Yet another barely thought out project, although this one has some crude code. If some 16,000 new taxonomic names are published each year, then that is roughly 40 per day. We don't have a single place that aggregates these, so any major biodiversity projects is by definition out of date. GBIF itself hasn't had an update list of fungi or plant names for several years, and at present doesn't have an up to date list of animal names.

I need more time to sketch this out fully, but I think a case can be made for a taxonomy-centric (or, perhaps more usefully, a biodiversity-centric) clone of PubMed Central. Why? We already have PubMed Central, and a European version Europe PubMed Central, and the content of Open Access journals such as ZooKeys appears in both, so, again, why?

One of the limitations of the Biodiversity Heritage Library (BHL) is that, unlike say Google Books, its search functions are limited to searching metadata (e.g., book and article titles) and taxonomic names. It doesn't support full-text search, by which I mean you can't just type in the name of a locality, specimen code, or a phrase and expect to get back much in the way of results.

One of the less glamorous but necessary tasks of data cleaning is mapping "strings to things", that is, taking strings such as "George A. Boulenger" and mapping them to identifiers, such as ISNI: 0000 0001 0888 841X. In case of authors such as George Boulenger, one way to do this would be through Wikipedia, which has entries for many scientists, often linked to identifiers for those people (see the bottom of the Wikipedia page for George A.

Following on from Testing the GBIF taxonomy with the graph database Neo4J I've added a more complex test that relies on linking taxa to names. In this case I've picked some legume genera ( Coursetia and Poissonia ) where there have been frequent changes of name.

Imagine a web site where researchers can go, log in (easily) and get a list of all the species they have described (with pretty pictures and, say, GBIF map), and a list of all DNA sequences/barcodes (if any) that they've published. Imagine that this is displayed in a colourful way (e.g., badges), and the results tweeted with the hastag #itaxonomist.

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.

Note to self about a possible project. This PLoS ONE paper: describes a method for inferring a hierarchy from a set of tags (and cites related work that is of interest). I've grabbed the code and data from http://hiertags-beta.elte.hu/home/ and put it on GitHub. Possible project Use Tibély et al. method (or others) on taxonomic names extracted from BHL text (or other) and see if we can reconstruct taxonomic classifications.

One of my pet projects is BioStor, which has been running since 2009 (gulp). BioStor extracts articles from the Biodiversity Heritage Library (details here: http://dx.doi.org/10.1186/1471-2105-12-187), and currently has over 110,000 articles, all open access. The site itself is showing its age, both in terms of performance and design, so I've wanted to update it for a while now.

Quick notes on modelling taxonomic names in databases, as part of an ongoing discussion elsewhere about this topic. Simple model One model that is widely used (e.g., ITIS, WoRMS) and which is explicit in Darwin Core Archive is something like this: We have a table for taxa and we don't distinguish between taxa and their names. the taxonomic hierarchy is represented by the parentID field, which points to your parent.

In my (previous post ) I discussed the potential for the Biodiversity Data Journal (BDJ) to be a venue for nano (or near-nano publications). In this post I want to draw attention to what I think is a serious stumbling block, which is the lack of machine readable statements in the journal.