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Empowering Healthcare with R: Javier Orraca-Deatcu’s Journey from Finance to Predictive Health Models

By Blog

Javier Orraca-Deatcu of the Southern California R User Group (SoCal RUG) highlighted his work at a health insurance company for quality of life improvements through data science models. He uses R for predicting health issues in Medicare and Medicaid populations and alerting their care management teams about preventive measures and lifestyle changes to prevent these issues. He shares in-depth insight into how R has the potential to impact the lives of the elderly population. He also advises R users to start their own R user groups within their companies to expand their network.

Javier has a Bachelor’s degree in Management from the Georgia Institute of Technology. He also holds a Master’s in Business Analytics from the University of California, Irvine (UCI). He works as the Lead Machine Learning Engineer at Centene Corporation. Javier co-organizes the SoCal RUG and is also a co-founder of the Centene R Users Group. 

Please share about your background and your involvement in the R Community. What is your level of experience with the R language?

My traditional background before I pivoted into data science was financial modeling. I was doing valuations and assisting with the lifecycle of mergers and acquisitions. At the time, I was maximizing the capabilities of Microsoft Excel and Microsoft Access. Around 2015, I started hearing chatter about “data science” and became interested in how to augment my financial forecasts and simulations with code. I quit my job, returned to graduate school, and was able to dedicate all of my time to learning about business analytics, data science, and R.

The Southern California R Users Group conducts an annual hackathon, which they host in collaboration with the UCI. I was enrolled in the Master of Business Analytics program at the UCI, and I joined the hackathon with a team of classmates. That’s when I met the organizers of SoCal RUG, and it was great to network with like-minded members of the data science community.

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

I work for a healthcare insurance company, Centene, and it was pretty exciting to see us become a Fortune 25 corporation earlier this year. Our core business is to manage care insurance products covering mostly government-sponsored healthcare insurance like Medicaid and Medicare. We are fortunate to have robust access to health data since we manage our members’ care. As a data scientist and MLE at Centene, it’s exciting that I can apply modeling techniques to support quality-of-life improvements, such as early disease identification.

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

The big appeal is to network with a very diverse group of professionals in many different industries. The opportunity to come together and brainstorm problems is invaluable. We provide technical workshops and monthly meetups with new information to learn from our presenters and passionate members of the R community. 

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

I’m doing less data storytelling these days with interactive visualizations and web apps, but the evolution we are seeing with Shiny and new opinionated Shiny frameworks has been a delight. Shiny is quickly maturing as a web app framework, and it’s becoming, in my opinion, a go-to enterprise web app framework with more and more recognition. In addition, the tidyverse and tidy syntax have made it much easier for non-programmers (people without a computer science or software engineering background) to adopt R for their business needs.

Throughout grad school and professionally, I have had exposure to several other languages, including Python and Julia. But for data analysis and manipulation, it’s just so easy to do with R. The rate at which the tidymodels framework matures has also been impressive. This modeling framework acts as a sort of meta-engine that helps data scientists develop reproducible, end-to-end machine learning workflows and pipelines. The ability to develop a modeling workflow purpose-built for fast iteration, consumption at scale, and production are all big wins for corporate data scientists and MLEs.

Anything else you would like to share with R Users around the globe?

For R enthusiastic professionals who regularly educate their coworkers about modern use cases for R. I recommend starting an internal R user group at your company — it’s a great way to network internally and share knowledge. I helped start the Centene R Users Group in 2019, and in six months, I saw our monthly meetups grow from less than 10 people to over 100 participants. I’ve met a lot of new teams and groups that I would have otherwise never had the opportunity to come in contact with.

A Continental Movement: LatinR Event is Face-to-Face in Montevideo, Uruguay This Year

By Announcement, Blog

LatinR 2023 is being held October 18-23, 2023, in Montevideo, Uruguay. Presentations are held in Spanish, Portuguese, or English. Register now! 

LatinR was founded in 2017, Natalia da Silva, Riva Quiroga, and Yanina Bellini Saibene are the actual chairs in the 2023 edition. 

The inaugural LatinR event kicked off in Buenos Aires, Argentina, followed by a second chapter in Santiago de Chile, Chile. These early events were more than just conferences; they were festive gatherings that celebrated the robust bonds the community had built over the years.

It wasn’t always easy. Da Silva, Quiroga, and Saibene have talked about the trials and tribulations of building such a successful and energetic R-focused conference.

The R Consortium has regularly been an enthusiastic sponsor of LatinR, and this year is no exception.

During COVID-19,  Zoom rooms replaced physical auditoriums, but the essence of shared learning and vibrant exchange persevered. But let’s face it, we’ve all missed the face-to-face interactions, the hallway conversations, and, of course, the local flavors of each host city. That’s why there’s a buzz of anticipation for this year’s event: LatinR is returning to its roots with an in-person conference on October 18-20th, 2023. Pack your bags because we’re heading to Montevideo, Uruguay!

LatinR has evolved into the cornerstone event for the R community in Latin America, a testament to what can happen when a community comes together with purpose and enthusiasm. The Montevideo edition of LatinR isn’t just another conference; it’s a homecoming, a celebration of how far we’ve come, and a toast to the exciting road ahead. So, whether you’re an R newbie or a seasoned data scientist, LatinR promises to be a confluence of minds, methods, and, most importantly, people united by a common language, both in code and culture.

