The goal of my BioNames project is to link every taxonomic name to its original description (initially focussing on animal names). The rationale is that taxonomy is based on evidence, and yet most of this evidence is buried in a non-digitised and/or hard to find literature. Surfacing this information not only makes taxonomic evidence accessible (see Surfacing the deep data of taxonomy), it also surfaces a lot of basic biological information.

In a classic paper Boggs (1949) appealed for an “atlas of ignorance”, an honest assessment of what we know we don’t know: This is the theme of this year's GBIF Challenge: Analysing and addressing gaps and biases in primary biodiversity data. "Gaps" can be gaps in geographic coverage, taxa group, or types of data. GBIF is looking for ways to access the nature of the gaps in the data it is aggregating from its network of contributors.

BioStor now has 150,000 articles. When I wrote a paper describing how BioStor worked it had 26,784 articles, so things have progressed somewhat! I continue to tweak the interface to BioStor, trying different ways to explore the articles. Spatial search I've tweaked spatial search in BioStor.

Some notes on containers, microservices, and data. The idea of packaging software into portable containers and running them either locally or in the cloud is very attractive (see Docker). Some use cases I'm interested in exploring.

I've been experimenting with simple spatial search in BioStor, as shown in the demo below. If you go to the map on BioStor you can use the tools on the left to draw a box or a polygon on the map, and BioStor will search it's database for articles that mention localities that occur in that region. If you click on a marker you can see the title of the article, clicking on that title takes you to the article itself.

In between complaining about the lack of open data in biodiversity (especially taxonomy), and scraping data from various web sites to build stuff I'm interested in, I occasionally end up having interesting conversations with the people whose data I've been scraping, cleaning, cross-linking, and otherwise messing with. Yesterday I had one of those conversations at Kew Gardens.

In the previous post I sketched out a workflow to annotate articles using hypothes.is and aggregate those annotations.

I will be at ReCon 16 in Edinburgh (hashtag #ReCon_16), the second ReCon event I've attended (see Thoughts on ReCon 15: DOIs, GitHub, ORCID, altmetric, and transitive credit). For the hack day that follows I've put together some instructions for a way to glue together annotations made by multiple people using hypothes.is. It works by using IFTTT to read a user's annotation stream (i.e., the annotations they've made) and then post those to a

The last few days I've been re-reading articles about Ted Nelson's work (including ill-fated Project Xanadu), reading articles celebrating his work (brought together in the open access book "Intertwingled"), playing with Hypothes.is, and thinking about annotation and linking.

Given that Wikipedia, Wikidata, and the Biodiversity Heritage Library (BHL) all share the goal of making information free, open, and accessible, there seems to be a lot of potential for useful collaboration. Below I sketch out some ideas. BHL as a source of references for Wikipedia Wikipedia likes to have sources cited to support claims in its articles. BHL has a lot of articles that could be cited by Wikipedia articles.

I'll be taking a break shortly, so I thought I'd try to gather some thoughts on a few projects/ideas that I'm working on. These are essentially extended notes to myself to jog my memory when I return to these topics. BOLD data into GBIF Following on from work on getting mosquito data into GBIF I've been looking at DNA barcoding data. BOLD data is mostly absent from GBIF.