More fictional taxa and the myth of the expert taxonomic database

I know I'm starting to sound like a broken record, but the more I look, the more taxonomic databases seem to be full of garbage. Databases such as the Catalogue of life, which states that it is a "quality-assured checklist" have records that are patently wrong. Here's yet another example.

If you search for the genus Raymondia in the Catalogue of Life you get multiple occurrences of the same species names, e.g.:

• Raymondionymus fossor Ganglebauer, L., 1906
• Raymondionymus fossor Hustache, A., 1930

Both of these are listed as "provisionally accepted names", supplied by WTaxa: Electronic Catalogue of Weevil names (Curculionoidea). Clearly we can't have two species with the same name, so what's happening?

Firstly, Hustache, A., 1930 is:

Hustache A (1930) Curculionidae Gallo-Rhénans. Annales de la Société entomologique de France 99: 81-272. http://gallica.bnf.fr/ark:/12148/bpt6k6112240j/f3

On p. 246 Hustache refers to Raymondionymus fossor Aubé, 1864 (see below).



So, Raymondionymus fossor Hustache, A., 1930 is not a new species but simply the citation of a previously published one (it's a chresonym). Hustache cites the author of the name as Aubé, 1864, and you can see the original description by Aubé in BioStor (Description de six espèces nouvelles de Coléoptères d'Europe dont deux appartenant a deux genres nouveaux et aveugles, http://biostor.org/reference/104589). So, if the taxonomic authority should be Aubé, 1864, what about Raymondionymus fossor Ganglebauer, L., 1906? Again, if we track down the original publication (Revision der Blindrüsslergattungen Alaocyba und Raymondionymus, http://biostor.org/reference/104591) it's simply Ganglebauer citing (on p. 142) Aubé's paper, not describing a new species.

Note that the nomenclature of this weevil species is further complicated because Aubé originally described the species as Raymondia fossor, but Raymondia was already in use for a fly (see Über eine neue Fliegengattung: Raymondia, aus der Familie der Coriaceen, nebst Beschreibung zweier Arten derselben, http://biostor.org/reference/104588). To resolve this homonymy Wollaston proposed the name Raymondionymus:

Wollaston, T. V. (1873). XVIII. On the Genera of the Cossonidae. Transactions of the Royal Entomological Society of London, 21(4), 427–652. doi:10.1111/j.1365-2311.1873.tb00645.xhttp://biostor.org/reference/51301

So, we have a bit of a mess. Unfortunately this mess percolates up through other databases, for example EOL has three different pages for Raymondionymus fossor.

For me the lesson here is that relying on acquiring data from "trusted" sources, curated by "experts" is simply not a tenable strategy for building lists of taxa. If names are essential bits of biodiversity infrastructure upon which we hang other data, then these lists need to be cleaned, which means exposing them to scrutiny, and providing an easy means for errors to be flagged and corrected. Trust is something that is earned, not asserted, and it's time taxonomic databases stop claiming to be authoritative simply because they rely on expert sources. Expertise is no guarantee that you won't make errors.

For me this is one of the key reasons projects like BHL are so important. As more and more of the original literature becomes available, we lessen our reliance on "expertise". We can start to see for ourselves. In other words, "Nullius in verba" ("take nobody's word for it").

The GBIF classification is broken — how do we fix it?

This post arose from an ongoing email conversation with Tony Rees about extracting and annotating taxonomic names. In BioStor I use the GBIF classification to display the taxonomic names found in the OCR text in the form of a tree. The idea is to give the reader a sense of "what the paper is about". I also use the classification to help link to GBIF occurrence records.

The GBIF backbone classification ("nub") is probably the single largest classification of life that has been assembled, and provides GBIF users with a way to navigate through GBIF's collection of specimen and observation records. Given the scale of the undertaking it is inevitable that there will be issues with the classification, and this post provides one example.

On the page for the article "Further additions to the known marine Molluscan fauna of St. Helena" (http://biostor.org/reference/88554, see also http://dx.doi.org/10.1080/00222939208677383) part of the classification looks like this:

└Animalia
 └Annelida
  └Polychaeta
   └Sabellida
    └Serpulidae
     └Hipponyx

Tony points out that "Hipponyx" is a mollusc, yet in the GBIF classification appears in the annelid worms.

