In 1998 the Association for Computing Machinery (ACM) presented its Software System Award to John Chambers for the design and development of S. The award included a prize of $10,000, which Dr. Chambers generously donated to the Statistical Computing Section to endow an annual prize for student statistical software. The prize carries with it a cash award of $2000. The award is given for the development and implementation of computational tools for the statistical profession by a graduate or undergraduate student.
Please find the submission details at http://asa.stat.uconn.edu.
On Saturday May 15, the Association for Computing Machinery (ACM) presented its prestigious Software System Award to researcher John Chambers of Bell Labs. The award was presented for the design of the S System for statistical computing, which the ACM said has "forever altered how people analyze, visualize, and manipulate data. S is an elegant, widely accepted, and enduring software system, with conceptual integrity, thanks to the insight, taste, and effort of John Chambers." And in more good news for statistical computing, Chambers announced plans to turn over his $10,000 award to the American Statistical Association to endow a new prize that will recognize outstanding student work in software for statistics.
This is the first time in its 17-year history that the Software System Award has been given for data analysis software, and the first time it has been given to a statistician. Beginning with the UNIX* System - created in 1969 by Bell Labs researchers Dennis Ritchie and Ken Thompson - the Software System Award has recognized ideas and developments that have had a major, lasting impact on computing, such as TCP/IP and the World Wide Web.
The first versions of S in the 1970s pioneered the use of data visualization and interactive statistical computing. Subsequent versions provided richly enhanced modeling capability, and user extensibility, based on its functional object-based approach.
Still more recent versions provide a powerful class/method structure, new techniques to deal with large objects, extended interfaces to other languages and files, object-based documentation compatible with HTML, and powerful interactive programming techniques. The commercial version, S-Plus, is used across many disciplines where analysts must struggle with creative ways to manage and extract useful information from data. More information about S is available at the Bell Lab's web site .
John Chambers is one of the researchers pursuing a new joint project, Omega, aimed at the next generation of statistical software. In this project, emphasis is on Java and distributed computing, with the goal of a wide range of new software in open source, benefiting and involving the whole statistical computing community. More about Omega and its activities can be found on the project web site.
Looking toward the future in another way, Chambers donated the prize money from his Software System Award - all $10,000 of it - to the ASA, to endow a prize for the best student software written to support the computing used in statistics.
The purpose of the prize, Chambers said, "is to recognize contributions in the design and implementation of software that has value for the statistical community, and to raise awareness in that community of the importance of good software to those involved in statistical applications and research." In particular, Chambers hopes the existence of the prize will foster greater recognition that software design is a key component of statistical research, deserving recognition on the same level as mathematical theory and other essential elements.
Statistical software created by undergraduate or graduate students in any field will be eligible for the prize. The prize will be administered by the Statistical Computing section of the ASA. Details of the prize will appear in future issues of the Newsletter and Amstat News.
John Chambers (right) hands over the ACM prize to 1999 Computing Section Chair Jim Rosenberger (left). The money will be used to establish an award supporting student research in statistical computing.
The review panel of the John M. Chambers Statistical Software Award consisted of Yixuan Qiu (Section on Statistical Computing), Samantha Tyler (Section on Statistical Computing; chair of the review panel) and Philip Waggoner (Section on Statistical Computing). The 2022 John M. Chambers Statistical Software Award goes to:
Hubert Baniecki (for python package dalex, https://github.com/ModelOriented/DALEX/tree/master/python/dalex
), Warsaw University of Technology.
An honorable mention goes to
Vittorio Orlandi (for R package FLAME, https://github.com/almost-matching-exactly/R-FLAME
), Duke University.
The review panel of the Chambers Statistical Software Award consisted of Brennan Bean (Section on Statistical Computing), Philip Waggoner (Section on Statistical Computing), and Samantha Tyler (Section on Statistical Computing; chair of the review panel). The 2021 John M. Chambers Statistical Software Award goes to:
The review panel of the Chambers Statistical Software Award consisted of Joyce Robbins, Deepayan Sarker, and Yihui Xie (chair). We did not grant the Chambers Statistical Software Award this year.
An honorable mention goes to:
Jialin Ma (for R package symengine, https://github.com/symengine/symengine.R), Georgia Institute of Technology.
The review panel of the Chambers Statistical Software Award consisted of Amelia McNamara, Deepayan Sarker, and Yihui Xie (chair). The 2019 John M. Chambers Statistical Software Award goes to:
An honorable mention goes to:
This year we had 12 entries. The award is shared by two winners.
- Dustin Tran (Department of Computer Science, Columbia University) for edward, a Python package for probabilistic modeling, inference, and criticism.
- Nan Xiao (School of Mathematics and Statistics, Central South University, China) for liftr, an R package for persistent reproducible reporting.
Thanks to the Chambers Award review committee consisting of Patrick Breheny (chair), Deepayan Sarkar, and Yihui Xie.
(Iowa State University).
plotly for R
Winner: Tong He (Simon Fraser University) and Tianqi Chen (University of Washington) XGBoost [additional contributors]
Honorable Mention: Spectra, by Yixuan Qiu (Purdue University)
Kyle Dwayne Bemis
University of Santiago de Compostela
Nonparametric circular methods for density and regression (NPCirc)
R. Philip Chalmers
York University, Toronto
Unidimensional and Multidimensional Item Response Modeling with the mirt Package
Jennifer Bobb and Ravi Varadhan
Johns Hopkins University
turboEM: A Suite of Convergence Acceleration Schemes for EM and MM algorithms
Deducer's Plot Builder: A General GUI for Statistical Graphics
The Bigmemory Project
Renmin University of China
Alejandro Jara Vallejos
Catholic University of Leuven
Heather Turner and David Firth
University of Warwick
Iowa State University
Reshape and ggplot
University of Augsburg
JGR - a Java GUI for R
University of Gottingen
RGL - A library linking R to Open GL
An extension to the R system allowing for 3D visualization
Lee Wilkinson, Chair of the Section (left), and Daniel Adler(right). Taken at the Joint Computing and Graphics Sections Mixer/Business Meeting in San Francisco (8/03).
University of Wisconsin -- Madison
A package implementing Trellis Graphics in R
University of Augsburg
Klassification - Interactive Methods for Trees
Interactive software for the graphical analysis of trees.
Simon Urbanek (left) and John Chambers (right). Taken at the Joint Computing and Graphics Sections Mixer/Business Meeting in New York City (8/02).
Dr. Alessandra Brazzale
Institute for Systems Science and Biomedical Engineering of the Italian National Research Council
HOA: Higher-Order Asymptotics
A library of S-PLUS functions (and data) for higher-order asymptotic inference
From left to right: Brian Smith, John Chambers and Sylvia Winkler. Taken at the Joint Computing and Graphics Sections Mixer/Business Meeting in Indianapolis (8/00).
- Sylvia Winkler
University of Augsburg
CASSATT: Coordinate Analysing Statistical Software Applying Tandem Transformations
The interactive software CASSATT has been developed to visualise high-dimensional, multivariate data using parallel coordinates. CASSATT is platform independent and widens the range of methods for analysing parallel coordinate data. CASSATT uses interactive tools to extend the basic graphic displays.
- Brian Smith
University of Iowa
BOA: Bayesian Output Analysis Program
BOA is an S-PLUS/R program for carrying out convergence diagnostics and statistical and graphical analysis of Monte Carlo sampling output. It can be used as an output processor for the BUGS software or for any other program which produces sampling output.