We are proud to announce that the R Consortium has awarded RECON a grant for $23,300 to develop the RECON COVID-19 challenge, a project aiming to centralise, organise and manage needs for analytics resources in R to support the response to COVID-19 worldwide.
These resources will permit to expand our initial preliminary collection of github issues to create a user-friendly web platform gathering R tasks reflecting needs from different projects and groups, and facilitate contributions from the wider R programming community.
We are looking for two consultants (see ‘We need you!’ section below), including:
a project manager to drive the project forward
a web developer to create the website
The RECON COVID-19 challenge in a nutshell
The RECON COVID-19 challenge aims to bring together the infectious disease modelling, epidemiology and R communities to improve analytics resources for the COVID-19 response via a website which will provide a platform to centralise, curate and update R development tasks relevant to the COVID-19 response. Similar to the Open Street Map Tasking Manager (tasks.hotosm.org), this platform will allow potential contributors to quickly identify outstanding tasks submitted by groups involved in the response to COVID-19 and ensure that developments follow the highest scientific and technical standards.
While this project is aimed at leveraging R tools for helping to respond to COVID-19, we expect that it will lead to long-lasting developments of partnerships between the R and epidemiological communities, and that the resources developed will become key assets for supporting outbreak responses well beyond this pandemic.
The first COVID-19 Data Forum, co-sponsored by the Stanford Data Science Institute and the R Consortium, was held May 14, 2020. The forum used Zoom as a way to connect remote specialists, present information, and conduct a Q&A session so that participants could ask questions and give opinions.
UPDATED – Full video recording here
Close to 200 people attended, watching a range of experts cover a level of detail around COVID-19 that is not available through newspapers, and asking questions covering science and policy.
From the COVID-19 Data Forum site:
The COVID-19 pandemic has challenged science and society to an unprecedented degree. Human lives and the future of our society depend on the response. That response, in turn, depends critically on data. This data must be as complete and accurate as possible; easily and flexibly accessible, and equipped to communicate effectively with decision-makers and the public.
The COVID-19 Data Forum is a project to bring together those involved with relevant data in a series of multidisciplinary online meetings discussing current resources, needed enhancements, and the potential for co-operative efforts.
Speakers (full slides for each presentation available soon)
Orhun Aydin, Researcher and Product Engineer, ESRI
Ryan Hafen, data scientist consultant with Preva Group, and adjunct assistant professor, Purdue University
Alison L. Hill, Research Fellow and independent principal investigator at Harvard’s Program for Evolutionary Dynamics.
Noam Ross, Senior Research Scientist, EcoHealth Alliance
The Stanford Data Science Institute, which aims to give Stanford faculty and students the tools, skills and understanding they need to do cutting-edge research, is joining with the R Consortium to build the COVID-19 Data Forum series.
The COVID-19 Data Forum series is an ongoing set of online meetings that connect multidisciplinary topic experts to focus on data-related aspects of the COVID-19 pandemic modeling process such as data access and sharing, essential data resources for modeling and how we can best support decision making.
The first half of the meeting is a public webinar and all are welcome to attend.
At the Linux Foundation, we have been studying robust, scalable virtual events platforms that we can not only use for our own R Consortium events, but that we could extend as a resource to the R community.
Here is the current state of our evaluation. We’ve covered 86 virtual event platforms, and come up with a list of 4 finalists. Since specific circumstances and goals for events will always vary, we expect that there will never be a one-size-fits-all solution.
The four finalists are:
Best for large events with high budgets requiring a virtual conference experience with few compromises
Best for medium to large events with smaller budgets that want to offer a 3D environment/booth experience
Best for any size event where attendee networking tools are a priority and sponsor ‘booths’ aren’t required
QiQo is best for smaller technical gatherings that don’t need all the bells and whistles of an industry event focus, a great option for developer meetings and hackathons
The good news is that for those events that can no longer safely take place in person, virtual events still offer the opportunity to connect within our communities to share valuable information and collaborate. While not as powerful as a face-to-face gathering, a variety of virtual event platforms available today offer a plethora of features that can get us as close as possible to those invaluable in-person experiences. Thanks to our community members, we’ve received suggestions for platforms and services that the events team has spent the past several weeks evaluating.
