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.
One of the striking things about Neo4J is how much effort has gone in to making it easy to play with. In particular, you can create GraphGists, which are simple text documents that are transformed into interactive graphs that you can query. This is fun, and I think it's also a great lesson in how to publicise a technology (compare this with RDF and SPARQL, which is in no way fun to work with).
I created some GraphGists that explore various problems with the current GBIF taxonomy. The goal is to find ways to quickly test the classifications for logical errors, and wherever possible I want to use just the information in the GBIF classification itself.
The first example is a version of the "papaya plots" that I played with in an earlier post (see also an unfinished manuscript Taxonomy as impediment: synonymy and its impact on the Global Biodiversity Information Facility's database). For various reasons, GBIF has ended up with the same species occuring more that once in its backbone classification, usually because none of its source databases has enough information on synonymy to prevent this happening.
As an example, I've grabbed the classification for the bat family Molossidae, converted it to a Neo4J graph, and then tested for the existence of species in different genera that have the same specific epithet. This is a useful (but not foolproof test) of whether there are undetected synonyms, especially if the generic placement of a set of species has been in flux (this is certainly true for these bats). If you visit the gist you will see a list of species that are potential synonyms.
A related test catches cases where one classification treats a taxon as a subspecies whereas another treats it as a full species, and GBIF has ended up with both interpretations in the same classification (e.g., the butterfly species Heliopyrgus margarita and the subspecies Heliopyrgus domicella margarita).
Another GraphGist tests that the genus name for a species matches the genus it is assigned too. This seems obvious (the species Homo sapiens belongs in the genus Homo) but there are cases where GBIF's classification fails this test, such as the genus Forsterinaria. Typically this test fails due to problematic generic names (e.g., homonyms), incorrect spellings, etc.
The last test is slightly more pedantic, but revealing nevertheless. It relies on the convention in zoology that when you write the authorship of a species name, if the name is not in the original genus then you enclose the authorship in parentheses. For example, it's Homo sapiens Linnaeus, but Homo erectus (Dubois, 1894) because Dubois originally called this species Pithecanthropus erectus.
Because you can only move a species to a genus that has been named, it follows that if a species is described before the genus name was published, then if the species is in that newer genus the authorship must be in parentheses. For example, the lepidopteran genus Heliopyrgus was published in 1957, and includes the species willi Plötz, 1884. Since this species was described before 1957, it must have been originally placed in a different genus, and so the species name should be Heliopyrgus willi (Plötz, 1884). However, GBIF has this as Heliopyrgus willi Plötz, 1884 (no parentheses). The GraphGist tests for this, and finds several species of Heliopyrgus that are incorrectly formed. This may seem pendantic, but it has practical consequences. Anyone searching for the original description of Heliopyrgus willi Plötz, 1884 might think that they should be looking for the text string "Heliopyrgus willi" in literature from 1884, but the name didn't exist then and so the search will be fruitless.
I think there's a lot of scope for deveoping tests like these, inclusing some that m make use of external data as well. In an earlier post (A use case for RDF in taxonomy ) I mused about using RDF to perform tests like this. However Neo4J is so much easier to work with I suspect that it makes better sense to develop standard queries in it's query language (CYPHER) and use those.
