The goal of the Infrastructure Steering Committee (the ISC) is to support projects that broadly help the R community. This might be software development, developing new teaching materials, documenting best practices, standardising APIs or doing research. Currently, the ISC chiefly provides financial support for projects proposed by individuals or teams who have the skills to carry out the work, but we can also provide administrative support, promotion and some collaboration tools for groups who would like to study more ambitious projects.

Below is a list of the projects currently funded by the ISC.

Active Funded Projects

Enhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials

Funded: 13,912 USD
Proposed By: Richard Webster (rwebster@cheo.on.ca)
Project URL: https://cheori.org/samplesize/
Project Summary: Sample size calculation and power analysis are fundamental for study design, yet they are challenging to do in the R programming language due to limited inter-package documentation. It is difficult to find the required functionality within the sea of open source packages. Indeed, there is no systematic R resource that allows users to search for whether a particular study design and corresponding statistical test has a power analysis implemented in R. Our aims are to improve usability of power analyses performed in R, to facilitate proper design and analysis of data, and promote reproducible research. Our duel approach is to create a Task View page for sample size calculations & power analyses, as well as a series of tutorials to reduce the R users’ learning curve. Addressing the usability of sample size calculation / power analyses will benefit a broad spectrum of R users, as this is a vital component for study design, result interpretability and reproducibility.

A central class for tracking and movement data

Funded: 10,000 USD
Proposed By: Mathieu Basille (basille@ufl.edu)
Project URL: https://github.com/mablab/sftraj
Project Summary: The only aim of the package will be to present a central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R. The first stage of the work will specifically involve the Movement community in R. During this stage, we will open contributions of use cases for the package (using GitHub’s issue system), which set practical goals for the development of the package. Use cases describe the workflow that is expected from both users’ and developers’ perspectives, and thus the capabilities that a trajectory package needs to offer. The package specifications and development will aim at addressing all use cases described, to make sure the solution provided is relevant for a wide array of users and package developers.

R-global: analysing spatial data globally

Funded: 10,000 USD
Proposed By: Edzer Pebesma (edzer.pebesma at uni-muenster.de)
Project URL: https://github.com/r-spatial/global/
Project Summary: Currently, a number of R spatial functions assume that coordinates are two-dimensional, taken from a “flat” space, and may or may not work for geographical (long/lat) coordinates, depicting points on a globe. This project will try to make such functions more robust and helpful for the case of geographical coordinates. It will reconsider the concept of a bounding box, and build an interface to the S2 geometry library (http://s2geometry.io/), which powers several modern systems that assume geographic coordinates.

Expanding the ‘metaverse’; an R ecosystem for meta-research

Funded: 20,171 USD
Proposed By: Martin Westgate (martin.westgate at anu.edu.au)
Project URL: https://rmetaverse.github.io
Project Summary:Evidence synthesis is the process of identifying, collating and summarizing primary scientific research to provide reliable, transparent summaries such as systematic reviews and meta-analyses. Despite their importance for linking research with policy, however, evidence synthesis projects are often time-consuming, expensive, and difficult to update. Open and reproducible workflows would help address these problems, but these workflows are poorly supported by the current package environment, preventing access by new users and hindering uptake of the well-developed suite of statistical tools for meta-analysis in R. The metaverse project will integrate and expand tools to support evidence synthesis and meta-research in R; suggest flexible workflows to complete these projects in a straightforward and open manner; and provide a collector package allowing easy access to these developments for new and experienced users.

R Community Collaboratives

Funded: 20,000 USD
Proposed By: Angela Li (angela at angelalidata.com)
Project URL: https://github.com/unconf-toolbox
Project Summary:Previously known as the Unconf Toolbox, R Community Collaboratives provide resources and support to facilitate on-the-ground organization of community events. These events engage individuals in the R community through in-person collaboration on open source projects. R Collabs emphasize learning and mentorship, encouraging R users to become R developers. They are inspired by the unconference organized by rOpenSci, but are designed to encourage local organizers to put on events for their own community. To do so, this project develops useful technical and logistical infrastructure for R Collab organizers. These include a website template, an organizing handbook, and a project dashboard for reporting out.

