Brewing Success with R.U.M.: How Inclusivity Fuels Manchester’s Thriving R Community

================== AnthonyEvans

:=========================: MartinHerrerias Azcue

:==============: RowanGreen

:==============: SianBladon

:=========================: Stavrina Dimosthenous

The R Consortium recently had the opportunity to interview Anthony Evans, Martin Herrerias Azcue, Rowan Green, Sian Bladon, and Stavrina Dimosthenous, organizers of the R User Group at the University of Manchester (R.U.M.). These leaders bring together a diverse community of students, researchers, and staff dedicated to advancing their skills in R programming. Their shared goal is to create an inclusive environment for learning and collaboration, which has driven the growth and success of the R.U.M. community.

Related Links

• RUM website
• CaDiR

Please share about your background and involvement with the RUGS group.

Tony: Yes, we’ve been involved in this group for about two years now. Initially, it was run by someone named Kamilla, who later moved to another university, and her role was taken over by Martin. Martin has been doing an excellent job leading the group, which mainly serves postgraduates, teaching staff, and research staff—really anyone enthusiastic about learning R and improving their skills, including a lot of newcomers.

When I first joined, my main goal was to improve my own R skills. Before that, I had been a helper in some R courses taught by the university, but I felt I could learn more and benefit from being part of a supportive community. The group is full of volunteers who are passionate about R and programming in general. They’re always willing to share their knowledge and help one another, which has been incredibly valuable. This spirit of sharing and collaboration creates a fantastic environment, especially in a university setting where research thrives on collective learning.

Martin: I joined the group about two years ago. I had only been using R for about six months before that, so I didn’t have much experience with it. Our group had only a handful of people who knew R, and two of them left the University shortly after. Suddenly I found myself needing to support researchers who ran into issues with R, as well as managing projects like our pilot Shiny server. We had to find ways to support these types of projects. The R User Group became a valuable resource for us to stay connected with researchers actively using R and to continue learning the language ourselves.

Rowan: I am a PhD student in evolution and ecology. When the R.U.M group was restarted, a general email was sent to the university. As someone who enjoys mentoring younger lab group members in R and learning about new R tools, I was interested in helping restart the group.

Stavrina: As a Data Scientist and Data Visualization enthusiast, I used to run our Data Visualisation Club monthly meetups. I have taken a step back, but I was involved in the group’s initial creation and help a bit with organizing and strategizing now.

Can you share what the local R Community is like?

Tony: The university’s local community is mostly composed of postgraduates, along with some researchers who are starting to use R in their work. Everyone in the community is very enthusiastic, eager to learn, and focused on improving their skills. It’s a highly motivated and self-sustaining group. Everyone in the R community is very friendly and welcoming. It’s a great, supportive environment.

Martin: Most people in our R community come from humanities backgrounds. There’s a group in health economics that uses R extensively, as well as some in psychology and language studies. We also have a large group in genomics. It feels like there’s a wide range of experience—some researchers have been working with R for a long time, while many postgraduates are just starting to learn. As a group, it can be challenging to support both experienced users and beginners, but we do our best to meet everyone’s needs.

Rowan: The local R community exists at multiple levels. It is often most active at a small scale within research groups, where members share advice. At the university level, R.U.M. brings together people from a broader variety of backgrounds. There is also a city-wide R community in Manchester, where quarterly talks are organized by Datacove. These events bring together people from industry, public health, academia, and more.

You had a Meetup on “R Functions [for visualization].” Can you share more about the topic covered? Why this topic?

Martin: Our previous event hadn’t gone as well as we hoped. We tried to cover a pretty complex topic—reproducible science using R on a Docker container with renv—but it wasn’t very well attended. So, we decided to shift our focus to beginner users and cover some basics that every R user should know but that we’ve noticed many beginners struggle with. The event covered the basics of function syntax and organizing code with functions. We also had a second talk that was a bit more advanced, focusing on using functions with the purrr map function to automate plot production. The goal was to attract a broader range of users, as our previous events have mainly catered to advanced users.

Tony: We’ve noticed that many users haven’t been responding to the more advanced topics. In general, though, making code readable is crucial, especially for researchers who need others to reproduce their work. If the code is hard to understand, it complicates reproducibility, but organizing code with functions makes it much clearer. This is an essential aspect of programming, and it also ties into plotting, which is one of the most requested skills among students. Most students using R for research will need to create plots to convey complex conclusions and ideas. Plots are much more effective than raw data alone, and R produces some of the best visualizations out there. Even organizations like the Financial Times use R for their high-quality graphs, so it’s a valuable and widely-used skill.

Stavrina: A barrier to entry in any programming language or tool is sometimes seeing demonstrable evidence of how it can be useful to an individual, especially at undergraduate and early postgraduate level. Working within a University and Research environment, we all have to make plots and advanced visualizations. Sometimes, though, the extra step is standardizing and making that reproducible for high-throughput plotting. Combining visualizations with functions achieves just that and can serve as a practical and aspirational demonstration for our community.

Any techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?

Tony: One technique we started using since COVID is hybrid teaching. We initially used Zoom, but then switched to Teams. This approach has been very inclusive because it allows people in distant locations, even in other countries, or those with long commutes to participate in our talks. In the past, everyone had to be physically on campus, which excluded those who lived further away. Now, with hybrid teaching, more people can join in, regardless of their location.

Martin: Yes, we’ve noticed that this might have been part of the issue. Our last talk was advertised as in-person only because it was meant to be hands-on, Carpentry-style training. That may have contributed to the low attendance. It definitely makes a difference—when we make an event hybrid, we tend to get a lot more participation.

Stavrina: We use conferencing software for all our meetings and make the invitation open to anyone outside the organization, we are lucky that we have access to meeting spaces that have suitable equipment for running hybrid meetings.

What trends do you currently see in R language and your industry? Any trends you see developing in the near future?

Tony: Researchers and academic programs are increasingly looking to include R and RStudio in their teaching and research for two main reasons. First, data regulations have become much stricter over the past couple of years, and with R, you have complete control over where your data is stored. You know it’s not in the cloud or being transferred to any external organization, which helps in meeting university data compliance standards.

The second reason for the shift towards R is that it’s free from licensing restrictions. With some other software, licensing can be highly restrictive—you might only be allowed to use it in certain countries, like the UK, or only on campus. R, on the other hand, offers a more inclusive environment for research, allowing access without these geographic or licensing limitations. This flexibility is a big part of why R is becoming so popular within the research community.

Martin: I completely agree. I couldn’t have put it better myself, but as Tony pointed out, R is becoming more and more popular. It’s gaining broader appeal and is now appreciated as a general scientific programming language rather than just a niche statistical tool. There’s a clear trend, as Tony described, toward open science and open source software, and R is becoming a significant part of that movement.

Rowan: One big trend is the use of LLMs/AI both for writing code in R, and as a tool executed through R. We were really lucky to have a former R users group member, Kamilla Kopec-Harding, return to give a talk on both of these perspectives earlier this year.

Sian: R remains relatively niche and widely recognized in bioinformatics, clinical trials, fintech, and marketing. However, Hadley Wickham and others’ contributions - through the tidyverse and packages like dplyr, ggplot2, and roxygen2 - have significantly broadened R’s appeal and impact in recent years. From an anecdotal perspective, about a decade ago, it was rare to see job postings requiring R skills. Today, although R may not have the same reach as languages like Python, job searches for R roles now yield far more opportunities than before.

How do I Join?

R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.

https://r-consortium.org/all-projects/rugsprogram.html