Working together to push science forward
Happy rOpenSci users can be found at
A new version of rentrez, our package for the NCBI’s EUtils API, is making it’s way around the CRAN mirrors. This release represents a substantial improvement to rentrez, including a new vignette that documents the whole package. This posts describes some of the new things in rentrez, and gives us a chance to thank some of the people that have contributed to this package’s development. Thanks Thanks to everyone who has filed and issue or written us an email about rentrez, your contributions have been an important part of the package’s development....
We’re happy to announce the launch of a CRAN-style repository for rOpenSci at http://packages.ropensci.org This repository contains the latest nightly builds from the master branch of all rOpenSci packages currently on GitHub. This allows users to install development versions of our software without specialized functions such as install_github(), allows dependencies not hosted on CRAN to still be resolved automatically, and permits the use of update.packages(). Using the repository To use, simply add packages....
Despite the hype around “big data”, a more immediate problem facing many scientific analyses is that large-scale databases must be assembled from a collection of small independent and heterogeneous fragments – the outputs of many and isolated scientific studies conducted around the globe. Collecting and compiling these fragments is challenging at both political and technical levels. The political challenge is to manage the carrots and sticks needed to promote sharing of data within the scientific community....
There are many different databases. The most familiar are row-column SQL databases like MySQL, SQLite, or PostgreSQL. Another type of database is the key-value store, which as a concept is very simple: you save a value specified by a key, and you can retrieve a value by its key. One more type is the document database, which instead of storing rows and columns, stores blobs of text or even binary files....
There are two things that make R such a wonderful programming environment - the vast number of packages to access, process and interpret data, and the enthusiastic individuals and subcommunities (of which rOpenSci is a great example). One, of course, flows from the other: R programmers write R packages to provide language users with more features, which makes everyone’s jobs easier and (hopefully!) attracts more users and more contributions. But what if you have an idea, or a need, but not the time or confidence to write a package for it?...
Happy rOpenSci users can be found at