Like a fool I started to investigate further. First off, what is "Hipponyx"? Browsing the GBIF classification there are species of Hipponyx and Hipponix under the genus Hipponix, so it looks like we have two alternative spellings of this genus name. Nomenclator Zoologicus has both spellings, Hipponix credited to DeFrance 1819 Journ. de Physique, 88, 217, and Hipponyx credited to Defrance 1819 Bull. Sci. Soc. philom. Paris, 8. Gotta love those cryptic citations. After some digging around in BHL I found Journ. de Physique, 88, 217 (Mémoire sur un nouveau genre de mollusque) and Bull. Sci. Soc. philom. Paris, 8. (Sur un nouveau genre de coquilles (Hipponix)). Both papers are by Jacques Louis Marin DeFrance, and both use the spelling Hipponix (no 'y'). I'm guessing the second paper is actually the original description of the genus, but my French is abysmal (Google Translate to the rescue).

OK, so we have two spellings of what is probably the same thing (and I've no idea why we have two spellings). Both spellings seem in use (see Google NGrams chart below).

Source: books.google.com via Roderic on Pinterest

So, bit of a mess, but this still doesn't deal with Hipponyx being a worm in GBIF. After a bit of Googling on "Serpulidae" and "Hipponyx" I came across a specimen record from Te Papa labelled "Worm, Temporaria inexpectata (Mestayer, 1929); holotype; holotype of Hipponyx inexpectata Mestayer, 1929". I then came across this paper:

Fleming, C. A. (1971). A preliminary list of New Zealand fossil polychaetes. New Zealand Journal of Geology and Geophysics, 14(4), 742–756. doi:10.1080/00288306.1971.10426332

with the following abstract:

An annotated list of fossil “worm tubes” from New Zealand includes both published and new records from Mesozoic and Cenozoic deposits.

The binomen Zoophycos plicatus (Hutton) is proposed for the trace fossil long known as the Amuri fucoid, of unknown zoological affinity.

The following living species are recorded as New Zealand fossils for the first time: Protula bispiralis (Savigny), Salmacina dysteri (Huxley), Hydroides norvegicus Gunnerus, Pomatoceras cariniferus (Gray), P. aff. terranovae (Benham), Galeolaria hystrix (Moerch), Boccardia ? polybranchia (Haswell); new records of fossil species are Ditrupa cf. plana (Sowerby), Dorsoserpula lumbricalis (Schlotheim), and Neomicrorbis crenatostriatus (Münster). The name Hipponyx inexpectata Mestayer 1929, applied to a serpulid operculum, is used in the combination Temporaria inexpectata for a tubeworm common in deep water off New Zealand that has also been identified, with associated operculum, from the bathyal Waitotaran (Pliocene) sediments of Palliser Bay. Serpula wharjensis Wilkens and S. ougenensis Chapman are placed in Sclerostyla Moerch. Two species of Vermiliopsis and two of Spirorbis are figured but not named specifically.

The author of the paper (Charles Fleming) argues that Hipponyx inexpectata, regarded as a mollusc by its describer (Marjorie K. Mestayer, see Notes on New Zealand Mollusca. No. 4.) is actually a worm, and he moves it to the genus Temporaria.

So it seems that the reason Hipponyx has ended up being a worm in the GBIF classification is due to this synonymy.

Now, this little investigation was "fun", but took a couple of hours. Much of that was spent tracking down the literature and adding it to BioStor, which is a one-time cost. Not every issue with the GBIF classification will take this long to resolve, some cases may take longer. So there's a problem of scalability. Then there's the issue of how this information gets into the GBIF classification so we fix it (and so that people don't think Hipponyx is a worm). As has been said several times before, most eloquently by David Shorthouse, isn't it time we started using software development tools such as version control to help build, annotate, and correct classifications such as the one that underpins GBIF? That way when somebody spots an error it can be flagged, and someone with the time (and curiosity) can fix it.

Clustering strings

Revisiting an old idea (Clustering taxonomic names) I've added code to cluster strings into sets of similar strings to the phyloinformatics course site.

