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The R-Consortium recently talked to Adriana Picoral of the R-Ladies Tucson about the diverse R community in Tucson, Arizona. Adriana founded the R-Ladies chapter in 2018 and has been actively involved with the local R Community. 

The group is hosting a virtual “Reproducing Open Science Research-2” event on September 15, 2023. The event focuses on reproducing an open science research paper in linguistics with experimental data. 

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

I am an assistant professor of practice at the Department of Computer Science at the University of Arizona. My educational background includes a bachelor’s degree in computer science and a Ph.D. in applied linguistics.

My journey with R and involvement with the R community began during my graduate studies. When I was a doctoral candidate, my research focused on quantitative analysis. As a result, I had experience with other programming languages, but I used R for the first time in 2014 for my research. Unfortunately, Tucson had no R-Ladies chapter, so I wanted to establish a local presence. Therefore, in 2018, I founded the R-Ladies Tucson.

It has been five years since I started this chapter. Many of our events initially focused on linguistics and applied linguistics, which was my study area as a graduate student. In 2020, after successfully defending my thesis, the onset of the pandemic forced our group to shift our events online. This change helped us connect with people from all over the US. We had “Tidy Tuesday” challenges at our weekly virtual meetings with selected datasets.

Can you share what the R community is like in Tucson? 

The R community here in Arizona and Tucson is well established. I’m part of the University of Arizona, which has many Data Science programs across different departments and colleges. Although Python plays a role, the predominant focus in these programs is R. I also co-direct an initiative called the Data Science Ambassadors program, which engages graduate students. 

The R community is diverse regarding academic backgrounds, including individuals from the biology, statistics, and computer science fields. I have been the ambassador for Women in Data Science, which is also focused on R. It is diverse in terms of backgrounds but maybe not as diverse in gender identification, but we are working towards that.

You have a Meetup on Reproducing Open Science Research 2. Can you share more on the topic covered? Why this topic? 

In this meetup, we will replicate open science research. This meetup is the second event of the Reproducing Open Research Series. We chose the paper “Learning, Inside and Out: Prior Linguistic Knowledge and Learning Environment Impact Word Learning in Bilingual Individuals” within the linguistics domain and features experimental data.

We will review the paper’s analysis, facilitating its replication while educating the participants about the process. Open science is really important, and having the data available is nice. Before working on your data, engaging with external data often provides a valuable learning opportunity.

Who was the target audience for attending this event? 

R-Ladies’ events ‌attract women, but we also welcome participants identifying as other genders. The event is aimed at graduate students lacking quantitative analysis training, focusing on language data and open science. So, I would say the target audience is women and graduate students.

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 unable to attend physical events in the future? 

After the pandemic, having experienced Zoom, we prefer to host most of our events online. Virtual events are much more inclusive as participants and the speaker don’t need to commute. Another proper technique that helps participants who do not have software installed on their systems is using Posit Cloud. We use Posit Cloud with our Rstudio ID, so they don’t have to install anything. I demonstrate all the steps from the beginning on how to start a new project on Posit Cloud and go from there. 

I also made a tutorial beforehand for the participants. We don’t record our sessions, as it encourages attendees to participate more openly and makes the events more interactive.

The R User Group-Philippines (RUG–PH) celebrated its 10th anniversary on the 16th of August. The group marked the occasion with its first physical event since the pandemic, and it highlighted the group’s progress over the past decade. 

The RUG-PH hosted 115 events in the past decade, making it one of the most persistent RUGs. During the pandemic, many RUGs struggled to remain active; however, RUG-PH continued with online events.  

Joe Brillantes and Michelle Alarcon are the two faces behind the group’s success and brilliant track record. The R Consortium recently talked to Joe and Michelle regarding the group’s evolution. They shared their journey with R in their work and their experience keeping the group up and running for a decade. They have also witnessed a growing acceptance of R in the Philippines and the industry. 

