February 2024 Newsletter | Data Science and Society

Volume 2, Issue 2

Happy New Year! We hope you are all doing well. Since our last newsletter in October 2023, the DSS Steering Committee has been continuing our efforts in working groups to accomplish concrete tasks based on the feedback we’ve received from the campus community and peer institutions. Read on to learn more!

DSS Faculty and Student Small Grant Program. We’re thrilled to announce the new Data Science & Society (DSS) Faculty and Student Small Grant Program, aimed at enriching data science in research and education. Open to faculty and students, this initiative offers three funding categories: Faculty Research, Faculty Teaching, and Student Research and Learning. Opportunities include grants for data skills development, research assistance, and specialized resources. We encourage applicants, particularly from non-traditional STEM fields, to advance data science applications in their work. Join us in this innovative endeavor to integrate data science into our academic community! Please see our website for more information and the application link.

DSS Technical Workshops. We’re also excited to announce that we will be holding three technical workshops this semester. These are open to everyone from the campus community. Please find information and registration links for each workshop below.

Introduction to Python for Data Science
February 21 3:30 – 5:00 PM, Sci Viz Lab

Python has become more and more popular for data maintenance, wrangling, visualization, and analysis. Do you want to see what all the fuss is about? This hands-on workshop will cover the basics of Python coding and will introduce some common data-focused packages. This workshop is suitable for novice coders as well as those with coding or scripting experience in other statistical software such as R or Stata. Computers available, however, if possible, please bring a laptop to the session.

Sponsored by Data Science and Society, led by Simon Hoellerbauer of DSS

Introduction to Git and Github
March 22, 10:30 AM – 12:00 PM, Sci Viz Lab

Tired of naming files final_draft_v12_comments_corrected_v10.docx? Git is a commonly used version control system that solves this exact problem and is especially helpful when collaborating with others. GitHub is one of the most popular home for Git-based projects on the internet. This workshop will introduce you to Git and GitHub. You will practice making commits, pushing, and pulling, but alone and in collaboration with others. Please bring a laptop to the session.

Sponsored by Data Science and Society, led by Simon Hoellerbauer of DSS

Introduction to R for Data Science
April 12, 10:30 AM – 12:00 PM, Sci Viz Lab

R is a statistical programming environment commonly used in academia for creating data visualizations and doing statistical analyses in a more regimented manner. This workshop provides a basic overview of using R and RStudio (a common interactive development environment) for statistical analysis (please note that this workshop does not cover statistical concepts).This workshop is suitable for novice coders as well as those with coding or scripting experience in other statistical software such as SPSS or Stata. Computers available, however, if possible, please bring a laptop to the session.

Sponsored by Data Science and Society, led by Simon Hoellerbauer of DSS

Colloquium Series. There are currently two colloquium series events planned for the Spring 2024 semester.

On Wednesday, February 7th, at 5 PM in Rockefeller Hall 300, Brenden Lake (Professor of Psychology and Data Science, NYU) is giving a talk co-sponsored by the Department of Cognitive Science titled “Addressing two classic debates in cognitive science with deep learning.”

On Tuesday, April 9th, the Lens Media Lab of the Institute for the Preservation of Cultural Heritage at Yale University is giving a presentation on digital humanities and art in the medium of photography, co-sponsored by the Department of Art and the Loeb.

Please let us know if there is someone you would like to bring to Vassar, and we can make it happen! You can view the developing schedule here and mark your calendars: https://pages.vassar.edu/dss/colloquium-series-schedule/

DSS-Interested Student Mailing List. In order to continue to identify and establish the DSS community on campus, we are gathering a list of students interested in data science. We share data science opportunities on and off campus with this list, and plan to use it to develop more student-centered DSS programming. Please share this sign-up link with any of your students or advisees who may be interested in data science: https://forms.gle/EdZMXn8UbPGBzixq6

DataFest 2024 @ Vassar will be held April 5th to 7th this year. Everyone is welcome to be involved – students can register as participants and faculty/staff can volunteer as consultants or judges. DataFest has been held at Vassar since 2016 and has been generously sponsored by departments and programs across campus. For the second year, DSS is delighted to join as a sponsor. To learn more about DataFest, visit https://pages.vassar.edu/datafest/. Are you a faculty/staff interested in volunteering as a consultant or judge? Contact any of the organizers (Ming An, Simon Hoellerbauer, Monika Hu, and Lee Kennedy-Shaffer). Students can register for free (as a part of a team or as an individual) and the deadline is Friday March 1, 2023.

Curriculum Efforts. The DSS Steering Committee is diligently drafting a proposal for a Data Science and Society correlate. We have set an internal deadline of March 2 for the various components of the correlate – courses, progression, oversight, staffing, etcl. We will spend the second half of the semester evaluating whether the proposal meets the goals of the steering committee and the needs of Vassar students. If so, we plan to submit it for CCP and faculty approval by the 2024-2025 academic year at the latest. We expect to share more about the correlate requirements soon!

From all of us on the DSS Steering Committee:
Ming An (Mathematics and Statistics)
Allan Clifton (Psychological Science)
Leroy Cooper (Biology, STS)
Abby Coplin (Sociology, STS)
Jonathan Gordon (Computer Science)
Ben Ho (Economics)
Simon Hoellerbauer (Data Science and Society)
Monika Hu (Mathematics and Statistics)
Lee Kennedy-Shaffer (Mathematics and Statistics
Ben Lotto (Mathematics and Statistics)
Sarah Pearlman (Economics)
Marc Smith (Computer Science)
Jason Waterman (Computer Science)