That’s a lot alike Data Science, isn’t it? Hydrologic Processes evolve in space and time, are extremely complex and we may never comprehend them. For this reason Hydrologists use models where their inputs and outputs are measurable variables: climatic and hydrologic data, land uses, vegetation coverage, soil type etc.

Olfactory Coding Detecting volatile chemicals and encoding these into neuronal activity is a vital task for all animals that is performed by their olfactory sensory systems. While these olfactory systems vary vastly between species regarding their numerical complexity, they are amazingly similar in their general structure.

I am happy to say that the latest issue of The R Journal includes a paperdescribing rentrez,the rOpenSci package for retrieving data from the National Center for Biotechnology Information(NCBI). The NCBI is one of the most important sources of biological data. The centreprovides access to information on 28 million scholarly articles through PubMed and 250million DNA sequences through GenBank.

At rOpenSci, our R package peer review process relies on the the hard work of many volunteer reviewers. These community members donate their time and expertise to improving the quality of rOpenSci packages and helping drive best practices into scientific software. Our open review process, where reviews and reviewers are public, means that one benefit for reviewers is that they can get credit for their reviews.

To give you an idea of where I am in my R developer germination, I’d just started reading about testing when I received an email from @rOpenSci inviting me to review the weathercan package. Many of us in the R community feel like imposters when it comes to software development. In fact, as a statistician, it was a surprise to me when I was recently called a developer.

I love working with R and have been sharing the love with my friends and colleagues for almost seven years now.

rOpenSci is holding our annual staff and leadership meeting in Vancouver, so we’re taking the opportunity to share what we do and, if you’re interested, how you can get involved. Join us for a series of 7 short talks and demos followed by informal networking over snacks & refreshments. rOpenSci is a non-profit initiative that promotes open and reproducible research using shared data and reusable software.

webmockr webmockr is an R library for stubbing and setting expectations on HTTP requests.It is a port of the Ruby gem webmock. webmockr works by plugging in to another R package that does HTTP requests. It currently only works with crul right now, but we plan to add support for curl and httr later.

Earlier this month we released a new version of the tesseract package to CRAN. This package provides R bindings to Google’s open source optical character recognition (OCR) engine Tesseract. Two major new features are support for HOCR and support for the upcoming Tesseract 4. hOCR output Support for HOCR output was requested by one of our users on Github.

rOpenSci’s mission is to enable and support a thriving community of researchers who embrace open and reproducible research practices as part of their work. Since our inception, one of the mechanisms through which we have supported the community is by developing high-quality open source tools that lower barriers to working with scientific data.