Please share about your background and involvement with the RUGS group

Michelle: My name is Michelle Alarcon, and I have been an analytics practitioner since 1999. I used commercially available software at university and brought it with me to the jobs I had. Open source tools were a minor part of my toolkit in practice. In 2013, I founded my analytics consulting firm, Z-Lift Solutions. As a consultant, I aimed to avoid being bound to software vendors that clients might have purchased, such as SAS or SPSS. So, I began searching for a versatile tool that would allow us to offer consultation without being locked into any particular vendor.

That’s when I discovered R, which was unpopular in the Philippines back then. However, R was gaining popularity among practitioners striving to learn analytics without heavy investments. I asked a former classmate from my old school, the University of the Philippines School of Statistics, for advice when I started my consultancy. I wanted to know the tools used by the new generation of statisticians. To my surprise, the curriculum remained largely unchanged over two decades. This realization led me to explore alternatives.

My efforts to ensure a consistent talent pool for consultancy drove me to get connected with Edward Santos, a key figure in the history of the R Users Group. I also connected with Joselito Magadia, a university professor who played a crucial role in the Philippines’ CRAN network. Through Edward and Joselito, I got introduced to the R Users Group. Our annual R Users Group anniversary celebrations often include Edward.

Joe: I’m Joe Brillantes, and I first encountered R in 2007 during my studies in the US. My mathematical statistics instructor introduced me to it. While I initially leaned towards software like MATLAB or Maple, my perspective shifted when I returned to the Philippines. Because of a tight budget, I had to create a portfolio optimization model for a shipping company without using expensive software. R emerged as a more feasible solution.

When I started using R, there wasn’t a community of R Users in the Philippines. Since I was new to it, I asked many questions, mainly to my classmates or other R users in the US. And then, someone started a Google group on R users specific to the Philippines, and that’s when I joined it. It seemed very appealing to me, as I no longer needed to ask people in the US and then wait for them to respond because of the different time zones. 

We did not start the Philippines R Users Group (RUGS); credit goes to Edward Santos. However, I co-organized the group alongside Michelle for the past decade. My commitment to R persisted throughout my career, replacing MATLAB and other software in my toolkit.

Can you share what the R community is like in the Philippines?

Michelle: In the past decade, I’ve witnessed an increasing acceptance of open source programming tools in the Philippines. In 2013, awareness of open source options was scarce. AWS was pivotal in promoting open source use, joined by Java‘s long-standing presence. However, the acquisition of Revolution Analytics by Microsoft was a turning point. Microsoft, on our request, provided us space for hosting our meetups, which were happening at coffee shops before that. Microsoft’s support showcased a shift toward open source.

A decade later, R has gained acceptance as a staple tool for data scientists and analysts, often mentioned alongside Python. Our user group collaborates with other tech communities, like AWS and Python. Interest in R has increased over the years. However, our meetup attendance has plateaued, maintaining a consistent level of participants even during the pandemic when we held virtual events. 

Joe: Today, data science and analytics practitioners in the Philippines typically gravitate toward Python or R. Both languages are considered essential tools. The open source nature of R fosters acceptance within organizations. If an employee is proficient in R, they typically approve its usage due to familiarity. However, an area for further growth is in deploying models. The deployment of predictive and prescriptive analytics models in production remains limited. R is commonly used in data science but not widely in production environments.

You had a Meetup RUG_PH 10th Anniversary. Can you share some details of this event?

Joe:  We recently celebrated the R Users Group – Philippines’ 10th anniversary. We wanted it to be special, so it was also the first time we organized an in-person meetup since the pandemic ended. There were around 20 people who attended, half of whom had attended numerous meetups in the past, while the remaining were first-timers. We were pleasantly surprised that a substantial portion of attendees were first-timers because that indicated that R usage and user groups still have significant growth potential in the Philippines.

Because it’s an anniversary, the primary topic was to review how we’ve grown and changed over the years. Our event venues changed from cafes to company offices to online. Our participants became more diverse in terms of backgrounds and moved from predominantly analysts to a mix of data engineers, data scientists, software engineers, and managers. Participants come from Metro Manila to other areas in the Philippines and even abroad. We had dinner, an icebreaker, a raffle, and networking at the event.

