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”.

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.

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

CiTO v2.0 contains just two main object properties, cito:cites and its inverse cito:isCitedBy , each of which as thirty-two sub-properties. Intentionally, these properties are not constrained as to domain or range, thereby maximising their applicability in a wide range of citation contexts.

In his recent blog post entitled How to use Citation Typing Ontology (CiTO) in your blog posts , Martin Fenner describes a plug-in for WordPress he has created that makes it easy to add citation typing into your blog post, using a sub-set of the CiTO (Citation Typing Ontology) relationships presented in a convenient drop-down menu.

Jodi Schneider of DERI has posted on her blog at http://jodischneider.com/blog/2010/10/18/cito-in-the-wild/ a most helpful description of how to employ CiTO properties characterizing bibliographic citations as tags for references in CiteULike. Thanks, Jodi!