After researching a large number of possibilities over the last few weeks, the Linux Foundation has identified four virtual event platforms (and a small-scale developer meeting tool) that could serve the variety of needs within our diverse project communities. Our goal was to determine the best options that capture as much of the real-world experience as we can in a virtual environment for virtual gatherings ranging from large to small.
If you are considering a virtual alternative for your R community meetup or event, please contact us. We may be able to help!
By Rachael Dempsey, Senior Enterprise Advocate at RStudio / Greater Boston useR Organizer
Last month, the Boston useR Group held our very first virtual meetup and opened this up to anyone that was interested in joining. While I wasn’t sure what to expect at first, I was so happy with the turnout and reminded again of just how great the R community is. Everyone was so friendly and appreciative of the opportunity to meet together during this time. It was awesome to see that people joined from all over the world – not just from the Boston area. We had attendees from the Netherlands, Spain, Mexico, Chile, Canada, Ireland, and I’m sure many other places!
Our event was a virtual TidyTuesday Meetup held over Zoom, which can hold up to 100 people without having to purchase the large meeting add-on. (If you’re worried about the number of people being over this, keep in mind that often half the people that register will attend.)
This was our agenda:
5:30: Introductions to useR Meetup & TidyTuesday (Rachael Dempsey & Tom Mock)
5:35: Presentation #1 – Meghan Hall: “Good to Great: Making Custom Themes in ggplot2”
5:50: Presentation #2 – Kevin Kent: “The science of (data science) teaching and learning”
6:00: Introduction to R for Data Science Slack Channel – Jon Harmon
6:05: Breakout into groups to work on TidyTuesday dataset – groups will be open for two-hours but you can come and go as you want!
7:30: Come back together to the Main Room for an opportunity to see a few of the examples that people would like to share
If you’re thinking of keeping your monthly event and want to host it virtually, I’ve included a few tips below:
Find someone (or multiple people) to co-host with you!
Thank you, Kevin Kent and Asmae Toumi! Kevin, a member of the Boston useR Group was originally going to be the lead for our in-person TidyTuesday meetup and posted about the meetup on Twitter, where we both met our other co-host, Asmae Toumi. Asmae then introduced us to one of our presenters, Meghan Hall. Having co-hosts not only made me feel more comfortable, but gave me a chance to bounce ideas off of someone and made it much easier to market the event to different groups of people. While I often share events on LinkedIn, Kevin and Asmae have a much bigger presence on Twitter. Aside from your own meetup group and social media, another helpful place to find potential co-hosts may be on the events thread of community.rstudio.com. Instead of co-hosting, you could also just ask people if they would be willing to volunteer to help at the meetup. Thank you to Carl Howe, Jon Harmon, Josiah Parry, Meghan Hall, Priyanka Gagneja, and Tom Mock for your support. If I can help you with finding volunteers, please don’t hesitate to reach out on LinkedIn.
Have a practice session on Zoom!
The day before the event we held a practice session on Zoom to work out a few of the kinks. As we were hosting a TidyTuesday meetup, we wanted to be able to meet in smaller groups too, as we would if we were in-person. I had never used Zoom breakout rooms before and wanted to test this out first. After the initial presentations, we broke out into 7 smaller groups. These groups worked well to help facilitate conversation among attendees. During the test, we confirmed that you can move people from different breakout groups if needed. This was helpful for keeping the groups even as some attendees had to leave before the end of the event.
Have a Slack Channel or a way for people to chat if they have questions
During the meetup, we used the R for Data Science Online Learning Community Slack Channel as a venue to ask questions and share examples of what people were working on. You can join this Slack channel by going to r4ds.io/join. We used the channel, #chat-tidytuesday which you can find by using the search bar within Slack.
Accept that it won’t be perfect
You can practice and plan how you want things to go, but I think it’s helpful to recognize that this is the first time doing this and it’s okay if things aren’t perfect. For example, we were going to create separate breakout groups based on people’s interests and have everyone use a Google doc to indicate this at the start. While it was good in theory, we determined this would be a bit too hard to manage and complicate things so I just automatically split people up into the 7 different groups. It wasn’t perfect, but it worked!
Think about Zoom best practices
This came up in discussion during our practice call and I think we’ve all seen recently that there can be a few bad-actors out there trying to ruin open meetings. @alexlmiller shared a few tips on Twitter that I’d like to cross post here as well.