Some participants also volunteered to discuss data visualization for scientific publication and causal inference in future meetups. We will promote these meetups to the community for future events through our Meetup page, Slack workspace, and Facebook page. We’re always happy to see familiar faces and to meet new R users.

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?   

Joe: We encourage presenters to share their materials soon after the meetup. They usually share them through GitHub or shared drives like Google Drive, OneDrive, or Dropbox. We started recording the meetups and plan to share them on our Facebook page. We do these to help attendees continue learning, reach those who couldn’t make it, and encourage future attendance.

We’re still exploring the best way to do hybrid meetups. People attending online usually feel left out in hybrid meetings because of low-quality equipment and lousy internet. Speakers usually select the in-person format as it requires less time and effort than preparing for a hybrid setup. We’re still figuring out the best way to have hybrid meetups that do not isolate online attendees. In the meantime, we ask presenters their preferred format: in-person, online, or hybrid. The voted-out meetup setup would likely be because the presenters are the best people to decide how their content can be best communicated.

I would also like to take this opportunity to reach out to RUGs around the globe. We at the RUG-PH are excited to be part of the global R community through the R Consortium. We look forward to collaborating with other RUGs and welcoming participants from around the globe. 

How do I Join?

R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups around the world organize, share information and support each other. We have given grants over the past four years, encompassing over 65,000 members in 35 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. We are now accepting applications!

The R Validation Hub – a working group established within the R Consortium to support the adoption of R within a biopharmaceutical regulatory setting – held a two-part mini-series about their {riskmetric} package and {riskassessment} application. 

The full talk is available here. Part 1 is available here.

In the second part of the mini-series, the team explained in depth how the {riskassessment} application helps those making “package inclusion” requests for GxP environments, which means the application empowers users to assess package risks themselves before making an IT request. It arms them with the criteria they need to show a package meets (or fails to meet) their organization’s unique set of requirements. 

The highlight of the talk was covering upgrades and improvements made to the application. 

Here’s a breakdown of what’s new:

• Valuable Enhancements: Aesthetic & functional enhancements were made to the ‘Report Builder’ and ‘Database Viewer.’
• In-depth Analysis: The app now boasts enhanced support for analyzing package dependencies.
• Tailored Customizations: More organizational-level adjustments, including a configuration file for a bespoke experience.
• Admin Capabilities: Admin users now have the power to modify roles and privileges. This ensures a seamless workflow by determining who should partake in the review processes.

• Explore with Ease: A new feature allows users to delve into the source contents of a package through a file browser, making exploration straightforward and comprehensive.

The R Validation Hub team also shared a sneak peek of some exhilarating features, such as {riskscore}; there’s also more in store for package exploration within the app.

A Special Note on GSK’s Contributions

GSK Collaborators have generously contributed code that enhances the user experience. This new feature will enable users to delve deeper into exported functions. Imagine perusing function-level source code, documentation, and tests in one unified and easily navigable user interface. Thanks to GSK, this will soon be a reality!

The R Validation Hub – a working group established within the R Consortium to support the adoption of R within a biopharmaceutical regulatory setting – held a two-part mini-series about their {riskmetric} package and {riskassessment} application. 

The full talk is available here. Part 2 is available here.

In Part 1, the R Validation team talked about defining risk in software quality. Equally important is understanding the intended use of the software. The {riskmetric} package fulfills the crucial need to assess the quality of R packages, ensuring they adhere to the highest standards.

{riskmetric} isn’t just a tool; it’s a comprehensive system. For users, it provides a well-defined workflow and offers insights into the package’s internals, aiding in understanding its functioning better.

Mapping the Future – Roadmap:

The {riskmetric} package is being actively worked on and improved. The major features in the upcoming roadmap include:

• Ease of Use: The focus is on enhancing user experience. A more intuitive interface coupled with informative messages and functions to generate straightforward reports is on the horizon.
• Metric Completion: The goal is to provide many metrics from various package metadata sources.