Next-generation text layout in grid and ggplot2

Funded: 25,000USD
Proposed By: Claus O. Wilke (wilke at austin.utexas.edu)
Project URL: TBA
Project Summary: Text is a key component of any data visualization. We need to label axes and legends, we need to annotate or highlight specific data points, and we need to provide plot titles and captions. The R graphics package ggplot2 provides numerous features to customize the labeling and annotation of plots, but ultimately it is limited by the current capabilities of the underlying graphics libary it uses, grid. Grid can draw simple text strings or mathematical expressions (via plotmath) in different colors, sizes, and fonts. However, it lacks functionality for changing formatting within a string (e.g., draw a single word in italics or in a different color), and it also cannot draw text boxes, where the text is enclosed in a box with defined margins, padding, or background color. This project will support the development of a new package, gridtext, that will alleviate these text formatting limitations. The project will also support efforts to make these new capabilities available from within ggplot2.

Catalyzing R-hub adoption through R package developer advocacy

Funded: 46,050USD
Proposed By: Maëlle Salmon (maelle.salmon at yahoo.se)
Project URL: TBA
Project Summary: After the continuing technical progress of R-hub over the last two years, this project aims at catalizing its adoption by R package developers of all levels through developer advocacy. Indeed, R-hub is currently a successful and very valuable project, but it is not documented thoroughly, which hinders its wider adoption by package developers. This project shall answer this concern by three main actions: improving R-hub documentation, making R-hub better known in the community and making the R-hub web site more attractive to, and easier to use by, R developers and users via the ingestion of METACRAN services and the creation of a R-hub blog.

Editorial assistance for the R Journal

Funded: 50,000USD
Proposed By: Di Cook (dicook at monash.edu)
Project URL: TBA
Project Summary: This project supports the operation of the R Journal. There are two aspects, one is to fund an editorial assistant to send reminders about reviews, and assist with typesetting and copyediting issues. The second part is to explore updating the technical operations of the journal production.

Symbolic Formulae for Linear Mixed Models

Funded: 6,000USD
Proposed By: Emi Tanaka (dr.emi.tanaka at gmail.com)
Project URL: TBA
Project Summary: Symbolic model formulae define the structural component of a statistical model in an easier and often more accessible terms for practitioners. The earlier instance of symbolic model formulae for linear models was applied in Genstat with further generalisation by Wilkinson and Rogers (1973). Chambers and Hastie (1993) describe the symbolic model formulae implementation for linear models in the S language which remains much the same in the R language (Venables et al. 2018). Linear mixed models (LMMs) are widely used across many disciplines (e.g. ecology, psychology, agriculture, finance etc) due to its flexibility to model complex, correlated structures in the data. While the symbolic formula of linear models generally have a consistent representation and evaluation rule as implemented in stats::formula, this is not the case for LMMs. The inconsistency of symbolic formulae arises mainly in the representation of random effects, with the additional need to specify the variance-covariance structure of the random effects as well as structure of the associated model matrix that governs how the random effects are mapped to (groups of) the observational units. The differences give rise to confusion of equivalent model specification in different R-packages. The lack of consistency in symbolic formula and model representation across mixed model software motivates the need to formulate a unified symbolic model formulae for LMMs with: (1) extension of the evaluation rules described in Wilkinson and Rogers (1973); and (2) ease of comprehension of the specified model for the user. This symbolic model formulae can be a basis for creating a common API to mixed models with wrappers to popular mixed model R-packages, thereby achieving a similar feat to parsnip R-package (Kuhn 2018) which implements a tidy unified interface to many predictive modelling functions (e.g. random forest, logistic regression, survival models etc). We would like to find out what are your experiences with fitting linear mixed model in R! Please fill out the survey below to help us understand your problems: https://docs.google.com/forms/d/e/1FAIpQLSeblEoPtDmPS-dH2dmsHjLxLuKl19UY1JdmTrZux-AUSq3N7Q/viewform?usp=sf_link