You can start with the Main Settings on your Zoom account and do the following:
1) Disable “Join Before Host”
2) Give yourself some moderation help by enabling “Co-Host” – this lets you assign the same host controls to another person in the call
3) Change “Screen sharing” to “Host Only”
4) Disable “File Transfer”
5) Disable “Allow Removed Participants to Rejoin”
And also to make the overall experience a little nicer:
1) Disable “Play sounds when participants join or leave”
2) Enable “Mute participants upon entry”
3) Turn on “Host Video” and “Participants Vide” (if you want that)
One more thing, if you want to split meeting participants into separate, smaller rooms you have to enable “Breakout Rooms”.
Market your event on social media
Once your event is posted to meetup, share it with others through multiple channels. Maybe that’s a mix of your internal Slack channel, Twitter, your LinkedIn page and/or the “R Project Group” on LinkedIn …or wherever you prefer to connect with people online. Keep in mind that this could be a different audience than your usual meetups because it’s now accessible to people all over the world. Ask a few people to share your post as well so that you can leverage their network as well.
Reflecting back on our meetup, some of us found that with the use of Zoom breakout groups and a Slack channel our event was surprisingly more interactive than our actual in-person meetups. It was also an awesome opportunity to do something social and get together with others from the community during this crazy time. If you have any tips from your own experiences, please let me know and don’t hesitate to reach out if I can assist in any way. Hope this helps!
Esri, international supplier of geographic information system software, web GIS and geodatabase management applications, is providing a comprehensive set of resources for researchers and others mapping the spread of the coronavirus 2019 (COVID-19) pandemic.
From Esri: “As the situation surrounding coronavirus disease 2019 (COVID-19) continues to evolve, Esri is supporting our users and the community at large with location intelligence, geographic information system (GIS) and mapping software, services, and materials that people are using to help monitor, manage, and communicate the impact of the outbreak. Use and share these resources to help your community or organization respond effectively.”
The site provides
Access GIS Resources: COVID-19 GIS Hub
View global maps and dashboards
Get insights – View reliable, up-to-date content related to COVID-19 from trusted sources.
From Esri: As global communities and businesses seek to respond to the COVID-19 pandemic, you can take these five proactive steps to create an instant picture of your organization’s risk areas and response capacity.
Map the cases
Map confirmed and active cases, fatalities, and recoveries cases to identify where COVID-19 infections exist and have occurred.
Map the spread
Time-enabled maps can reveal how infections spread over time and where you may want to target interventions.
Map vulnerable populations
COVID-19 disproportionally impacts certain demographics such as the elderly and those with underlying health conditions. Mapping social vulnerability, age, and other factors helps you monitor the most at-risk groups and regions.
Map your capacity
Map facilities, employees or citizens, medical resources, equipment, goods, and services to understand and respond to current and potential impacts of COVID-19.
Communicate with maps
Use interactive web maps, dashboard apps, and story maps to help rapidly communicate your situation.
By Leonardo Collado Torres, Ph. D., Research Scientist, Lieber Institute for Brain Development, Brain genomics #rstats coder working w/ @andrewejaffe @LieberInstitute. @lcgunam @jhubiostat @jtleek alumni. @LIBDrstats @CDSBMexico co-founder
I have been attending R conferences since 2008, and while I’ve seen the R community grow rapidly, I generally don’t encounter as many Latin Americans (LatAm) among communities of R developers. Traditionally, a lab lead investigator invested in R or Bioconductor would teach their trainees and students these skills, becoming a local R hotspot. However, that scenario is uncommon in Mexico for several reasons. Recognizing some of these challenges and driven to promote R in our home country and LatAm, in 2017 Alejandro Reyes and I teamed up with Alejandra Medina Rivera and Heladia Salgado to eventually launch the Community of Bioinformatics Software Developers CDSB (in Spanish) in 2018. One of our goals is to facilitate and encourage the transition from R user to R/Bioconductor developer. We have organized yearly one-week long workshops together with NNB-UNAM and RMB and just announced our 2020 workshop (August 3-7 2020 Cuernavaca, Mexico).
Now unto our third workshop, I feel like we’ve had several success stories.
CDSB2018 alumni wrote a blog post about their R GitHub package: `rGriffin`.
