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rOpenSci, Statistical Software, and the R Validation Hub

By Mark Padgham on September 21, 2020

Background rOpenSci is an organization devoted to “transforming science through data, software and reproducibility.” One of rOpenSci’s focal activities is peer review of R packages, historically focusing on packages that cover the data management lifecycle. This has historically excluded software implementing statistical methods, for which standards and review require addressing a different set of challenges. This year, we have begun tackling these so as to expand our peer review system to explicitly encompass statistical software, under project funded by the Alfred P.

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Risk Assessment Application

By Andy Nicholls on August 5, 2020

Background Towards the end of 2019, the R Validation Hub received an additional grant from the R Consortium to progress the next phase of our road map and produce a risk assessment app to complement the riskmetric package. In early 2020, Fission Labs were selected as our partner to build the first iteration of the application. Fission Labs is a software product development services company delivering product life-cycle management and high-end scalable technology solutions.

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Status Update July 2020

By Juliane Manitz on July 20, 2020

It’s time to bring some updates to you on the current status of the R validation hub and we are have plenty of great developments. Fission has finished their work on the R package risk assessment app and made the source code is available on github. It is an interactive web application providing a front end for the collection of metrics for R packages via riskmetric package including visualizations and comparison metrics.

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Introduction to the R Package `riskmetric`

By Juliane Manitz, Douglas Kelkhoff, Eli Miller, and Yilong Zhang on June 9, 2020

Many contributed R packages lack documentation expected in software qualification, which is required within pharma and other regulated industries. For pharma, there are various regulations, which require documentation that demonstrates software is used appropriately and works as expected. Thus, industry needs to establish appropriate requirements for R packages using selected metadata and useful risk metrics. In context of the R Validation Hub, the R package riskmetric has been developed, which seeks to take the first steps in identifying metrics and best practices to quantify the quality of R packages.

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Participating Organisations

Members of the following organisations are participating in this project