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.

Just noticed that BioStor now has just over 70,000 articles extracted from the Biodiversity Heritage Library. This number is a little "soft" as there are some duplicates in the database that I need to clean out, but it's a nice sounding number. Each article has full text available, and in most cases reasonably complete metadata.

Some quick notes on possibilities for text-mining BHL (in rough order of priority). Any text-mining would have to be robust to OCR errors. I've created a group of OCR-related papers on Mendeley: Skip to content Welcome Enter your email to continue with Mendeley Email Continue Sign in via your organization About Elsevier Terms and conditions Privacy policy Help We use cookies to help provide and enhance our service.

Anyone who works with taxonomic databases is aware of the fact that they have errors. Some taxonomic databases are restricted in scope to a particular taxon in which one or more people have expertise, these then get aggregated into larger databases, which may in turn be aggregated by databases whose scope is global. One consequence of this is that errors in one database can be propagated through many other databases.

Just some random thoughts on creating searchable PDFs for article extracted from BHL.

In Arthur C. Clarke's short story The Nine Billion Names of God Tibetan monks hire two programmers to help them generate all the the possible names of God. The monks believe that the purpose of the Universe is to generate those names, once that goal is achieved the Universe will end.

As part of a project to build a tool to navigate through taxonomic names and classifications I've become interested in quick ways to compare classifications. For example, EOL has multiple classifications for the same taxon, and I'd like to quickly discover what the similarities and differences are.

One visualisation method I keep coming back too is the treemap. Each time I experiment with them I learn a little bit more, but I usually end up abandoning them (with the exception of using quantum treemaps to display bibliographic data). But they keep calling me back.

While exploring ways to visually compare classifications I came across the Australian snake name Demansia atra , and ended up reading a series of papers in the Bulletin of Zoological Nomenclature discussing the status of the name (more fun than it sounds, trust me). For example, Smith and Wallach Case 2920.

In response to Rutger Vos's question I've started to add GBIF taxon ids to the iPhylo Linkout website. If you've not come across iPhylo Linkout, it's a Semantic Mediawiki-based site were I maintain links between the NCBI taxonomy and other resources, such as Wikipedia and the BBC Nature Wildlife finder. For more background see Page, R. D. M. (2011). Linking NCBI to Wikipedia: a wiki-based approach. PLoS Currents, 3, RRN1228.