We have greatly benefited from the logistics and organization support by NNB-UNAM and RMB local teams, allowing us to focus on designing the workshop curriculum and inviting a diverse set of instructors, including Maria Teresa Ortiz who is an RLadiesCDMX co-founder and has been supporting us from the beginning. However, we face economic challenges as the budget for the national science foundation (CONACyT) has decreased in recent years. The support by the small R conference fund by R Consortium and other sponsors has been instrumental, as well as diversity and travel scholarships some of our instructors have secured at R conferences. We just recently revamped our sponsor page and answered the question: why should you support us?
However, while we are just getting started, one of our highlights was born by rOpenSci’s icebreaker exercise at CDSB2019. We were able to really build a sense of community and desire to perform outreach activities at our local communities. Particularly, a CDSB2018 and 19 alumni, Joselyn Chávez, volunteered to join the CDSB board. At CDSB2019 we also created an #rladies channel in our Slack where at the time we had members of 3/4 Mexico’s RLadies chapters (Qro, Xalapa, CDMX) and now have 5/6 (Cuerna, Monterrey), as CDSB2018 and CDSB2019 alumni have been co-founders of two chapters: Ana Beatriz Villaseñor-Altamirano for Qro and Joselyn Chávez for Cuerna.
I am proud and excited of what we have achieved with our one-week long CDSB workshops, but also with how we used the tools we’ve learnt from other communities in order to keep interacting and communicating throughout the rest of the year. Time will tell if our efforts created a ripple that grew into a wave or if we’ll end burning out. Sustainability is a challenge, but we are greatly motivated by the impact we’ve had and can only imagine a brighter future.
The March 2020 ISC Call for Proposals is now open. Once again, we are looking for ambitious projects that will contribute to the infrastructure of the R ecosystem and benefit large sections of the R community. Our goal is to stimulate creativity and help you turn good ideas into tangible benefits.
It is very likely that everyone who reads this post will be reorganizing aspects of their everyday lives to cope with the challenge of the Covid-19 virus. Accordingly, we are suggesting a theme for this call for proposals: What can we do to improve the R infrastructure for locating, accessing, cleaning and reporting on data related to the epidemic that will be useful now and in the future?
In the recently published post COVID-19 epidemiology with R, researcher Tim Churches highlights some of the challenges presented in acquiring accurate “real time” data. These include locating sources, writing code to scrape Wikipedia, a site whose structure may change every time it is updated, digging out data embedded in multiple different languages etc and providing mechanisms for researchers to store data, share code and exchange ideas.
But don’t be constrained by the theme. There is other work that needs to be done and we want to hear about ideas that we may be able to facilitate.
As always, “Think Big” but structure your proposal with intermediate milestones. The ISC is not likely to fund proposals that ask for large initial cash grants. We tend to be conservative with initial grants, preferring projects structured in such a way that significant initial milestones can be achieved with modest amounts of cash.
As with any proposed project, the more detailed and credible the project plan, and the better the track record of the project team, the higher the likelihood of receiving funding. Please be sure that your proposal includes measurable objectives, intermediate milestones, a list of all team members who will be contributing work and a detailed accounting of how the grant money will be spent.
To submit a proposal for ISC funding, read the Call for Proposals page and submit a self-contained pdf using the online form. You should receive confirmation within 24 hours.
The deadline for submitting a proposal is midnight, April 2, 2020.
Services include R consulting, development, and training; contributes to multiple R open source projects including golem, framework for building robust Shiny apps
SAN FRANCISCO, March 3, 2020 – The R Consortium, a Linux Foundation project supporting the R Foundation and R community, today announced that ThinkR has joined the R Consortium as a Silver Member. ThinkR provides R engineering, training, and consulting, and is based in France.
“We provide R Language infrastructure, engineering and training to our clients, and at the same time we believe it is important to give back to the R community by participating in open source projects, holding meetups and training, and promoting R in many ways. Joining the R Consortium will help us to expand our support for R even more, and allow us to work toward building better R infrastructure that helps R developers and our customers,” said Diane Beldame, CEO, ThinkR. “Joining the R Consortium will allow us to better support and promote the R community and that is a big benefit for our clients.”
ThinkR developers devote a part of their time to R and Data Science communities. This includes supporting various R packages on Github, holding meetups and other conferences connected to R, posting development tips on the ThinkR blog, and responding on Stackoverflow and other Slack communities.
