In the last two weeks I've been busy with making Version 0.2 of Citation.js. Here I'll explain some of the changes and the reasoning behind them. In the past months I've updated Citation.js several times, and the changes included a Node.js program for the commandline and better Wikidata input parsing. While I was working with the "old" code, I noticed some annoying issues in it. One of the biggest things was the internal data format.
Last week I made Citation.js usable for the command line, with Node.js. First of all, the main file determines if it is being run with Node.js or in the browser, and switches to Browser or Nodejs mode based on that.
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.
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.