This service (available at http://iphylo.org/~rpage/phyloinformatics/services/clusterstrings.php) takes a list of strings, one per line, and returns a list of clusters. For example, given the names

Ferrusac 1821
Bonavita 1965
Ferussa 1821
Fer.
Lamarck 1812
Ferussac 1821

the service finds three clusters, displayed here using Google images:



(Note to self, investigate canviz as an alternative for displaying graphviz graphs.)

If you are curious, these strings are taxonomic authorities associated with the name Helicella, and based on this clustering there are three taxonomic names, one of which has three different variations of the author's name.

Using Google Refine and taxonomic databases (EOL, NCBI, uBio, WORMS) to clean messy data

Google Refine is an elegant tool for data cleaning. One of its most powerful features is the ability to call "Reconciliation Services" to help clean data, for example by matching names to external identifiers. Google Refine comes with the ability to use Freebase reconciliation services, but you can also add external services. Inspired by this I've started to implement services to reconcile taxonomic names.

The services I've implemented so far are:

• EOL http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_eol.php
• NCBI taxonomy http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_ncbi.php
• uBio FindIT http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_ubio.php
• WORMS http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_worms.php
• GBIF http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_gbif.php
• Global Names Index http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_globalnames.php

To use these you need to add the URLs above to Google Refine (see example below). The EOL, NCBI and WORMS do a basic name lookup. The uBio FindIT service extracts a taxonomic name from a string, and can be viewed as a "taxonomic name cleaner".

How to use reconciliation services

Start a Google Refine session. Save the names below to a text file and open it as a new project.

Names
Achatina fulica (giant African snail)
Acromyrmex octospinosus ST040116-01
Alepocephalus bairdii (Baird's smooth-head)
Alaska Sea otter (Enhydra lutris kenyoni)
Toxoplasma gondii
Leucoagaricus gongylophorus
Pinnotheres
Themisto gaudichaudii
Hyperiidae

You should see something like this:


Click on the column header Names and choose Reconcile → Start reconciling.



A dialog will popup asking you to select a service.



If you've already added a service it will be in the list on the left. If not, click the Add Standard Services... button at the bottom left and paste in the URL (in this case http://iphylo.org/~rpage/phyloinformatics/services/reconciliation_ubio.php).

Once the service has loaded click on Start Reconciling. Once it has finished you should see most of the names linked to uBio (click on a name to check this):



Sometimes there may be more than one possible match, in which case these will be listed in the cell. Once you have reconciled the data you may want to do something with the reconciliation. For example, if you want to get the ids for the names you've just matched you can create a new column based on the reconciliation. Click on the Names column header and choose Edit column → Add column based on this column.... A dialog box will be displayed:



In the box labelled Expression enter cell.recon.match.id and give the column a name (e.g., "NamebankID"). You will now have a column of uBio NamebankIDs for the names:



You could also get the names uBio extracted by creating a column based on the values of cell.recon.match.name. To compare this with the original values, click on the Names column header and choose Reconcile → Actions → Clear reconciliation data. Now you can see the original input names, and the string uBio extracted from each name:



These are some very simple ideas for using Google Refine with taxonomic name services. Obvious extensions would to use services that provide an "accepted name", or services that support approximate string matching so you could catch spelling mistakes (most of the services I've implemented here have some degree of support for these features).

Development notes
The code for these services is in Github (undocumented as yet, that's on the to do list). I had a few hiccups getting these services to work. There is detailed documentation at http://code.google.com/p/google-refine/wiki/ReconciliationServiceApi, but this seems a little out of step with what actually happens. Based on the documentation I thought Google Refine called a reconciliation service using HTTP GET, but in fact it uses POST. Google Refine always called my reconciliation service using "Multiple Query Mode", which meant supporting this mode wasn't optional. Once these issues were sorted out (turning on the Java console as per David Huynh's tip helped) things work pretty well.

Mendeley mangles my references: phantom documents and the problem of duplicate references

One issue I'm running into with Mendeley is that it can create spurious documents, mangling my references in the process. This appears to be due to some over-zealous attempts to de-duplicate documents. Duplicate documents is the number one problem faced by Mendeley, and has been discussed in some detail by Duncan Hull in his post How many unique papers are there in Mendeley?. Duncan focussed on the case where the same article may appear multiple times in Mendeley's database, which will inflate estimates of how many distinct references the database contains. It also has implications for metrics derived from the Mendeley, such as those displayed by ReaderMeter.