“We are excited to welcome ThinkR to the R Consortium. ThinkR is on the front lines of providing R to industries in ways that immediately contribute to their customers’ success,” said Joseph Rickert, RStudio’s R Community Ambassador and R Consortium Board Chair. “At the same time, ThinkR contributes to the R community with open source projects and much more, and we’re very pleased they will be involved in moving the R Consortium forward.”
ThinkR has clients in a wide range of industries including public institutions, Pharmaceutical, Energy, Banking, Electronics Manufacturing, Research, and more.
The R Consortium is a 501(c)6 nonprofit organization and Linux Foundation project dedicated to the support and growth of the R user community. The R Consortium provides support to the R Foundation and to the greater R Community for projects that assist R package developers, provide documentation and training, facilitate the growth of the R Community and promote the use of the R language. For more information about R Consortium, please visit: http://www.r-consortium.org.
About Linux Foundation
Founded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world’s leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation projects like Linux, Kubernetes, Node.js and more are considered critical to the development of the world’s most important infrastructure. Its development methodology leverages established best practices and addresses the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org
Google Summer of Code (GSoC) is an annual 3-month open-source software development (coding) program that provides a platform for mentors and students (mentees) to collaborate on open source projects. This article highlights our accomplishments in the final coding phase of the 2019 GSoC project: “Data-Driven Exploration of the R Community”. The first part of the project explored R-Ladies chapters, the second part explored all R user groups available through Meetup.com and in the last phase we explored Google Summer of Code projects under the R Project over the past 12 years.
What We Achieved
1. Aggregating all R-GSoC projects into a CSV file presenting names of students, mentors, and projects and computing summaries for students, mentors, and projects and storing them in JSON format
2. Assigning all 215 R-GSoC projects into a work-product category among: Package, Infrastructure, Data, Database, GUI, Visualization, Documentation and Application
3. Updating the names of students and mentors to maintain consistency – some names are abbreviated, some are just Google user names and others appear differently across projects
4. Charting work-product distribution using grouping functions from d3.js and charting functions from echarts.js
5. Building a dashboard using similar tools described in our article here
6. Creating a word-cloud from the projects’ topics using d3.js and d3-layout.cloud.js libraries, and charting the top 20 frequent words
While you may not read about R-Google Summer of Code (R-GSoC) activities every day via blog posts and Twitter, many important R contributions have emerged from R-GSoC activities. Example past R-GSoC projects include enhancements of Toby Dylan Hocking’s animint [animated interactive plots] package and statistical modeling R packages like the Stan-using BayesHMM.
This is a screenshot from our R Community Explorer’s “Past GSoC R Projects” section:
Our previous articles discussed our celebration of R-Ladies and the general R User Group community through open-source dashboards that highlight the growth, geographical distribution, and activity of the R community on Meetup. We hope applying this similar approach to exploring R-GSoC projects will encourage more R-GSoC proposals, increase consideration of prior projects, and attract more participants to the R ecosystem.
The following summaries are displayed on the dashboard:
+ Most active mentors
+ Students returning as mentors
+ Students returning for another GSoC
+ Counts and averages of projects, students and mentors
+ Count of projects co-mentored by former GSoC students
Google has funded 215 R projects, accomplished by 189 students and 202 mentors in the past 12 years of GSoC. The number of projects is quite significant – thanks to Google’s generosity towards the R-Project by giving them adequate GSoC slots each year.
The word-cloud and bar chart of top 20 words on the dashboard show that in the past 12 years of Google Summer of Code under R, data analysis, package development/enhancement and biodiversity applications have been the most popular. Modeling, interactive visualization, optimization and performance improvement have also taken top positions within GSoC projects.
From 2013, the number of mentors per year at least doubled the number of participating students. This is as a result of policies by the R org admins who require at least two mentors for each project so as to reduce student failure rates and improve mentor availability throughout the program.
25 Google Summer of Code students (13% of all students) under the R-Project have returned as mentors and they have co-mentored about 72 projects (33% of all projects) in the past 12 years
The R-Project participated in the Google Code-In contest for the first time in 2019 and we are glad to explore the resulting data and report our findings. We generally hope that aggregating and reporting activities around many popular and unpopular aspects of the R language will bring greater visibility to the hard work of several contributors, highlight opportunities around Google programs, and continue to give the global R community a feel of the popularity of R over the years.