Licensing R – Guidelines and tools

Funded: 6,000USD
Proposed By: Colin Fay (colin at thinkr.fr)
Project URL: TBA
Project Summary: Licensing is a vital part of Open Source. It provides guidelines for interacting with a program, and for making code accessible and reusable (or not). It provides a way to make code open source, in a way one wants to share it, protecting how it will be used and reused. Licensing is also challenging and complex: there are a lot of available licenses, and the choice is influenced by how you import and interact with elements from other packages and/or programs. With this project, we propose to explore and document the current state of open source licenses in R, and to decipher compatibility and incompatible elements inside these licenses, to help developers chose the best-suited license for their project.

serveRless

Funded: 10,000USD
Proposed By: Christoph Bodner (christoph.bodner at gmail.com)
Project URL: https://github.com/harlecin/serverless
Project Summary: R is a great language for rapid prototyping and experimentation, but putting an R model in production is still more complex and time-consuming than it needs to be. With the growing popularity of serverless computing frameworks such as AWS Lambda and Azure Functions, we see a huge chance to allow R developers to more easily deploy their code into production. We want to build an R package called ‘serverless’ to allow R users to easily deploy scripts and custom R packages to AWS Lambda and in a second step to Azure Functions. Our main goal is to build a user-friendly cloud agnostic wrapper that can be extended to include additional cloud providers later on. We want to build on the work already done for deploying R functions to AWS Lambda by Philipp Schirmer and on the work already done by Neal Fultz and Gergely Daróczi on a gRPC client/server for R, which is necessary for Azure Functions. If you like our idea and want to help us, feel free to reach out to us on Github at https://github.com/harlecin/serverless

Preserving and Transferring Algorithmic Knowledge

Proposed By: John C. Nash (nashjc at uottawa.ca)
Funded:  4,000USD
Project URL:  https://gitlab.com/nashjc/histoRicalg
Project Summary: Many of the algorithms making up the numerical building-blocks of R were developed several decades ago, particularly in Fortran. Some were translated into C for use by R. Only a modest proportion of R users today are fluent in these languages, and many original authors are no longer active. Yet some of these codes may have bugs or need adjustment for new system capabilities. The histoRicalg project aims to document and test such codes that are still part of R, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future. Our initial task is to establish a ***Working Group on Algorithms Used in R*** and add material to a website/wiki currently at https://gitlab.com/nashjc/histoRicalg. Interested workers are invited to contact John Nash

Conference Management System for R Consortium Sponsored Conferences

Funded: 32,000USD
Proposed By: Heather Turner (ht at heatherturner.net)
Project URL:  TBA
Project Summary:  This project will evaluate a number of open source conference management systems to assess their suitability for use with useR! and satRdays. Test versions of these systems will be set up to test their functionality and ease of use for all roles (systems administrator, local organizer, program chair, reviewer, conference participant). A system will be selected and a production system set up, with a view to be ready for useR! 2018 and future satRdays events.

Forwards Workshops for Women and Girls

Funded: 25,000USD
Proposed By: Dianne Cook (rowforwards at gmail.com)
Project URL:  http://forwards.github.io
Project Summary:  The proportion of female package authors and maintainers has remained persistently low, at best at 15%, despite 20 years of the R project’s existence. This project will conduct a grassroots effort to increase the participation of women in the R community. One day package development workshops for women engaged in research will be held in Melbourne, Australia and Auckland, New Zealand in 2017, and at locations yet to be determined in the USA and Europe in 2018. Additionally, one-day workshops for teenage girls focused on building Shiny apps will be developed to encourage an interest in programming. These will be rolled out in the same locations as the women’s workshops. All materials developed will be made available under a Creative Commons share-alike license on the Forwards website (http://forwards.github.io).

