After a winter break of working at half-speed, I’m finding it a little daunting to face the overwhelming number of projects that need my attention in the new year. As I sort through and prioritize the ones where the biggest fires are raging, I also like to use this time to reevaluate how I go about these activites and identify areas for improvement. If you’re in the same mental state right now, I’d like you to consider making your science a little more open as a challenge to take on in 2013.
More and more research published these days is difficult to replicate, validate, or build upon without all the critical components such as the underlying data and the code that was used to analyze it. Although support for open data and open science is steadily growing in the research community, putting this into practice requires some upfront investment. Since there is often no immediate incentives or payoff, activities such as documenting code, metadata, and making both available in permanent repositories with appropriate licences end up taking the back seat.
At rOpenSci, my fantastic colleagues and I have been building various R packages that make it easy to retrieve and reuse existing data and also share your research output through persistent repositories. If you’ve come across some of these before and found them useful, but hesitated because of the learning curve associated with using them for a real world project, you’re in luck! We’re offering our time and expertize to help you make your efforts (however small) to reuse data (or share your own research output) a reality. Our current suite of packages get you access to a rich variety of data from phylogenetic databases, taxonomic databases, fisheries time series, to full-text of any PLOS article and various scienceometrics datasets. Perhaps the tutorials might inspire you. Even if you’re only working with data you collected, you can use rOpenSci tools to programmatically clean, and submit your data, code, and/or manuscript pre-prints to figshare, a free science repository that will give you a permanent location (with a doi) to share with colleagues. If you have additional data sources in mind that don’t have an associated R package, drop us a line. We might be able to put together something fairly quickly for you to use (or we’ll add it to our existing todo list).
Learn more about the Open Science challenge and get in touch.