About the presenter
Scott Chamberlain is a postdoctoral fellow at Simon Fraser University. In addition to doing research in ecology and evolution, Scott helped start rOpenSci (http://ropensci.org/), a collaborative effort to develop R based tools to facilitate open science.
There is immediate need for science to become more open - this can happen in four areas that make up much of the scientific workflow: data, data analysis and visualization, writing, and literature/publications. Data products from scientific research have been largely private, but open source science data sets are becoming increasingly common. For example, the Global Biodiversity Information Facility (GBIF) provides a great API for their geo-located species occurrence data, which we can use in R to easily create visualizations of species distributions. Data analysis has required extremely expensive payments for proprietary software - R solves this problem with powerful open source tools for analysis and visualization. The writing process has been dominated by expensive software such as Microsoft Word and EndNote. A number of tools are available now in R to make writing easy and reproducible. Last, publishers have been keeping publicly funded research behind pay-walls, preventing many people (even researchers) from accessing important research findings. Open access publishers are arising rapidly to fill this need. For example, the Public Library of Science (PLoS) provides an extensive API for the content and metrics on all their articles, which we can leverage in R. In this talk I will describe how the rOpenSci (http://ropensci.org/) project is attempting to facilitate open and reproducible science using R.
See http://ropensci.org/ for more details about the topic.