Attending the R/Medicine Conference and Collaboration Opportunities

Posted by kimberlycarlo on May 31st, 2026 Posted in: Blog, Data
Tags: coding, conferences, Data

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The 2026 R/Medicine conference took place virtually from June 5th to June 8th.

This conference provides a live space for sharing R-based tools and approaches to analyze and gain insights from health data. Even though not everyone attending this conference will consider themselves data librarians, we all share an interest in working with health data, further developing our R skill set, and building community. Anyone who works with data in R or those who want to learn more about R would benefit from this conference.

 

The conference attendees and presenters were from all over the globe. This gave us all a chance to learn from those who may be working with data differently and see how professionals throughout the United States and overseas are working with data. If you would like to learn more about the conference and the keynote speakers, feel free to check out the R/Medicine webpage. It may inspire you to attend next year! Another benefit of a global, virtual conference like this one is having the chance to develop your own R packages with people from all over the world. One of the presentations that encouraged this work was a workshop before the conference week called “Make your first R open source contribution with git, forks, and PRs”. This was presented by Daniel Chen (Lecturer at The University of British Columbia in the Statistics Department and Master’s of Data Science program). This workshop was great for R beginners and to prepare attendees for the conference. In addition to learning about developing my own R packages, some of the new ones I learned about at the conference include teal, rOpenSci, and the shinyscholar package.

If you were unable to attend, but still would like to watch the presentations, check out the R Consortium YouTube Channel. If you visit the playlist tab, they have videos from other conferences and presentations hosted by the R Consortium.

 

Although networking is encouraged at this conference, I would like to share some additional networking resources and opportunities for data professionals. I heard about various R communities, such as R Ladies, Py Ladies, Data Latam, and the Data Science Hangout. Attendees of the R/Medicine conference raved about these communities. While many of the networking opportunities are virtual, there may be opportunities to meet with your fellow community members in your area.

After the conference, I attended my first virtual Data Science Hangout on May 21st. This is a weekly community call for anyone who works with data. There are new speakers from a variety of institutions who talk about their work and their experiences in this field. The virtual chatroom is very active and full of welcoming community members. You can check the upcoming speakers on the Data Science Hangout webpage. There is also a Discord server for the community to connect. After the Data Science Hangout ended, the conversation continued in the community server.

 

I would like to thank the R/Medicine community for welcoming new attendees, accepting users of all skill levels, and introducing me to additional R communities and resources outside the conference. I am very grateful to have other lifelong learners in my circle while I continue to develop how I use R in my work.