Kudos and congratulations to the R Core Team for their receipt of the Rousseeuw Prize for Statistics!
This award is a testimony to the tremendous volunteer efforts to build this free and open-source resource for the entire community. Please join me in thanking them for their above and beyond work over the past three decades.
More details can be found at https://rousseeuwprize.org/2026
Five members of the R Core Team have been awarded the Rousseeuw Prize for Statistics for their decades of work building and maintaining the R Project. The 2026 laureates are:
- Prof. Brian Ripley, University of Oxford, United Kingdom
- Prof. Martin Maechler, ETH Zurich, Switzerland
- Prof. Kurt Hornik, Vienna University of Economics and Business, Austria
- Prof. Peter Dalgaard, Copenhagen Business School, Denmark
- Prof. Luke Tierney, University of Iowa, United States
Half of the prize money goes to the five laureates because they are deemed to have made the longest sustained contributions, and half goes to the other members of the R Core Team. The laureates have spent nearly thirty years of work on R, developing an open-source programming language and software environment that transformed statistics from an expensive proprietary corporate tool into a global public good.
The R Project is a collective endeavor that has had an enormous impact on the development of statistical methodology and data analysis, over the last three decades. R is a computer language and an environment for data analysis and graphics. It has become a vehicle for the development and dissemination of new methods, through the establishment and maintenance of an ecosystem of well-defined software extension packages.
R started in the early nineties, when Robert Gentleman and Ross Ihaka created another implementation of S, for which John Chambers would receive the 1998 Software System Award of the Association for Computing Machinery. Initially meant for classroom use and to allow experiments with the computer language itself, their initiative was soon joined by volunteers from academia sharing a vision of together developing an open source, state-of-the-art system, freely available on all major software platforms.
Since mid-1997, this `R Core Team' has been stewarding the development of the core systems of R. A subset of the R Core Team created and keeps maintaining the Comprehensive R Archive Network (CRAN) which provides an actively maintained repository of over 23,000 interoperable packages that work with current and development versions of the base system. It has extensive graphics capabilities. It is also the basis of the Bioconductor software for research on genomic data.
Under the auspices of the R Core Team, R has developed substantially beyond its original goal of re-implementing S, a milestone that was achieved with the first major release of R in 2000. From the start R supported not only English but also Western European text, which was rare for statistics tools at the time. Soon there were requests to support other languages, including Japanese, so R was re-worked to support processing of text written in most human languages and for R messages to be translated. The base system gained a byte compiler for substantially increasing run time performance, a namespace mechanism allowing all those packages to coexist, a high quality C library for statistical computing, a new graphics engine, a dynamic HTML help system, and a package management system which very conveniently allows to build, check and deploy extensions to the base system, and much more.
It is through the combination of providing a high quality base system, and mechanisms and infrastructure for extending this base system, that R has become the common language of statistics and data science. Methodological innovations in modern statistics are typically obtained using R and freely provided as R extension packages, making them accessible to everyone. By keeping R free and open-source under the GNU General Public License, the R Core Team removed many of the financial barriers that have historically limited access to advanced analytics software. Due to this increased accessibility, millions of users including researchers, students, hospitals, public health organizations, and governments around the world are able to utilize the same statistical tools regardless of institutional resources, also in developing countries. Their work has transformed statistics and data science from many isolated workers writing long programs into an enthusiastic collaborative community where ideas and code are easily shared and built upon.
The efforts of the R Core Team members have been driven by the vision that everybody should have free access to the state-of-the-art of statistical methods, and therefore be able to perform better data analysis and decision making. This involves spending huge amounts of time on the ongoing work of adapting R to evolving hardware and software environments. The fact that the main R Core Team reference has been cited over 343,000 times on Semantic Scholar, and the quantity and quality of available extension packages shows that the time investment of the R Core Team has clearly paid off, with huge benefits for the wide community of users.
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Nicholas Horton
Beitzel Professor of Technology and Society (Statistics and Data Science)
Department of Statistics
Amherst College
Northampton, MA United States
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