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🔗 We’ve been busy We have been busy hacking away at code and our website. Here is an update on what we’ve been up to. 🔗 Packages rplos/alm PLoS provides two different API services: the Search API and ALM API. As their names suggest, the search API lets you search and get text from their papers and associated metadata. The ALM API allows you to get article level metrics data on PLoS papers....
A guest blog post by Steve Moss Why Python? A little background! I started using Python in the summer of 2010. I had applied for the Master of Research postgraduate degree in Computational Biology at the University of York. They teach the programming portion of their course using Python. I thought it might be useful to learn it, before starting, to give me a bit of a head start. From the beginning, it was clear to me, that Python was something different, in relation to all the other languages I had previously used....
This is a guest post by Class-Thido Pfaff We here present the BEFdata R package as part of the rOpenSci project. It is an API package that combines the strengths of the BEFdata portal in handling small, complex datasets with the powerful statics package R. The portal itself is free software as well and can be found here. The BEFdata platforms support interdisciplinary data sharing and harmonisation of distributed research projects collaborating with each other....
Many US federal agencies are now running app competitions to highlight their web services (see here), and hopefully get people to build cool stuff using government data (see Data.gov for more). See here for a nice list of the US government’s web services. One of these agencies was the United States Geological Survey (USGS). They opened up an app competition and [we won best overall app! Check out our app called TaxaViewer here: http://glimmer....
Real use cases from people using our software are awesome. They are important for many reasons: 1) They make the code more useable because we may change code to make the interace and output easier to understand; 2) They may highlight bugs in our code; and 3) They show us what functions users care the most about (if we can assume number of questions equates to use). If someone has a question, others are likely to have the same, or a similar question....
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