I've put the my Elsevier Challenge demo online. I'm still loading data into it, so it will grow over the next day or so. There's also the small matter of writing a paper on what's under the hood of the demo. Feel free to leave comments on the demo home page. For some example of what the project does, take a look at Mitochondrial paraphyly in a polymorphic poison frog species (Dendrobatidae;

One of the things I've struggled with most in putting together a web site for the challenge is how to summarise that taxonomic content of a study. Initially I was playing with showing a subtree of the NCBI taxonomy, highlighting the taxa in the study. But this assumes the user is familiar with the scientific names of most of life. I really wanted something that tells you "at a glance" what the study is about.

Elsevier have released this video about the challenge, featuring a few of the contestants. I couldn't get my act together in time to send anything useful, and having seen the 16 gigabytes song (full version here), I'm glad I didn't -- there's just no way I could compete with Michael Greenacre and Trevor Hastie.

One of the judges for the Elsevier Article 2.0 Contest is Andrew Perry, whose blog has some posts on Noel O'Boyle's OpenRef idea (see DOI or DOH? Proposal for a RESTful unique identifier for papers). Andrew discusses some implementations he has come up with, and compares OpenRef with OpenURL. This prompted me to add OpenRef-style identifiers to bioGUID's OpenURL resolver.

Chris Freeland's tweet alterted me to the Elsevier Article 2.0 Contest: Elsevier are clearly looking for ideas (they also have their Grand Challenge), and there's been some interesting commentary on the Article 2.0 contest.

Watch CBS Videos Online CBS News Sunday Morning Segment on the EOL. All fun stuff (Paddy skewering the interviewer who fails to recognise an echidna), but still long on promises and short on actual product.

One problem with my cunning plan to use Mediawiki REDIRECTs to handle DOIs is that some DOIs, such as those that BioOne serves based on SICIs contain square brackets, [ ], which conflicts with wiki syntax.

Bibliographic coupling is a term coined by Kessler (doi:10.1002/asi.5090140103) in 1963 as a measure of similarity between documents. If two documents, A and B, cite a third, C, then A and B are coupled. I'm interested in extending this to data, such as DNA sequences and specimens. In part this is because within the challenge dataset I'm finding cases where authors cite data, but not the paper publishing the data.

Duncan Hull alerted me to his paper "Defrosting the Digital Library: Bibliographic Tools for the Next Generation Web" ( PloS Computational Biology , doi:10.1371/journal.pcbi.1000204). Here's the abstract: It's an interesting read, and it also cites my bioGUID project.

Following on from adding specimens to my OpenURL resolver, I've added support for GenBank records. Either an OpenURL request such as http://bioguid.info/openurl?id=genbank:DQ502033, or the short URL http://bioguid.info/genbank/DQ502033 will resolve the GenBank record for accession number DQ502033.

The A Shared Culture video from the Creative Commons web site.