• Optional Third-party Metric Inclusion: An API that supports metrics reliant on additional packages, giving users a choice to use them.
• Cohorts: Evaluating the risk associated with a group of packages, treating them as a unified entity.

Metrics aren’t just about numbers; they’re about quality and relevance. In the talk, the team shed light on the guidelines and best practices for proposing or designing package metrics, complemented with examples for clarity.

Introduction of {riskscore} 

The team introduced {riskscore}, a repository that stores the results of riskmetric runs on CRAN. It is envisioned as a community resource with multiple aims:

• Contextual Scoring: Helping users decipher scores, distinguishing between what’s deemed “good” or “bad.”
• Benchmarking: Enabling development teams to benchmark scoring weight algorithms with historical results.
• Trend Analysis: create an interesting dataset for package quality/risks analysis. 

The Berlin R User Group fosters a diverse and vibrant R community in Berlin. Rafael Camargo shared some insights from his experience regarding the potential of R and some anecdotes for organizers of RUGs. The Berlin RUG is currently looking for sponsors to host their physical events, and companies interested in hosting the group can contact Rafael. 

The group is hosting a physical event using R for spatial data analysis on September 26, 2023.

Rafael is a Spatial Data Scientist working at Quantis as a Sustainability Expert. He has a Bachelor’s in Environmental Studies and a Master’s in Environmental planning.

Please share your background and involvement with the RUGS group.

I was first introduced to R during my Master’s studies in 2016. A Ph.D. student encouraged me to use R for data analysis, and I grew fond of it.

Later, during my Master’s thesis, I used it as well. After completing my Master’s degree, I used to work for WWF, a nature conservation organization. My responsibilities included maintaining a web tool and conducting spatial analysis.

In my job, I noticed repetitive tasks which I found tedious. I started automating tasks and report generation using R Markdown and, later, Quarto to reduce repetition. I am one of the early adopters of Quarto and heavily use it for my work. I work for a consultancy firm, and again, with a strong focus on automating processes. I use Notebooks in my work for documentation and reproducibility. 

Can you share what the R community is like in Berlin? 

The R community in Berlin is very welcoming and has this spirit of helping each other.  I joined the Berlin RUG around the same time I started using R. ‌The group hosted monthly meetings with talks on a diverse range of topics by speakers from industry, academia, and freelancers. Some speakers offered courses in R and used this opportunity to market their courses while giving back to the community. 

Just before COVID hit, there was a shift towards machine learning topics. I think this shift mirrored the industry’s growing interest in machine learning applications. There are more speakers keen to give machine learning-related talks. The audience also grew, and we saw more people joining our meetups who were new to R but eager to learn about machine learning.

Within our group, we see members from diverse backgrounds. For example, small financial institutions use R to optimize interest rates through bank APIs, professionals in biomedicine doing statistics, health insurance exploring spatial analysis, and experts in real estate using R for house price prediction.

Overall, it’s a pleasant mix of academia and applied industry. Companies using machine learning are considering R for industry applications.

You have a Meetup on Spatial Data Science with R: {sf}, {stars}, and other packages. Can you share more on the topic covered? Why this topic? 

I’m particularly excited about our upcoming meetup on Spatial Data Science with R. I’ve been advocating for this topic. We’re fortunate to have Edzer Pebesma, a prominent developer and maintainer of various R packages for spatial analysis. He’ll deliver a talk at the end of September, covering material from his latest book, “Spatial Data Science using R,” and the latest advancements in the field. And, of course, leveraging the packages he has developed over the years.

Any tips you would like to share with other R Users Group Organizers that can be helpful for hosting successful events?   

I can share a few insights from my experience as a RUG organizer. When I joined as a participant, our meetups were hosted at a company-sponsored venue with a dedicated room accommodating up to 50 people. They also generously provided drinks and snacks for the participants. 