In this post I discuss the reverse problem, combining two or more distinct references into one. I've been uploading large collections of references based on harvesting metadata for journal articles. Although the metadata isn't perfect, it's usually pretty good, and in many cases linked to Open Access content in BioStor. References that I upload appear in public groups listed on my profile, such as the group Proceedings of the Entomological Society of Washington.

Reverse engineering Mendeley
In the absence of a good description by Mendeley of how their tools work, we have to try and figure it out ourselves. If you click on a refernece that has been recently added to Mendeley you get a URL that looks like this: http://www.mendeley.com/c/3708087012/g/584201/magalhaes-2008-a-new-species-of-kingsleya-from-the-yanomami-indians-area-in-the-upper-rio-orinoco-venezuela-crustacea-decapoda-brachyura-pseudothelphusidae/ where 584201 is the group id, 3708087012 is the "remoteId" of the document (this is what it's called in the SQLite database that underlies the desktop client), and the rest of the URL is the article title, minus stop words.

After a while (perhaps a day or so) Mendeley gets around to trying to merge the references I've added with those it already knows about, and the URLs lose the group and remoteId and look like this: http://www.mendeley.com/research/review-genus-saemundssonia-timmerman-phthiraptera-philopteridae-alcidae-aves-charadriiformes-including-new-species-new-host/ . Let's call this document the "canonical document" (this document also has a UUID, which is what the Mendeley API uses to retrieve the document). Once the document gets one of these URLs Mendeley will also display how many people are "reading" that document, and whether anyone has tagged it.

But that's not my paper!
The problem is that sometimes (and more often than I'd like) the canonical document bears little relation to the document I uploaded. For example, here is a paper that I uploaded to the group Proceedings of the Entomological Society of Washington:

Review of the genus Saemundssonia Timmermann (Phthiraptera: Philopteridae) from the Alcidae (Aves: Charadriiformes), including a new species and new host records by Roger D Price, Ricardo L Palma, Dale H Clayton, Proceedings of the Entomological Society of Washington, 105(4):915-924 (2003).

You can see the actual paper in BioStor: http://biostor.org/reference/57185. To see the paper in the Mendeley group, browse it using the tag Phthiraptera:

Note the 2, indicating that two people (including myself) have this paper in their library. The URL for this paper is http://www.mendeley.com/research/review-genus-saemundssonia-timmerman-phthiraptera-philopteridae-alcidae-aves-charadriiformes-including-new-species-new-host/, but this is not the paper I added!.

What Mendeley displays for this URL is this:

Not only is this not the paper I added, there is no such paper! There is a paper entitled "A new genus and a new species of Daladerini (Hemiptera: Heteroptera: Coreidae) from Madagascar", but that is by Harry Brailovsky, not Clayton and Price (you can see this paper in BioStor as http://biostor.org/reference/55669). The BioStor link for the phantom paper displayed by Mendeley, http://biostor.org/reference/55761, is for a third paper "A review of ground beetle species (Coleoptera: Carabidae) of Minnesota, United States : New records and range extensions". The table below shows the original details for the paper, the details for the "canonical paper" created by Mendeley, and the details for two papers that have some of the bibliographic details in common with this non-existent paper (highlighted in bold).

Field	Original paper	Mendeley
Title	Review of the genus Saemundssonia Timmermann (Phthiraptera: Philopteridae) from the Alcidae (Aves: Charadriiformes), including a new species and new host records	A new genus and a new species of Daladerini (Hemiptera: Heteroptera: Coreidae) from Madagascar	A new genus and a new species of Daladerini (Hemiptera: Heteroptera: Coreidae) from Madagascar	A review of ground beetle species (Coleoptera: Carabidae) of Minnesota, United States : New records and range extensions
Author(s)	Roger D Price, Ricardo L Palma, Dale H Clayton	DH Clayton, RD Price	Harry Brailovsky
Volume	105	105	104	107
Pages	915-924	915-924	111-118	917-940
BioStor	57185	55761	55669	55761

As you can see it's a bit of a mess. Now, finding and merging duplicates is a hard problem (see doi:10.1145/1141753.1141817 for some background), but I'm struggling to see why these documents were considered to be duplicates.

