, and that’s always valuable in any workplace setting.
7. What have you learned from working at the Library?
So much! Technically speaking, I learned about natural language processing from this job which is something that I didn’t get to learn through my coursework. I also got a lot of firsthand experience in data mining, cleaning, and visualization through this job, as well as learning so much about how machine learning is used in doing document comparisons for digital collections. Part of this role was getting to do my own independent research on what was already being used to solve similar problems, and I was surprised by all the different ways analytics are applied in library settings. Last but not least, I also got to meet some really incredible people during the time I worked at Parks. The lasting connections I’ve made with the people in both Stacks and DSI are something I’ll always cherish.