After joining the organizing committee, I learned about the company’s flexibility and willingness to accommodate our event requests. We were somewhat reactive,  with potential speakers approaching us with proposed dates, and we coordinated with the company to find a suitable date. I would negotiate with the speaker to ensure the talks were concise, with enough time for discussion. 

Fortunately, the company managed the event logistics, including venue and refreshments, so my role was minimal. However, they stepped down as sponsors last year after COVID-19, and we are actively seeking new sponsors. This has been particularly difficult due to our busy schedules. So, I would recommend organizers be more proactive in reaching out to sponsors and not rely on only one sponsor.

Additionally, I would like to take this opportunity to reach out to any companies in Berlin who can offer us space to host our events. 

Would you like to add anything else for the readers?

In the past 5 years, engaging with several global organizations and multinational corporations, I realized that many organizations outside the research, software development, e-commerce, or marketing domains also rely heavily on data-driven solutions.  However, ‌I see a lack of awareness among organizations about the true potential of R. Many people are surprised to know that R can be used for domains beyond statistics when I talk about my work with R. Many global organizations still rely on manual work using Excel, which is much prone to errors. They are unaware of R’s capabilities and recent developments. I wish more people knew about the user-friendly functionalities of Tidyverse, Posit Connect, and other tools available in R.

Ivan Millanes from the R en Rosario recently talked to the R-Consortium. He shared the group’s vision to create an inclusive knowledge-sharing platform for a diverse R community in Rosario. In Argentina, the group welcomes participants and speakers at all experience levels. Ivan also uses R at work and builds Shiny applications for the pharmaceutical industry. 

Ivan co-organizes R en Rosario and is one of the group’s founding members. He completed his Bachelor’s in Statistics at the National University of Rosario. Not to mention, Ivan has achieved multiple certifications in Machine Learning. Currently, he works as a R/Shiny developer at Appsilon. 

R en Rosario First Anniversary Celebrations

Please share your background and involvement with the RUGS group.

My educational background is in Mathematics and Statistics. I first used R around six years ago during my studies and have since gained experience in R through different jobs. I have worked in various industries like marketing, healthcare, and insurance. I am currently working in the Pharmaceutical industry. 

R en Rosario Founding Members

We started the R en Rosario User Group a couple of years ago, Argentina’s first R User Group. Later, other cities also started their R Users Groups, e.g., Buenos Aires. We hosted a few virtual meetings during the pandemic but stopped after a few months. Now that everything is returning to normal, we plan to resume our meetings. We would like to host speakers from different industries who use R for their work. A networking session would follow these talks. 

R en Rosario First Meeting

What industry are you currently in? How do you use R in your work?

I currently work in Pharma, where we develop Shiny applications using R.

The applications we develop have a similar workflow: we connect to SQL databases and produce some outputs the business needs in the form of PDFs or Word documents based on user choices for different parameters.

We use the Rhino package from Appsilon to develop the applications, as it provides a great framework for developing high-quality applications. We also use:

• R Markdown and officer to generate PDF and Word reports from the app
• ggplot to create plots
• tidyverse packages (such as dplyr) to process data

One application we developed generates annual reports of different incidents in the laboratory. Before we developed the application, this process was manual and took time. With this app, they have a relatively simple interface where they can select the data they want to see in the report. They can download the reports and also get it sent to their system.

Why do industry professionals come to your user group? What is the benefit for attending?

People from a diverse range of backgrounds attend our meetups. Some government officials use R to analyze traffic data for public services. Some people from the farming industry use R to interpret satellite images to understand crops. 

Even though statisticians founded this group, its purpose is to provide a platform for people from various backgrounds to learn R and use it for their work. We usually have around 20-30 people attending our meetups, and different companies provide space to host our meetups.

Networking is an important part of our meetups, allowing members to learn more about each other. 

We also do not have any limit on the topics for these talks, and anyone who feels like sharing their work in R with the audience can give a talk. So everyone, at any experience level, is more than welcome to give a speech. We are not experts and are not looking for only experts to give talks. The idea is for people from different backgrounds to come together and learn from each other. 

R en Rosario Meeting Hosted by a Company