One of GBIF's goals is to provide up to date, comprehensive data on the distribution of species. Although GBIF's taxonomy and geographic scope is global, not all species are equal, in the sense that the need for information on some species is potentially much more pressing. An example are mosquitoes of the genus Aedes , such as the species A. aegypti and A. albopictus that spread the Zika virus.

The Natural History Museum has released their data portal (http://data.nhm.ac.uk/). As of now it contains 2,439,827 of the Museum's 80 million specimens, so it's still early days. I gather that soon this data will also appear in GBIF, ending the unfortunate situation where data from one of the premier natural history collections in the world was conspicuous by its absence.

My BioNames project has been going for over a year now, but I hadn't gotten around to providing bulk access to the data I've been collecting and cleaning. I've gone some way towards fixing this. You can now grab a snapshot of the BioNames database as a Darwin Core Archive here.

This is guest post by Angelique Hjarding in response to discussion on this blog about the paper below. Thank you for highlighting our recent publication and for the very interesting comments. We wanted to take the opportunity to address some of the issues brought up in both your review and from reader comments. One of the most important issues that has been raised is the sharing of cleaned and vetted datasets.

TL;DR By using bookmarklets and a central annotation store, we can build a system to annotate any biodiversity database, and display those annotations on those databases. A couple of weeks ago I was at GBIF meeting in Copenhagen, and there was a discussion about adding a new feature to the GBIF portal. The conversation went something like this: Resources are limited, and adding new features to a project can be difficult.

There is a great post by Jeni Tennison on the Open Data Institute blog entitled Five Stages of Data Grief. It resonates so much with my experience working with biodiversity data (such as building BioNames, or exploring data errors in GBIF) that I've decide to reproduce it here.

Bryan Drew and colleagues have published a piece in PLoS Biology bemoaning the lack of databased phylogenies: This is an old problem (see for example "Towards a Taxonomically Intelligent Phylogenetic Database" doi:10.1038/npre.2007.1028.1), but alas the solution proposed by Drew et al. is also old: In my opinion, as soon as you start demanding people do something you've lost the argument, and you're relying on power ("you don't get to publish

Benoît Fontaine et al. recently published a study concluding that average lag time between a species being discovered and subsequently described is 21 years. The paper concludes: This is a conclusion that merits more investigation, especially as the title of the paper suggests there is an appalling lack of efficiency (or resources) in the way we decsribe biodiversity.

Now we are awash in challenges! EOL has announced its Computable Data Challenge: Some $US 50,000 is on offer. "Challenge" is perhaps a misnomer, as EOL is offering this money not as a prize at the end, but rather to fund one or more proposals (submitted by 22 May) that are accepted.

Interest in archiving data and data publication is growing, as evidenced by projects such as Dryad, and earlier tools such as TreeBASE. But I can't help wondering whether this is a little misguided. I think the issues are granularity and reuse. Taking the second issue first, how much re-use do data sets get? I suspect the answer is "not much". I think there are two clear use cases, repeatability of a study, and benchmarks.