The Summit will also introduce GBSI’s Reproducibility2020, an action plan for the biomedical research community to significantly improve the quality of research by 2020 targeting: 1) improved validation and standardization of biological reagents; 2) better tools and technologies to expand open access for reporting and sharing protocols and data; and 3) increased training that emphasizes rigorous study design and practice.

A talk given by Noam Ross: "Why was, as the title suggests, primarily focused on the benefits of reproducibility to us, and I proceeded from avoiding negatives (risk avoidance) to creating positives (more impact). In How I tried to be very high-level, talking about major concepts in reproducibility, and then talking generally about the tools that I have used for each, emphasizing that they may not be the right tools for everyone. Then we had a discussion about the most promising areas and tools to start with."

Researchers at Sweden's Karolinska Institute and Royal Institute of Technology have developed a new data analysis workflow for shotgun mass spec that could help improve the technique's quantitative reproducibility. Detailed in a paper published this month in Molecular & Cellular Proteomics, the approach uses a new quality scoring system that allows for more reliable recovery of missing data points across multiple mass spec runs.

Today the Federation of American Societies for Experimental Biology (FASEB) issued Enhancing Research Reproducibility, a set of recommendations aimed to promote the reproducibility and transparency of biomedical and biological research.

The topics of scientific rigor and data reproducibility have been increasingly covered in the scientific and mainstream media, and are being addressed by publishers, professional organizations, and funding agencies, including NIH. This webinar – the first in a series titled Training Modules to Enhance Data Reproducibility (TMEDR) – will address topics of scientific rigor as they pertain to pre-clinical neuroscience research.

R is a natural fit for a reproducibility project like this: as a scripting language, the R script itself provides a reproducible documentation of every step of the process. (Revolution R Open, Microsoft's enhanced R distribution, additionally includes features to facilitate reproducibility when using R packages.) The R script used for the psychology replication project describes and executes the process for checking the results of the papers.