King et al. survey some of the issues, but don't really tackle the big issue of how we're going to build this. If we define the "bibliography of life" somewhat narrowly as the list of all papers that have published a scientific name (or a new combination, such as moving a species from one genus to another), then this is a large, but measurable undertaking. According to ION's metrics page, these are the numbers involved (for animals and protozoa):
| Total New Names | 1,510,402 |
| Total New Genera / Subgenera | 215,242 |
| Total New Species / Subspecies | 1,192,366 |
| Total Other New Names | 102,794 |
| Total New Combinations | 241,296 |
| Total New Synonyms | 260,544 |
Even in the worse case scenario of one name per publication (clearly not the case) this is big, but not insurmountable, task.
Publications not taxa
Part of the challenge is figuring out the best way to tackle the problem. In the past, most efforts at building taxonomic bibliographies have focussed on specific taxa, which is natural — the bibliographies are being built by taxonomists and they specialise in particular groups. But I'd argue that this is not the most efficient way to tackle the problem. Because the taxonomic literature is so widely dispersed, after the obvious "low hanging fruit" have been collected, considerable effort must be spent tracking down the harder to find citations. There are few economies of scale in this approach. In contrast, if we focus on publications at, say, the level of journal, then we can build a bibliography much more quickly. Once we've found the source, say, for one article, often we could use that information to harvest many articles from the same source (e.g., write scripts to harvest from a digital repository such as a DSpace server, or a digital library such as Gallica). But if we are focussed on a particular taxon, we will ignore the other articles in that journal ("what do I care about fish, I like turtles").
Put another way, if we imagine a taxa × publication matrix, then we can either go after rows (i.e., a bibliography for a specific taxonomic group), or columns (a list of articles in a specific journal). The article-based approach will be faster, albeit at the cost of finding articles that aren't necessarily relevant to taxonomy. This is why I'm spending what feels like far too much time harvesting article lists and uploading these to Mendeley. It is also one reason BHL has been so successful. They've simply gone after scanning the literature wholesale, rather than focussing on particular taxonomic groups.
Crowd sourcing and WikispeciesCrowd sourcing often strikes me as a euphemism for "we can't be bothered doing the tedious stuff, lets get the public to do it for us (plus it will look like we're engaged with the public)." I'm not denying can work, but I suspect it's not a magic bullet. Perhaps the best crowd sourcing is not to try and bring the crowd to a project, but go where the crowd has already gathered. In this case, an obvious crowd is the Wikispecies community. Working with the ION database for my Sherborn presentation, it's clear that the quality of bibliographic data in ION is variable, and rather poor for older references. In contrast, the reference lists on Wikispecies can be very good (e.g., the bibliography for George Boulenger). There are some issues with Wikispecies, notably the lack of a decent bibliographic template (unlike Wikipedia) so parsing references can be *cough* interesting, but there is scope here to use it to improve other databases. Citation matching can be a challenge, but in this case we have citations indexed by taxonomic name (in both ION and Wikispecies), which greatly reduces the scope of possible matches.
Summary
I think building the "bibliography of life" needs a combination of aggressive data gathering, and avoiding building additional tools unless absolutely needed. There are great tools and communities that can already be leveraged (e.g., Mendeley, Wikispecies), let's make use of them.
Following on from my 
