Individuals are nominated by their peers, supervisors, and others who interact with them in the workplace. Recipients are selected by a committee of their peers.  The selection criteria include:

• Build Community: Promote a sense of community within their work group, department, or across campus.
• Promote Inclusivity: Welcome diversity of opinions, consider accessibility, and adhere to respectful workplace expectations.
• Demonstrate Leadership Qualities: Provide high-quality performance, direct people to resources, and handle difficult situations well.
• Exemplify UO’s Mission and advance the university’s goals and values through their work.

Cameron’s skilled, generous work leading workshops, supervising student quantitative peer consultants (tutors), and helping students, staff, and faculty learn statistical programming and analysis have been central to the success of the Data Services unit within UO Libraries and a key reason that the number of statistical consultations in the library nearly doubled every year between 2020 and 2023. Not to mention that he was specifically thanked in the acknowledgements for 5 UO dissertations!

Congratulations, Cameron!

Calling UO Students who are passionate about data and helping others!

The Data Services Department at The University of Oregon Libraries has job openings for one or more student peer consultants for the 2024-25 academic year. Our mission is to provide a welcoming environment for learning and intellectual exchange for our fellow Duck researchers. The ideal candidate enjoys working with data and helping others learn more about data analysis, statistics, programming, data visualization, and other exciting issues dealing with data! The student peer consultant will help fellow Ducks through statistical consultations on data questions and assist with workshops on subjects ranging from computer programming to research reference management.

More information about the position can be found in the PDF below or through the Handshake link below. Hiring for fall will occur this spring term. Applications must be received by May 30, 2024.

Please follow this link below for the full job description on Handshake. Make sure you are logged into Handshake before you click the link! From Handshake, you can also search “Quantitative Methods Peer Consultant”. If any questions arise, feel free to reach out to us via email at dataservices@uoregon.edu.

Spring is here and there are exciting new offerings at Data Services! For those who want to learn programming fast, we’re offering a command line workshop and boot camp-style intensives for Python and R at the introductory level. If you want a more relaxed and thorough approach with similar material, we have biweekly Python and R courses, as well as shorter workshops on Qualtrics, Git, and Pandas. 

As always, we offer consultations for statistical methods, data management, R, SPSS, Python, GIS, version control, Excel, Dedoose, and Qualtrics at our help desk Monday – Friday 11am – 4pm in the DREAM Lab and or by appointment. Want to meet others interested in data science? Drop by Coffee & Code for short talks, the Coding Circle to work on coding projects over snacks, or join our Data Book Club. 

Check out our full calendar below! 

Workshops

One-Day Programming Boot Camps 

These all-day workshops will introduce you to the fundamentals of Python and R respectively. Come in over the weekend, come out with a new skill. Lunch will be provided. 

Python April 13^th, 10:00am to 4:30pm 

R April 13^th, 10:00am to 4:30pm 

Weekday Workshops

Command Line Essentials April 12^th, 2:30pm to 4:00pm 

Learning to code? This workshop teaches the fundamentals of command line interfaces, filesystem navigation, and scripting in Bash. These are key skills for aspiring programmers. 

Introduction to Python Mondays and Wednesdays, begins April 8^th, 1:00pm to 2:00pm 

A ten-session, interactive course that will help you develop core Python programming skills. No experience required!  

Introduction to R Tuesdays and Thursdays, begins April 9^th, 12:00pm to 1:00pm 

This eight-session course will introduce you to the fundamentals of using R! Intended for absolute beginners or anyone wanting to review the basics. 

Introduction to Qualtrics May 13^th and May 15^th, 12:00pm to 1:30pm 

If you are conducting surveys, then you want to learn all about Qualtrics! This workshop will introduce the basics of online data collection, setting up projects, and exporting survey data. 

Python Data Science Fundamentals Mondays and Wednesdays, begins May 13^th, 1:00pm to 3:00pm 

Already taken our Python course? This four-part workshop will teach you to analyze and visualize tabular data in Python by working through hands-on exercises with real data. 

Events

Data Bookclub: The Cultural Logic of Computation Alternate Fridays, begins April 12^th, 1:00pm to 2:00pm 

Join us as we discuss the effects of computers on society as we read The Cultural Logic of Computation by David Golumbia. 

Coffee + Data && Code Alternate Fridays, begins April 19^th, 1:00pm to 2:00pm 

An informal space for presentations and conversations about topics in data science! Learn new tips and tricks and get to know other people interested in coding.  

Coding Circle Weekly, begins April 26^th, 2:00pm to 4:00pm 

Have a tangle in your coding project? Come to coding circle to work it out! An informal and inclusive co-working session for anyone working with data or code.  

Questions about our offerings? Reach out to us at DataServices@uoregon.edu. 

Our colleagues at the Oregon Data Science Collaborative (ODSC) are hosting a full day data science symposium!

This workshop and networking event will bring together scientists from across Oregon to learn about data science research and resources, network with potential colleagues, and help inform our efforts to build community and offer training and consulting services to promote data science across Oregon.  Share your data science research, ideas, and proposals, learn how you can get help with research projects, participate in brainstorming sessions, and connect with data scientists. 

Register using this link

May 7^th, 2024, 10:00 – 3:00

9:30-10:00 Welcome with coffee and light snacks
10:00-12:00 Morning session (Invited talks)
12:00-1:00 Lunch break and networking
1:00-2:00 Student flash talks
2:00-3:00 Panel discussion on careers in data science
3:00-5:00 Optional social gathering (location: TBD)

Portland State University, Smith Memorial Student Union (SMSU) 327/328
1825 SW Broadway, Portland, OR 97201

Sign up for the ODSC slack to stay connected: ODSC SLACK 

The Oregon Data Science Collaborative (ODSC) is an NSF-funded collaborative institute between Oregon State University, the University of Oregon, and Portland State University. Our goal is to advance research across disciplines by facilitating collaboration between researchers and data scientists and by building a community of practice to disseminate familiarity, expertise, and training in data science. We offer data science workshops and research consulting for researchers across Oregon and the wider scientific community.

During my Vollstedt internship as a Data Services Learning Resources Specialist at UO, I found myself immersed in the dynamic world of research data management. My primary responsibilities included preparing Dryad launching at UO, creating LibGuides on best practices for data management, and curating and organizing learning resources related to research data. I really appreciate this internship opportunity as I gained hands-on experience and kept up with the latest trends and advancements in the field of data services.

In the initial weeks, I familiarized myself with the research data services provided, the library data infrastructure, and the various tools employed for data management. Meetings with my mentor, Gabriele Hayden, and other seasoned librarians provided me with valuable insights into the challenges and opportunities within research data management. Based on my interests and expertise, I contributed to developing LibGuides to help researchers understand and master research data management, including Dryad data repository, data publication, how to use DMPTool, and how to write data management plans. These LibGuides have been published on the Research Data Management website.

Another highlight of my internship was the opportunity to help the Graduate College track new publications published by UO’s amazing graduate students and advertise their works in their newsletter during a specific period. The challenge of this project is to track the publications of graduate students as they might not use any author IDs (e.g., ORCID) and might have wrong affiliation information in their works. By using the powerful OpenAlex API, I wrote some Python codes to automatically achieve the goal. I was so excited that I could address an actual problem in the academic setting. The codes have been shared on GitHub so that anyone can reuse the codes for their purposes.

Overall, this experience as a Data Services Learning Resources Specialist provided me with a comprehensive understanding of research data management and also equipped me with valuable skills and insights into this evolving field, which provided a solid foundation for my future endeavors in research data services. I am grateful for the opportunities for growth and learning that this internship has afforded me.