Hot on the heels of Geoffrey Nunberg's essay about the train wreck that is Google books metadata (see my earlier post) comes Google Scholar’s Ghost Authors, Lost Authors, and Other Problems by Péter Jacsó. It's a fairly scathing look at some of the problems with the quality of Google Scholar's metadata.Now, Google Scholar isn't perfect, but it's come to play a key role in a variety of bibliographic tools, such as Mendeley, and Papers.

I've been playing recently with the Biodiversity Heritage Library (BHL), and am starting to get a sense for the complexities (and limitations) of the metadata BHL stores about publications.

Just a quick not to make a link between David Shorthouse's post about taxonomic consensus and distributed version control (Taxonomic Consensus as Software Creation), and Galen Charlton's article in The Code4Lib Journal (Distributed Version Control and Library Metadata). Some interesting food for thought here. Both mention Git.

Time for a rant. I spend a lot of time fussing with records from sources such as GenBank and DiGIR providers, trying to extract strings that might be identifiers, with a view to linking sequences to specimens (and thus to localities), sequences to publications, publications to GUIDs, etc.

Continuing on this theme of embedded metadata, this is one reason why DNA barcodingis so appealing. A DNA barcode is rather like embedded metadata -- once we extract it we can look up the sequence and determine the organism's identity (or, at least whether we've seen it before). It's very like identifying a CD based on a hash computed from the track lengths.

Following on from the previous post, as Howison and Goodrum note, Adobe provides XMP as a way to store metadata in files, such as PDFs. XMP supports RDF and namespaces, which means widely used bibliographic standards such as Dublin Core and PRISM can be embedded in a PDF, so the article doesn't become separated from its metadata.