I'm doing some work with Nicole Kearney (@nicolekearney) at the Melbourne Museum on the general theme of "linking all the things". It's the end of the first full week we've had, so here's a quick update of what we've been up to. Brainstorming The things we want to do are being captured as a project on GitHub. This is where we come up with ideas, comment on then, then try to figure out which ones can be done.

If we view biodiversity data as part of the "biodiversity knowledge graph" then specimens are a fairly central feature of that graph. I'm looking at ways to link specimens to sequences, taxa, publications, etc., and doing this across multiple data providers. Here are some rough notes on trying to model this in a simple way.

Following on from my previous post bemoaning the lack of links between biodiversity data sets, it's worth looking at different ways we can build these links. Specifically, data can be tightly or loosely coupled. Tight coupling Tight coupling uses identifiers. A good example is bibliographic citation, where we state that one reference cites another by linking DOIs.

The Integrated Digitized Biocollections (iDigBio) project aims to advance digitising US biodiversity collections. They recently published a GUID Guide for Data Providers. In the PDF document I read this: My heart sank.

If we are ever going to link biodiversity data together we need to have some way of ensuring persistent links between digital records. This isn't going to happen unless people take persistent identifiers seriously. I've been trying to link specimen codes in publications to GBIF, with some success, so imagine my horror when it started to fall apart.

Playing with some sequence data I found numerous Plasmodium sequences from the following paper: These sequences (e.g., U43145) give the host as Thamnomys rutilans . You'd think it would be fairly easy to learn more about this animal, given that it hosts a relative of the cause of malaria in humans, and indeed there are a number of biomedical papers that come up in Google, e.g.: Google also tells me that Thamnomys

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.

When I think of the Biodiversity Heritage Library (BHL) or GBIF I tend to think of taxonomy and biodiversity. Folk wisdom has it that BHL is full of old books, mostly pre-1923. Great for finding old taxonomic names, or nice artwork, but not exactly "modern" biology. GBIF is mainly about displaying organism distributions based on museum specimens, the primary data of taxonomic research.

Following on from exploring links between GBIF and GenBank here I'm going to look at links between GBIF and the primary literature, in this case articles scanned by the Biodiversity Heritage Library (BHL). The OCR text in BHL can be mined for a variety of entities. BHL itself has used uBio's tools to identity taxonomic names in the OCR text, and in my BioStor project I've extracted article-level metadata and geographic co-ordinates.

Browsing EOL I stumbled upon the recently described fish Protoanguilla palau , shown below in an image by rairaiken2011: Two things struck me, the first is that the EOL page for this fish gives absolutely no clue as to where you would to find out more about this fish (apart from an unclickable link to the Wikipedia page http://en.wikipedia.org/wiki/Protoanguilla - seriously, a link that isn't clickable?), despite the fact this fish