In the spirit of release early and release often, here is the first workable version of a biodiversity knowledge graph that I've been working on for Australian animals (for some background on knowledge graphs see Towards a biodiversity knowledge graph now in RIO). The core of this knowledge graph is a classification of animals from the Atlas of Living Australia (ALA) combined with data on taxonomic names and publications from the Australian

Earlier this year I stopped over in Singapore, home of the spectacular "supertrees" in the Garden by the Bay. The trip was a holiday, but I spent a good part of one day visiting Rudolf Meier's group at the National University of Singapore. Chatting with Rudolf was great fun, he's opinionated and not afraid to share those opinions with anyone who will listen. Belatedly I've finally written up some of the topics we discussed.

GBIF has reached 1 billion occurrences which is, of course, something to celebrate: An achievement on this scale represents a lot of work by many people over many years, years spent developing simple standards for sharing data, agreeing that sharing is a good thing in the first place, tools to enable sharing, and a place to aggregate all that shared data (GBIF). So, I asked a question: My point is not to do this: Rather it is to

I've written a short paper entitled "Liberating links between datasets using lightweight data publishing: an example using plant names and the taxonomic literature" (phew) and put a preprint on bioRxiv (https://doi.org/10.1101/343996) while I figure out where to publish it. Here's the abstract: In some ways the paper is simply a record of me trying to figure out how to publish a project that I've been working on for several years, namely

First off, let me say that what follows is a lot of arm waving to try and obscure how little I understand what I'm talking about. I'm going to sketch out what I think is a "radical" idea for a GBIF Challenge entry. The motivation for this idea comes from several sources: 1. GBIF is (under-)funded by direct contributions from governments, hence each year it essentially "begs" for money.

David Shorthouse (@dpsspiders) makes some very cool things, and his latest project World Taxonomists & Systematists is a great example of using automation to assemble a list of the world's taxonomists and systematists. The project uses ORCID.

Last year I finished my four-year stint as Chair of the GBIF Science Committee. During that time, partly as a result of my urging, GBIF launched an annual "GBIF Ebbe Nielsen Challenge", and I'm please that this year GBIF is continuing to run the challenge. In 2015 and 2016 the challenge received some great entries.

It's been a little quiet on this blog as I've been teaching, and spending a lot of time data wrangling and trying to get my head around "data lakes" and "triple stores". So there are a few things to catch up on, and a few side projects to report on. I continue to play with iSpecies, which is a simple mashup off biodiversity data sources.

The following is a guest post by Bob Mesibov. Nico Franz and Beckett Sterner created a stir last year with a preprint in bioRxiv about expert validation (or the lack of it) in the "backbone" classifications used by aggregators.

These notes are the result of a few events I've been involved in the last couple of months, including TDWG 2017 in Ottawa, a thesis defence in Paris, and a meeting of the Science Advisory Board of the Natural History Museum in London. For my own benefit if no one else's, I want to sketch out some (less than coherent) ideas for how a natural history museum becomes truly digital.

David Attenborough’s latest homage to biodiversity, Blue Planet II is, as always, visually magnificent. Much of its impact derives from the new views of life afforded by technological advances in cameras, drones, diving gear, and submersibles. One might hope that the supporting information online reflected the equivalent technological advances made in describing and sharing information. Sadly, this is not the case.