Quick note that Morgan Jackson (@BioInFocus) has written nice blog post Citations, Social Media & Science inspired by the fact that the following paper:Kwong, S., Srivathsan, A., & Meier, R. (2012). An update on DNA barcoding: low species coverage and numerous unidentified sequences. Cladistics, no–no. doi:10.1111/j.1096-0031.2012.00408.xcites my "Dark taxa" in the body of the text but not in the list of literature cited.

I'm back from Copenhagen and GBIC2012.

For a current project I'm currently working I show organism distributions using data from GBIF, and I display that data on a map that uses the equirectangular projection.

Next week I'm in Copenhagen for GBIC, the Global Biodiversity Informatics Conference. The goal of the conference is to:The collaboration referred to is the agreement to mobilise data and informatics capability to met the Aichi Biodiversity Targets.I confess I have mixed feelings about the upcoming meeting. There will be something like 100 people attending the conference, with backgrounds ranging from pure science to intergovernmental policy.

In any discussion of data gathering or data cleaning the term "crowdsourcing" inevitably comes up. A example where this approach has been successful is the Encyclopedia of Life's Flickr pool, where Flickr users upload images that are harvested by EOL.Given that many Flickr photos are taken with cameras that have built-in GPS (such as the iPhone, the most common camera on Flickr) we could potentially use the Flickr photos not only as a source of

Just for future reference:

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.

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.

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.

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.

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