Joint Profiling of Native and R Code

Funded: 11,000USD
Proposed By: Kirill Müller (krlmlr at mailbox.org)
Project URL:  TBA
Project Summary:  R has excellent facilities for profiling R code: the main entry point is the Rprof() function that starts an execution mode where the R call stack is sampled periodically, optionally at source line level, and written to a file. Profiling results can be analyzed with summaryRprof(), or visualized using the profvis,  aprof, or GUIProfiler packages. However, the execution time of native code is only available in bulk, without detailed source information.

This project aims at bridging this gap with a drop-in replacement to Rprof() that records call stacks and memory usage information at both R and native levels, and later commingles them to present a unified view to the user.

Future Minimal API: Specification with Backend Conformance Test Suite

Funded: 10,000USD
Proposed By: Henrik Bengtsson (henrik.bengtsson at gmail.com)
Project URL:  TBA
Project Summary: The objective of the Future Framework implemented in the future package is to simplify how parallel and distributed processing is conducted in R. This project aims to provide a formal Future API specification and provide a test framework for validating the conformance of existing (e.g. future.batchtools and future.callr) and to-come third-party parallel backends to the Future framework.

An Earth data processing backend for testing and evaluating stars

Funded: 5,000USD
Proposed By: Edzer Pebesma (edzer.pebesma at uni-muenster.de)
Project URL: https://www.rdocumentation.org/packages/stars/versions/0.0
Project Summary: The stars project enables the processing Earth imagery data that is held on servers, without the need to download it to local hard drive. This project will (i) create software to run a back-end, (ii) develop scripts and tutorials that explain how such a data server and processing backend can be set up, and (iii) create an instance of such a backend in the AWS cloud that can be used for testing and evaluation purposes.

Maintaining DBI

Funded: 26,500USD
Proposed By: Kirill Müller
Project URL: http://dbi.r-dbi.org/
Project Summary: DBI, R’s database interface, is a set of methods declared in the DBI R package. Communication with the database is implemented by DBI backends, packages that import DBI and implement its methods. A common interface is helpful for both users and backend implementers.

The Maintaining DBI Project which follows up on two previous projects supported by the R Consortium will provide ongoing maintenance and support for DBI, the DBItest test suite, and the three backends to open-source databases (RSQLite, RMariaDB and RPostgres).

Developing Tools and Templates for Teaching Materials

Funded: 10,000USD
Proposed By: François Michonneau
Project URL: TBA
Project Summary: The first-class implementation of literate programming in R is one of the reasons for its success. While the seamless integration of code and text made possible by Sweave , knitr, and R Markdown was designed for writing reproducible reports and documentation, it has also enabled the creation of teaching materials that combine text, code examples, exercises and solutions. However, while people creating lessons in R Markdown are familiar with R, they often do not have a background in education or UX design. Therefore, they must not only assemble curriculum, but also find a way to present the content effectively and accessibly to both learners and instructors. As the model of open source development is being adapted to the creation of open educational resources, the difficulty to share materials due to a lack of consistency in their construction hinders the collaborative development of these resources.

This project will develop an R package that will facilitate the development of consistent teaching resources. It will encourage the use of tools and lesson structure that support and improve learning. By providing the technical framework for developing quality teaching materials, we seek to encourage collaborative lesson development by letting authors focus on the content rather than the formatting, while providing a more consistent experience for the learners.

R Validation Hub (formerly called PSI project for R Package Validation)

Funded: 4,000USD
Proposed By: Lyn Taylor (on behalf of PSI AIMS SIG)
Project URL: TBA
Project Summary: The documentation available for R packages currently widely varies. The Statisticians in the Pharmaceutical Industry (PSI) Application and Implementation of Methodologies in Statistics (AIMS) Special Interest Group (SIG) will collaborate with the R-Consortium and representatives from pharmaceutical companies on the setting up of an online repository /web portal, where validation which is of regulatory standard for R packages can be submitted and stored for free use. Companies (or individual R users) would still be liable to make their own assessment on whether the validation is suitable for their own use, however the online repository would serve as a portal for sharing existing regulatory standard validation documentation.

