One of the biggest challenges faced by modern scientists is information overload. The life sciences are probably the area most affected by it, with almost a million new entries being added to PubMed each year. While on-line publishing and bibliographic search engines have made the problem of finding individual research articles considerably easier, the present scholarly citation system inadequately exposes the knowledge networks that exist within the scientific literature, linking papers, authors and research projects. Much of the problem stems from the lack of freely available citation data in machine-readable form.
In this Open Access age, it is a scandal that reference lists from journal articles, the core elements of the academic data cycle, are not freely available for use by scholars. Current citation services are largely restricted to a small number of commercial companies whose valuable products are still insufficiently developed to satisfy all the needs of the academic community.
Google Scholar offers navigation through the citation network, but only in one direction – backwards. Thomson Reuter guards citation data in ISI Citation Index and Web of Knowledge as commercial assets, as does Elsevier for citation data in Scopus, with limited subscription-access search and display capabilities, and no methods for extracting citation data in bulk. Furthermore, they do not characterise the nature of citations between publications.
The value of citation data to the research community has grown as research evaluation has increased in importance. Citation metrics are increasingly used by institutions to establish their research quality, and by funding agencies to determine the effectiveness of their grant spending.
Citation data now need to be recognized as a part of the Commons – those works that are freely and legally available for sharing and reuse – extending the Science Commons / Open Knowledge Foundation philosophy to the world of scientific citation.
If machine-readable citation data for all scholarly publications were to be published freely on the Web, the construction and interrogation of citation networks would become trivially simple, with enormous advantages to scholarship. