[Skip to Content]
Visit us on Facebook Visit us on FacebookVisit us on Linked In Visit us on Linked InVisit us on Twitter Visit us on TwitterVisit us on Facebook Visit us on InstagramVisit our RSS Feed View our RSS Feed
Region 5 Blog November 22nd, 2024
CategoriesCategoriesCategories Contact UsContact Us ArchivesArchives Region/OfficeRegion SearchSearch

Aug

29

Date prong graphic

DataFlash: Guest Writer – NCDS Data Intern, Silvia Wu

Posted by on August 29th, 2022 Posted in: Blog, Data Science, Training & Education
Tags: , ,


Photo of NCDS Data Intern, Silvia WuHello everyone, I am Silvia C. Wu and I am thrilled to be your NNLM Region 5 guest blogger this week for DataFlash.

I am a student from the San Jose State University School of Information and will graduate this Fall 2022 with a Master’s in Library Sciences and Information Systems and an Advanced Certificate in Strategic Management of Digital Assets and Services.

I was very fortunate to learn about the NCDS internship announcement from a networking group on social media and I signed up for the informational session right away! I timed enough lunchtime to listen to their informational session while eating during a break. At that time I was working as a Cataloging and Metadata Student Assistant for the SJSU MLK Library. I was always interested in data analysis but didn’t have the confidence to pursue it. I felt the NCDS internship would give me a good understanding of the Data Services librarianship.

The project I was assigned was for the NYU Library Health Sciences Data Services (NYUHSL) titled “Improving Data Services Education through the Analysis of Participant Feedback”. NYUHSL provides workshops on various data services topics to the NYU Langone Health community.   We both had regular check-ins with our mentors from NYUHSL, where they coached and support our research projects.

I titled my research “Getting to Know your Audience” to perform a quantitative and qualitative analysis of participant feedback evaluations by understanding the library’s users and their needs to improve future workshop. NYUHSL provided a dataset about workshops from 2019 to 2021. Here are a few slides from my presentation.

Silvia's NCDS Project showing horizontal bar charts

I used Qualitative Data Coding and the Grounded Theory approach for the analysis methodology. Here I am observing and comparing data to find trends and propose meaningful feedback based on findings.

The foundational courses from my SJSU MLIS program helped me set the initial direction and apply advanced concepts throughout the project.

I loved the hands-on Data-Driven Research experience. My favorite parts were data cleaning and finding the story behind the data. Although data cleaning was daunting, it was the best way to get to know the data; its intricacies brought forth what it had to share with us. Here is where many of the ideas for research questions came through. I enjoyed creating visualizations and bringing the storyline behind the data.

I had to restart my project several times; this required a lot of patience, discernment, and self-discipline. A powerful lesson is that every new attempt is not a failure but a new discovery. The process of changing direction or so-called “mistakes” contains very valuable information.

The internship introduced us to a wealth of tools to learn in such a short time. Because of the nature of the project, I got to work primarily with spreadsheets, which enabled me to become more proficient with pivot tables; I used OpenRefine for data cleaning and Tableau for some visualizations.

We were also taught Python, MySQL, and Git/GitHub but did not apply them in my project, however, this has opened Pandora’s box of possibilities for future learnings.

We presented our projects via Zoom to our cohort interns and members of the NNLM community. I felt very nervous during my final presentation. Once my presentation was over, I received positive feedback from my mentors and cohorts, and I felt more at ease. It was a gratifying experience.

It was inspiring and humbling to work in the Data field at this level, and a privilege to work with a highly professional and talented team. The NYU Health Sciences Library Data Services project gave me a window to use my skills and the confidence to be successful as a data librarian.

The NCDS internship experience showed me that there is much more to learn. It opened the opportunity to work with real data and real circumstances, and best of all, it addressed my love for learning and applying new concepts.

I now better understand the possibilities of the Data Services librarian profession. I couldn’t have wished for anything better. I would encourage any student to participate in any future NCDS internship.

Special thanks to Peace Ossom-Williamson, Justin de la Cruz, Nicole Contaxis, Genevieve Miliken, Fred La Polla, and Alisa Surkis for all their support, coaching, and mentoring. To all my SJSU instructors, fellow students, and Student Leadership Groups that allowed me to shape my professional path.

https://www.linkedin.com/in/silviacwu/

 

Image of the author ABOUT Nancy Shin
I received my Bachelor of Science in the Integrated Sciences majoring in medical genetics and animal biology from the University of British Columbia (UBC). I also graduated from UBC's esteemed MLIS program with a focus on health librarianship. In 2018, I was the Research Data Management Sewell Fund Fellow for the Technology Incubator at Washington State University. Currently, I'm the NNLM Region 5's Outreach and Data Coordinator for the University of Washington's Health Sciences Library. In my spare time, I enjoy photography, drawing, cooking and baking, and travelling the world!!!

Email author View all posts by
Developed resources reported in this program are supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012343 with the University of Washington.

NNLM and NETWORK OF THE NATIONAL LIBRARY OF MEDICINE are service marks of the US Department of Health and Human Services | Copyright | HHS Vulnerability Disclosure | Download PDF Reader