Completed Funded Projects

Refactoring and updating the SWIG R module

Funded: 10,000USD
Proposed By: Richard Beare (richard.beare at monash.edu)
Project URL:  TBA
Project Summary: The Simplified Wrapper and Interface Generator (SWIG) is a tool for automatically generating interface code between interpreters, including R, and a C or C++ library. The R module needs to be updated to support modern developments in R and the rest of SWIG. This project aims to make the R module conform to the recommended SWIG standards and thus ensure that there is support for R in the future. We hope that this project will be the first step in allowing SWIG generated R code using reference classes.

Data-Driven Discovery and Tracking of R Consortium Activities

Funded: 5,250USD
Proposed By: Ubah Chibuokem Benaiah (ben at rpowerlabs.org)
Project URL: TBA
Project Summary: This project proposes an infrastructure that provides a data-driven approach to render the yearly activities of the R Consortium, by deploying web pages for discovering and tracking ISC Funded Projects, RUGS and Marketing activities. These pages are planned to appear like dashboards summarizing activities in interactive tables and charts, presenting several views, trends and insights to what R Consortium has achieved over time. The project hopes that presenting these achievements in a data-driven manner to the R community, the data science community and prospective R Consortium members will promote greater transparency, productivity and community inclusiveness around R Consortium activities.

SatRdays

Proposed By: Gergely Daroczi (Hungarian R user group) and Steph Locke (Mango Solutions)
Funded: 10,000USD
Project URL: https://github.com/satRdays
Project Summary: “SatRDays” are community-led, regional conferences to support collaboration, networking and innovation within the R community. Initially three events will be hosted, with plans for additional meet-ups as the R user base grows.

A unified platform for missing values methods and workflows

Funded: 10,000USD
Proposed By: Julie Josse and Nicholas Tierney
Project URL: TBA
Project Summary: The objective is to create a reference platform on the theme of missing data management and to federate contributors. This platform will be the occasion to list the existing packages, the available literature as well as the tutorials that allow to analyze data with missing data. New work on the subject can be easily integrated and we will create examples of analysis workflows with missing data. Anyone who would like to contribute to this exciting project can contact us.

Ongoing infrastructural development for R on Windows and MacOS

Funded: 62,400USD
Proposed By: Jeroen Ooms
Project URL: TBA
Project Summary: The majority of R users rely on precompiled installers and binary packages for Windows and MacOS that are made available through CRAN. This project seeks to improve and maintain tools for providing such binaries. On Windows we will upgrade the Rtools compiler toolchain, and provide up-to-date Windows builds for the many external C/C++ libraries used by CRAN packages. For MacOS we will expand the R-Hub homebrew-cran with formulas that are needed by CRAN packages but not available from upstream homebrew-core. Eventually, we want to lay the foundation for a reproducible build system that is low maintenance, automated as much as possible, and which could be used by CRAN and other R package repositories.

Strengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages

Funded: 20,000USD
Proposed By: Emmanuel Blondel (emmanuel.blondel1 at gmail.com)
Project URL: TBA
Project Summary: The project aims to strengthen the role of R in support of Spatial Data Infrastructures (SDI) management, through major enhancements of the geometa R package which offers tools for reading and writing ISO/OGC geographic metadata, including ISO 19115, 19110, and 19119 through the ISO 19139 XML format. This also extends to the Geographic Markup Language (GML – ISO 19136) used for describing geographic data. The use of geometa in combination with publication tools such as ows4R (https://cran.r-project.org/package=ows4R) and geosapi (https://cran.r-project.org/package=geosapi) fosters the use of R software to ease the management and publication of metadata documents and related datasets in web catalogues, and then allows to move forward with a real R implementation of spatial data management plans based on FAIR (Findable, Accessible Interoperable and Reusable) principles. The workplan includes several activities such as working on the completeness of the ISO 19115 (ISO 19115-1 and 19115-2) data model in geometa, functions to read/write multilingual metadata documents, and an increased metadata validation capability with a validator targeting the EU INSPIRE directive. Finally, functions will be made available to convert between geometa ISO/OGC metadata objects and other known metadata objects such as NetCDF-CF and EML (Ecological Metadata Language) to foster metadata interoperability. By providing these R tools, we seek to facilitate the work of spatial data (GIS) managers, but also data scientists, whatever the thematic domain, whose daily tasks consist in handling data, describing them with metadata and publishing datasets.

Interactive data manipulation in mapview

Funded: 9,100USD
Proposed By: Tim Appelhans (tim.appelhans at gmail.com)
Project URL: https://r-spatial.github.io/mapview/
Project Summary: mapview provides functions to very quickly and conveniently create interactive visualizations of spatial data. It was created to fill the gap of quick (not presentation grade) interactive plotting to examine and visually investigate both aspects of spatial data, the geometries, and their attributes.

Proposal to Create an R Consortium Working Group Focused on US Census Data

Funded: 4,000USD
Proposed By: Ari Lamstein (ari at lamsteinconsulting.com)
Project URL: TBA
Project Summary: The working group held its first meeting on August 8th. If you are interested in getting involved, write to us at rconsortium-isc@lists.r-consortium.org

R Documentation Task Force

Funded: 10,000USD
Proposed By: Andrew Redd (andrew.redd at hsc.utah.edu)
Project URL: https://github.com/halpo/R-Documentation-Task-Force-Proposal
Project Summary: Beta packages with limited functionality are being prepared for release

Quantities for R

Funded: 10,000USD
Proposed By: Iñaki Ucar (inaki.ucar at uc3m.es)
Project URL:  https://github.com/r-quantities/quantities
Project Summary:  The ‘units’ package has become the reference for quantity calculus in R, with a wide and welcoming response from the R community. Along the same lines, the ‘errors’ package integrates and automatises error propagation and printing for R vectors. A significant fraction of R users, both practitioners and researchers, use R to analyse measurements, and would benefit from a joint processing of quantity values with errors.

This project not only aims at orchestrating units and errors in a new data type, but will also extend the existing frameworks (compatibility with base R as well as other frameworks such as the tidyverse) and standardise how to import/export data with units and errors.

Stars: Scalable, Spatiotemporal Tidy Arrays for R

Funded: 10,000USD
Proposed By: Edzer Pebesma (edzer.pebesma at uni-muenster.de)
Project URL:  https://github.com/edzer/stars
Project Summary:  Spatiotemporal and raster data often come as dense, two-dimensional arrays while remote sensing and climate model data are often presented as higher dimensional arrays. Data sets of this kind often do not fit in main memory. This project will make it easier to handle such data with R by using dplyr-style, pipe-based workflows, and also consider the case where the data reside remotely, in a cloud environment. Questions and offers to support are welcome through issues at: https://github.com/edzer/stars .

A Unified Framework For Distributed Computing in R

Proposed By: Michael Lawrence (R core, Genetech), Edward Ma (Hewlett Packard Enterprise), and  Indrajit Roy (Hewlett Packard Labs)
Funded: 10,000USD
Project URL: https://github.com/vertica/ddR/issues/17
Project Summary: Many Big Data platforms expose R-based interfaces that lack standardization and are therefore difficult to learn. This project will develop a common framework to simplify and standardize how users program distributed applications in R, ultimately reducing duplication of effort.

