As part of the Open Citations Project, Alex Dutton recently completed a graphing plug-in for the Open Citations web site, that permits users to generate different kinds of graphs of citation networks by querying the Open Citation Corpus for a particular article, and either display the network of papers citing that article (input citations), papers cited by that article (output citations), or both.
**Executive summary ** *Introduction * To general readers of this blog, this post will appear different from normal posts. Rather than being about a particular topic, it pulls together a summary of the work undertaken over the past year within the Open Citations Project supported by the JISC, and is primarily intended to assist JISC evaluation of the project and its outputs.
The JISC Open Citations Project website at http://opencitations.net exists for several purposes: To hold introductory information about the JISC Open Citations Project. To hold contact information for the project team.
The input PubMed Central Open Access subset XML reference data, our starting corpus, were transformed into Open Citations RDF in multiple stages: The original XML was first transformed into an intermediate form using XSLT.
As previously described, the PubMed Central Open Access subset of journal articles yielded 6,529,815 independent bibliographic records of both citing and cited entities, while our use of the PubMed Entrez API provided a further 2,304,143 bibliographic records for the same cited entities. Before converting these references into RDF to create the Open Citations Corpust, we attempted to remove errors in the data.
To illustrate three kinds of problems in obtaining correct author lists for Open Citation data from articles in the PubMed Central Open Access subset (OASS), I take three examples, the first of which is the result of a publication policy, the second due to mis-handling of an authorship attribution at the time of publication, and the third exemplifing errors introduced when handling non-English personal names.
The Open Citations Project has aimed to liberate bibliographic references from biomedical research literature as Open Linked Data, using as its starting corpus the Open Access Subset (OASS) of articles within PubMed Central. The greatest problem faced during this project, naively unanticipated before we started, was the extend of incompleteness, noise and errors of various sorts within the reference information extracted from the OASS articles.
PubMed, created by the US National Library of Medicine in DATE, holds bibliographic records and abstracts for essentially all journal articles published in the biomedical sciences. It currently records almost a million new entries each year! PubMed Central (PMC), created as an extension of PubMed, is designed to hold full text articles from among the PubMed entries.
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