For more details and to catch all the updates, don’t forget to visit

Register here!

Hope to see you there!

Utilizing R for Reproducible Open Science Research in Tucson, Arizona

By Blog

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.

R User Group Philippines Turns 10

By Blog

The R User Group-Philippines (RUGPH) 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?

R Users Group-Philippines 10th Anniversary 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 accounts are awarded based on the intended use of the funds and the amount of money available to distribute. We are now accepting applications!

First Publicly Available R-Based Submission Package Submitted to FDA (Pilot 3)

By Announcement, Blog

The R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The FDA CDER staff are now able to begin their evaluation process. All submission materials can be found at: 

The pilot 3 test submission is an example of an all R submission package following eCTD specifications. These include the installation and loading of the proprietary {pilot3} R package and other open-source R packages, R scripts for the analysis data model (ADaM) datasets from pilot 3 and tables, listings, figures (TLFs) from pilot 1, analysis data reviewer’s guide (adrg), and other required eCTD components. To our knowledge, this is the first publicly available R-based FDA submission package, which includes R scripts to generate ADaM datasets and TLFs. We hope this submission package and our learnings can serve as a good reference for future R-based regulatory submissions from different sponsors. Additional agency feedback will be shared in future communications.  For any future questions, you may contact the pilot 3 team here:

The working group also began working on a pilot 4 project to explore the use of novel technologies such as Linux containers and WebAssembly software to bundle a Shiny application into a self-contained package in order to facilitate a smoother process for transferring and executing the application. Stay tuned for more about pilot 4 in the future.

For past announcements on pilot 1 and pilot 2, see below.

Announcement of the R Consortium R submission pilot 1:

Announcement of the R Consortium R submission pilot 2, an R based test submission with a shiny component:

About the R consortium R submission working group

The R Consortium R Submissions Working Group is focused on improving practices for R-based clinical trial regulatory submissions.

To bring an experimental clinical product to market, electronic submission of data, computer programs, and relevant documentation is required by health authority agencies from different countries. In the past, submissions have been mainly based on the SAS language. 

In recent years, the use of open source languages, especially the R language, has become very popular in the pharmaceutical industry and research institutions. Although the health authorities accept submissions based on open source programming languages, sponsors may be hesitant to conduct submissions using open source languages due to a lack of working examples.

Therefore, the R Consortium R Submissions Working Group aims at providing R-based submission examples and identifying potential gaps during submission of these example packages. All materials, including submission examples and communications, are publicly available on the R consortium Github page:

The R consortium R submission working group includes members from more than 10 pharmaceutical companies, as well as regulatory agencies. More details of the working group can be found at:

The R consortium R submission working group is open to anyone who is interested in joining. If interested, please contact Joseph Rickert at

R Validation Hub’s {riskassessment} Application – Mini Series Part 2

By Blog

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!

R Validation Hub’s Risk Metric Application and Risk Score – Mini Series Part 1

By Blog

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. 

Spatial Data Science Using R in Berlin, Germany

By Blog

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.

Grants For R Language Infrastructure Projects Available Now!

By Announcement, Blog

Round two is here! The R Consortium Infrastructure Steering Committee (ISC) orchestrates two rounds of proposal calls and grant awards per year to fortify the R ecosystem’s technical infrastructure. We have one key goal: to make meaningful infrastructure improvements that serve the R community. 

ISC’s Call for Proposals opens on September 1, 2023. Send in your submission! 

We’re reaching out to the extended R community to tap into your expertise and insights. What areas do you think need attention to extend R’s capabilities? Do you see emerging domains where R could significantly impact? Whether in Climate Science, Engineering, Finance, Medicine, or any other discipline, your ideas could spark innovations that advance the field and broaden the R community. 

Technical Infrastructure projects that have been funded include:

  • R-hub is a centralized tool for checking R packages
  • Testing DBI and improving key open-source database backends.
  • Improvements in packages such as mapview and sf 
  • Improving Translations in R
  • Ongoing infrastructural development for R on Windows and macOS

Social Infrastructure projects include:

  • SatuRDays bootstrapping a system for local R conferences.
  • Data-Driven Discovery and Tracking of R Consortium Activities

The ISC is interested in projects that:

  • Are likely to have a broad impact on the R community.
  • Have a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it into smaller chunks (a good example is with the DBI/DBItest project submission, where multiple proposals came in overtime to address the various needs).
  • Have a low-to-medium risk with a low-to-medium reward. The ISC tends not to fund high-risk, high-reward projects.

Key Dates for 2023

Second Grant Cycle: September 1 to October 1, acceptance by November 1, contract by December 1.

Review Process

The Chair of the ISC and committee members will review all proposals. Results will be announced as per the schedule above, and all funded projects will feature on the R Consortium blog.

Final Thoughts

Let’s enrich the R landscape, amplifying its utility across various sectors. The time is ripe, and your ideas could be the seeds of transformation. We look forward to your active participation.

Apply now and be part of shaping the future of R! You can read more about ISC Grant Proposal application process here.

Use of R for Pharma in Rosario, Argentina

By Blog

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:

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