All posts (Page 100 of 121)
For a fourth year running, we are excited to announce the rOpenSci unconference, our annual event loosely modeled on Foo Camp. We’re organizing #runconf17 to bring together scientists, developers, and open data enthusiasts from academia, industry, government, and non-profits to get together for a couple of days to hack on various projects and generally enrich our community. The agenda is mostly decided during the unconference itself. Past projects have related to open data, data visualization, data publication and open science using R. This event is unlike many other unconferences in that it is primarily invite-only, with a few spots set aside for self-nominations from the community at large. That’s you!...
Programmatic access to biodiversity data is revolutionising large-scale, reproducible biodiversity research. In the marine realm, the largest global database of species occurrence records is the Ocean Biogeographic Information System, OBIS. As of January 2017, OBIS contains 47.78 million occurrences of 117,345 species, all openly available and accessible via the OBIS API. The number of questions to address using these kinds of resources is as large as the number of investigators, but certain operations commonly crop up in many workflows. In my group, shefmeme.org, these typically involve checking the taxonomy of a list of species, extracting occurrence records for each species, mapping these and matching them to various environmental and geographic data layers, all using R. I recently wrote up these common operations in a detailed tutorial for OBIS, with associated code and data on GitHub. This tutorial made extensive use of rOpenSci packages and expertise, and so I’m delighted to have the opportunity to present an edited version here. (Please note that the code chunks included here are a subset of our original code, and are for illustration - if you want to run these examples we suggest visiting the original post.)...
This week an update for xml2 and a new xslt package have appeared on CRAN. A full announcement for xml2 version 1.1 will appear on the rstudio blog. This post explains xml validation (via xsd schema) and xml transformation (via xslt stylesheets) which have been added in this release.
XML schemas and stylesheets are not exactly new; both xslt 1.1 (2001) and xsd 1.0 (2004) have been available in browsers for over a decade. Revised specifications for xsd/xslt are still developed, but not widely implemented due to declined popularity of xml itself. Our R implementation builds on libxslt which supports XSLT 1.0 features plus most of the EXSLT set of processor-portable extensions functions.
...A research project often starts with a bright idea and an initial commitment of volunteer time, or perhaps, a fixed term grant. But what happens after that initial activity? How can the project continue to sustain itself? (We define sustainability as the capacity to endure. Software is sustainable if it will continue to be available in the future, on new platforms, and meeting new needs. [This is from slide 23 of http://www.slideshare.net/danielskatz/scientific-software-challenges-and-community-responses, though it may have been taken from somewhere else earlier - if you know where, let me know.])...
Making packages is a great way to organize R code, whether it’s a set of scripts for personal use, a set of functions for internal company use or a lab group, or to distribute your new cool framework foobar to the masses. There’s a number of guides to writing packages, including http://r-pkgs.had.co.nz/.
As you develop packages there’s a number of issues that don’t often get much air time. I’ll cover some of them here.
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