I keep returning to the problem of viewing large graphs and trees, which means my hard drive has accumulated lots of failed prototypes. Inspired by some recent discussions on comparing taxonomic classifications I decided to package one of these (wildly incomplete) prototypes up so that I can document the idea and put the code somewhere safe.

Garnett et al. recently published a paper in PLoS Biology that starts with the sentence "Lists of species matter": This paper (one of a forthcoming series) is pretty much the kind of paper I try and avoid reading.

These are simply notes to myself about taxonomic classifications in Wikidata. Classifications in Wikidata can be complex and are often not trees. For example, if we trace the parents of the frog family Leptodactylidae back we get a graph like this: Each oval represents a taxon in Wikidata, and each arrow connects a taxon to its parent(s) in Wikidata.

Given my renewed enthusiasm for Wikidata, I'm trying to get my head around the way that Wikidata models biological taxonomy. As a first pass, here's a diagram of the properties linked to a taxonomic name. The model is fairly comprehensive, it includes relationships between names (e.g, basionym, protonym, replacement), between taxa (e.g., parent taxon), and links to the literature.

There's a slow-burning discussion on taxonomic concepts on Github that I am half participating in. As seems inevitable in any discussion of taxonomy, there's a lot of floundering about given that there's lots of jargon - much of it used in different ways by different people - and people are coming at the problem from different perspectives. In one sense, taxonomy is pretty straightforward.

Following on from adding DNA barcodes to GBIF I've now uploaded a taxonomic classification of DNA barcode BINs (Barcode Index Numbers). Each BIN is a cluster of similar DNA barcodes that is essentially equivalent to a species.

I've been playing with the graph database Neo4J to investigate aspects of the classification of taxa in GBIF's backbone classification. Neo4J is a graph database, and a number of people in biodiversity informatics have been playing with it. Nicky Nicolson at Kew has a nice presentation using graph databases to handle names Building a names backbone, and the Open Tree of Life project use it in their tree machine.

There is a fairly scathing editorial in Nature [The new zoo. (2013). Nature, 503(7476), 311–312. doi:10.1038/503311b ] that reacts to a recent paper by Dubois et al.: To quote the editorial: Ouch! But Dubois et al.'s paper pretty much deserves this reaction - it's a reactionary rant that is breathtaking in it's lack of perspective.

One feature I've always wanted to have in BioNames is a timeline of taxonomic names. ION has one (see here), but I wanted a way to go from the timeline to the actual publications. In other words, if, say, there were approximately 99 bird names published in 2012, I want to see the papers that published those names.

Readers of this blog will know that I'm sceptical about the current value of linked data and RDF in biodiversity informatics. But I came across an interesting paper on RDF and biocuration that suggests a good "use case" for RDF in constructing and curating taxonomic databases. The paper is "Catching inconsistencies with the semantic web: a biocuration case study" (PDF here) by Jerven Bolleman and Sebastien Gehant.