Lecture: A Noob's Guide to Reproducibility

Lecture on January 25, 2016; 4:00pm to 5:00pm; 3110 Etcheverry Hall at Berkely Institute of Data Science. What does it mean to work reproducibly and transparently? Why bother? Whom does it benefit, and how? What will it cost me? What work habits will I need to change? Will I need to learn new tools? What resources help? What's the simplest thing I can do to make my work more reproducible? How can I move my discipline, my institution, and science as a whole towards reproducibility?

Upcoming Webinar: Scientific Rigor and Data Reproducibility

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's role in science breakthrough: reproducibility of psychology studies

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.

A Proactive Approach to Reproducibility with Evidence-Based Research on Research

The new Meta-Research Section in PLOS Biology is not the only example of how PLOS strives to improve the scientific endeavor through innovative communication efforts. PLOS has always recognized that publication of studies that reproduce published work or null results, either confirming or refuting the original result, is essential for progress in research. In fact, the largest journal at PLOS, PLOS ONE, is one of only a handful of publications that actively encourage these types of submissions with The Missing Pieces Collection.

Reproducibility at SC16 with the Student Cluster Competition

Replication and reproducibility of experimental computer science results in peer-reviewed paper is gaining relevance in the HPC community. SC, the leading conference in the field, wants to promote and support replication and reproducibility through a new initiative that aims to integrate aspects of past technical papers into the Student Cluster Competition (SCC). SC16 invites authors of technical papers accepted at past SC conferences, including SC15, to submit proposals for case studies based on applications and tests in their SC paper that can be transformed into benchmarks for the SCC. This initiative provides SC authors with the unique opportunity to further promote their published research as an example of replicable and reproducible experimental computer science.