What I'd like to see
I'm a big fan of Mendeley, so I'd like to see this problem fixed. What I'd really like to see is the following:

1. Mendeley publish a description of how their de-duplication algorithms work


2. Mendeley describe the series of steps a document goes through as they process it (if nothing else, so that users can make sense of the multiple URLs a document may get over it's lifetime in Mendeley).


3. For each canonical reference Mendeley shows the the set of documents that have been merged to create that canonical reference, and display some measure of their confidence that the match is genuine.


4. Mendeley enables users to provide feedback on a canonical document (e.g., a button by each document in the set that enables the user to say "yes this is a match" or "no, this isn't a match").

Perhaps what would be useful is if Mendeley (or the community) assemble a test collection of documents which contains duplicates, together with a set of the canonical documents this collection actually contains, and use this to evaluate alternative algorithms for finding duplicates. Let's make this a "challenge" with prizes! In many ways I'd be much more impressed by a duplication challenge than the DataTEL challenge, especially as it seems clear that Mendeley readership data is too sparse to generate useful recommendations (see Mendeley Data vs. Netflix Data).

n-gram fulltext indexing in MySQL

Continuing with my exploration of the Biodiversity Heritage Library one obstacle to linking BHL content with nomenclature databases is the lack of a consistent way to refer to the same bibliographic item (e.g., book or journal). For example, the Amphibia Species of the World (ASW) page for Gastrotheca aureomaculata gives the first reference for this name as:

Gastrotheca aureomaculata Cochran and Goin, 1970, Bull. U.S. Natl. Mus., 288: 177. Holotype: FMNH 69701, by original designation. Type locality: "in [Departamento] Huila, Colombia, at San Antonio, a small village 25 kilometers west of San Agustín, at 2,300 meters".

The journal that ASW abbreviates as "Bull. U.S. Natl. Mus." is in the BHL, which gives its title as "Bulletin - United States National Museum.". How do I link these two records? In my bioGUID OpenURL project I've been doing things like using SQL LIKE statements with periods (.) replaced by wildcards ('%') to find journal titles that match abbreviations (as well as building a database of these abbreviations). But this is error prone, and won't work for abbreviations such as "Bull. U.S. Natl. Mus." because the word "National" has been abbreviated to "Natl", which isn't a substring of "National".

After exploring various methods (including longest common subsequences, and sequence alignment algorithms) I came across a MySQL plugin for n-grams. The plugin tokenises strings into bi-grams (tokens with just two characters, see the Wikipedia page on N-grams for more information). This means that even though as words "National" and "Natl" are different, they will have some similarity due to the shared bi-grams "Na" and "at".

So, I grabbed the source for the plugin and the ICU dependency, compiled the plugin and added it to MySQL (I'm running MySQL 5.1.34 on Mac OS X 10.5.8). The plugin can be added while the MySQL server is running using this SQL command:

INSTALL PLUGIN bigram SONAME 'libftbigram.so';

Initial experiments seem promising. For the bhl_title table I created a bi-gram index:

ALTER TABLE `bhl_title` ADD FULLTEXT (`ShortTitle`) WITH PARSER bigram;

If I then take the abbreviation "Bull. U.S. Natl. Mus.", strip out the punctuation, and search for the resulting string ("Bull US Natl Mus")

SELECT TitleID, ShortTitle, MATCH(ShortTitle) AGAINST('Bull U S Natl Museum')
AS score FROM bhl_title
WHERE MATCH(ShortTitle) AGAINST('Bull U S Natl Museum') LIMIT 5;

I get this:

TitleID	ShortTitle	score
7548	Bulletin - United States National Museum.	19.4019603729248
13855	Bulletin du Muséum National d'Histoire Naturelle.	17.6493873596191
14964	Bulletin du Muséum National d'Histoire Naturelle.	17.6493873596191
5943	Bulletin du Muséum national d'histoire naturelle.	17.6493873596191
12908	Bulletin du Muséum National d'Histoire Naturelle.	17.6493873596191

The journal we want is the top hit (if only just). I'll probably have to do some post-processing to check that the top hit makes sense (e.g., is it a supersequence of the search term?) but this looks like a promising way to match abbreviated journal names and book titles to records in BHL (and other databases).