DATA SERVICES

Bits and Bytes

February 2025

Hello Data Enthusiast,

Welcome to the third issue of Bits and Bytes, the NYU Data Services newsletter!
Explore the many ways we support researchers at NYU by visiting our website, and read on to find out about past and upcoming events, explore our featured datasets, and get to know our team of specialists.

Federal Data: Resources and Updates

Recently, there have been significant changes to availability of federal data. These data are heavily used by researchers and the general public; they also undergird policy and funding decisions made on behalf of people across the US and worldwide (see an article in the New York Times and a story about CDC data in the Guardian). Data Services staff are following these developments closely and contributing to the many data rescue efforts by organizations and individuals across the research community.

If you are having difficulty accessing data you use for your research and/or teaching, or are concerned about posting data you have created on federally-hosted websites, please reach out to Data Services. We can work with you on access and storage plans.

If you'd like to get involved, check out the digital zine S ave Data: Curation Steps for Data Rescue for tips and best practices for rescuing and organizing data.

Upcoming Events in February and March

Image credit: NYU Libraries

Data Services Workshops and Tutorials: February 27 - March 7

Looking to use data in your work this semester? Take a workshop or tutorial with Data Services to learn something new or brush up on your skills. Our free workshops are available to current NYU students, faculty, and staff and continue until March 7th. Don't miss out! Find a Data Services class on the NYU Libraries events calendar. If you don't see a class you were looking forward to attending, you can always request a workshop or a personal consultation using this form.

Photo credit: NYU Dibner Library

Introduction to Machine Learning Clinic Series at Dibner Library

Calling all Brooklyn Campus regulars! Fabiha Khalid, our Data Services Specialist at Dibner, is running a Introduction to Machine Learning Clinic. Sessions are held biweekly, with the next one on March 6th at 2 PM, over at Bern Dibner Library. Don't forget to register for upcoming sessions!

In Case You Missed It...

Photo credit: NYU

Flash FORC: Advancing AI Literacy at NYU

NYU Data Services, GSAS Master’s College, and the Office of Teaching Excellence and Innovation hosted Flash FORC, a one-day AI literacy workshop on January 16, 2025. As an extension of the Foundations of Research Computing (FORC) series, Flash FORC pilot focused on generative AI’s role in research, attracting over 45 graduate students from diverse programs such as Journalism, Data Science, and Engineering (Tandon).

The workshop featured two specialized tracks: Patrick Burns led a non-coding session on understanding large language models (LLMs) and optimizing AI outputs using retrieval-augmented generation (RAG) workflows. Meanwhile, Makesh Srinivasan and Stuti Mishra guided participants through hands-on coding exercises to build RAG pipelines and develop context-aware AI solutions.

The Flash FORC model helps drive digital literacy, foster interdisciplinary connections, and empower early-career researchers with practical AI skills. Participant feedback highlighted a growing demand for extended sessions, so stay tuned for future FORC opportunities!

Image Credit: NYU Libraries

Love Data Week at NYU

Thank you to everyone who joined us in celebrating Love Data Week 2025 (February 10-14)! This year's theme, "Whose Data Is It, Anyway?" prompted attendees to reflect on where data comes from and how to use it ethically through a series of events.

Highlights from Love Data Week included:

A presentation on reducing risk and data anonymization from Kristi Thompson, Data Management Librarian from Western University
A session on NYU's Enterprise Information Management philosophy and practice with Kylie Vallario and Adrian Kulpa
A primer on privacy and protecting personal information (PII) in research data with Devin Nix of NYU's Global Privacy Office
A career panel featuring former NYU Data Services student employees
Discussions and workshops on NYC Open Data, Python, and Latex at Dibner Library
Data Services tutorials on R and Stata
And a Valentine's Day film screening of WALL-E

UltraViolet is part of a suite of repositories at NYU that provide a home for research materials. Got your own data, code, or other research materials? Check out our UltraViolet deposit guide and get in touch!

This month, we have published an exciting new set of urban data from Professor Solly Angel’s Urban Expansion Initiative team at the Marron Institute. Professor Angel and collaborators have released a report evaluating the Ethiopia Urban Expansion Initiative, along with accompanying household survey and mapping data. Developed with Amistad Civil Engineering PLC and the Marron Institute, the survey, geospatial analysis, and report evaluate the economic and health impacts of new arterial roads in Ethiopian cities. This data was curated by our Urban Data Student Specialist, Akanksha Patil, and is part of a Data Services initiative to collect and curate urban data across NYU.

Data Services Team Spotlight: Yuan (Zoey) Zhou!

Photo Credit: Yuan (Zoey) Zhou

What's your name, program, and year?
My name is Yuan (Zoey) Zhou, a second-year master's student for Applied Urban Science & Informatics.

What's your service area at Data Services and how long have you worked here?
Python and Quantitative analysis - I've been working at Data Services for 9 months!

What do you like most about working at Data Services?
What I enjoy most about working at Data Services is the opportunity to interact with researchers from diverse fields. It's fulfilling to help them leverage Python for data analysis and enhance their workflow efficiency. I can also expand my own knowledge by learning from different research perspectives through this process.

Describe your favorite data-related project that you've worked on.
One of my favorite data-related projects was analyzing mobility patterns of delivery workers using mobile phone dataset. The goal was to identify the trajectory of delivery workers and to analyze the geographical distribution. I worked on cleaning and processing large datasets, applying statistical methods, and visualizing insights using Python.

What's your favorite place to get a meal or a snack near Bobst Library?
Heytea Bubble tea is always my favorite!

Thanks for reading! We hope to see you soon either on the 5th floor at Bobst or online.

- Your friends at NYU Data Services

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