Establishing  DBI

Funded: 26,500USD
Proposed By: Kirill Müller (krlmlr at mailbox.org)
Project URL:  https://www.r-dbi.org/
Project Summary:  Getting data in and out of R is an important part of a statistician’s or data scientist’s work. If the data reside in a database, this is best done with a backend to DBI, R’s native DataBase Interface. The ongoing “Improving DBI” project supports the DBI specification, both in prose and as an automated test. It also supports the adaptation of the `RSQLite` package to these specs. This follow-up project aims to implement a modern, fully spec-compliant DBI backends to two major open-source RDBMS, MySQL/MariaDB and PostgreSQL.

Improving Database Interface (DBI)

Proposed By: Kirill Müller (ETH Zürich)
Funded: 25,000USD
Project URL: https://www.r-dbi.org/
Project Summary: Database access is an important cornerstone of the R ecosystem, but today’s specifications – data type transformation, return values, error conditions – remain vague and result in data analysis errors. This project aims to improve database access in R so that porting code is simplified and less prone to error.

RHub Project

Proposed By: Gábor Csárdi (Harvard University)
Funded: 80,000USD
Project URL: https://github.com/r-hub/
Project Summary: A new service for developing, building, testing and validating R packages. R-Hub will be complementary to both CRAN, the major repository for open source R packages, and R-Forge, the platform supporting R package developers. R-Hub will provide build services, continuous integration for R packages and a distribution mechanism for R package sources and binaries.

  • Goals for R-Hub include:
    • simplify the R package development process: creating a package, building binaries and continuous integration, publishing, distributing and maintaining it;
    • provide services free for all members of the community;
    • encourage community contributions; and
    • pre-test CRAN package submissions to ease burden on CRAN maintainers.

R-hub #2

Funded: 89,500USD
Proposed By: Gábor Csárdi (csardi.gabor at gmail.com)
Project URL: https://github.com/r-hub/
Project Summary:  R-hub is the first top level project of the R Consortium. The first stage of the project created a multi-platform, R package build server. This proposal includes the maintenance of the current R-hub infrastructure and a number of improvements and extensions including:

  1. R-hub as the first step of package submissions to CRAN
  2. R package reverse dependency checks, on R-hub and locally
  3. General R code execution, on all R-hub platforms
  4. Check and code quality badges
  5. Database of CRAN code
  6. The CRAN code browser

R Implementation, Optimization and Tooling Workshops (RIOT)

Proposed By: Mark Hornick, Lukas Stadler and Adam Welc (Oracle)
Funded: 10,000USD
Project URL: http://riotworkshop.github.io/
Project Summary: RIOT 2016 is a one-day workshop to unite R language developers, identify R language development and tooling opportunities, increase involvement of the R user community and more.

Simple Features Access For R

Proposed By: Edzer Pebesma (Institute for Geoinformatics, University of Muenster)
Funded: 10,000USD
Project URL: https://r-spatial.github.io/sf/
Project Summary: Using the “Simple Features” standard supported by the Open Geospatial Consortium and the International Organization for Standardization, this tool will simplify analysis on modern geospatial data.

Software Carpentry R Instructor Training

Proposed By: John Blishak, Jonah Duckles, Laurent Gatto, David LeBauer, and Greg Wilson (Software Carpentry)
Funded: 10,000USD
Project URL:http://software-carpentry.org/blog/2016/03/r-consortium-training.html
Project Summary: This two-day in-person training course will introduce the basics of R programming and address the growing demand for training resources for the R language.

An Infrastructure for Building R Packages on MacOS with Homebrew

Proposed By: Jeroen Ooms (jeroenooms at gmail.com)
Funded:  12,000USD
Project URL:  https://github.com/r-hub/homebrew-cran
Project Summary:  When installing CRAN packages, Windows and MacOS users often rely on binary packages that contain precompiled source code and any required external C/C++ libraries. By eliminating the need to set up a full compiler environment or manage external libraries this tremendously improves the usability of R on these platforms. Our project will improve the system by adapting the popular Homebrew system to facilitate static linking of external libraries.