What a year it has been!  Four key meetings were held during 2011, bringing together academics, computer scientists and scholarly publishers to discuss the future of scholarly communication.

Is Data Publication the Right Metaphor? is an essay by Mark Parsons and Peter Fox to be published in the Data Science Journal, for which a preprint has been provided for open pre-publication community peer review at http://mp-datamatters.blogspot.com/2011/12/seeking-open-review-of-provocative-data.html.

Many people will be familiar with Tim Berners-Lee’s five stars of linked data, categorising the publication of data on the web in levels of increasing usefulness.

In biology, the fields of macromolecular structural biology and sequence bioinformatics have, since the 1970s, had established international databases for the deposition of data, and journal policies mandating such deposition prior to acceptance for publication of manuscripts describing the data.  Similar good practices have developed more recently in other disciplines, notably astronomy.

In the previous post, I outlined reasons why researchers don’t publish data, presented as evidence to the Royal Society’s Policy Study “Science as a Public Enterprise” Call for Evidence.

Evidence submitted by David Shotton in response to the Royal Society’s Policy Study “Science as a Public Enterprise” Call for Evidence, addressing the following two topics raised by that call: Getting Researcher buy-in. How do we get researchers to be more willing to share data? What is there to be learned from disciplines such as genomics which have norms which favour wide sharing of data?

Alistair Miles, of SKOS fame, who formerly worked in our research group, spent yesterday afternoon catching up with us, and has written a nice blog post on the MalariaGEN Informatics Blog describing our current activities, including our work on the Open Citations Corpus, and how they might intersect with the data management activities of the MalariaGEN, the Malaria Genome Epidemiology Network for which he now works.

Reis et al . (2008) [1] cites an earlier paper from Albert Ko’s research group, Ko et al . (1999) [2]. In conventional parlance, as the following diagram shows, the word “reference” can mean either what is found in the text, what is found in the reference list, the act of citation, or the object of the citation itself, as in the sentence “All the references you will need to prepare for the journal club are on Kevin’s desk”.

In a recent blog post, Heather Piwowar, in discussing the advantages of citing datasets in the reference list of the article, said “No journals have standardized on this approach so far”. However, Pensoft Journals, a publisher that specializes in publishing biodiversity and biological systematics papers, and that has taken the lead in promoting the publication of datasets with DOIs, has exactly such a policy.

As an approach towards developing best practice for data citation, I recently wrote a Data Citation Best Practice Discussion Document that is available on Google Docs, and that I have now slightly revised to Version 2 [1]. In that document, I first compared what is recommended by DataCite [2] and by Altman and King [3] with what currently practised by the Dryad Data Repository and what presently occurs ‘in the wild’ in a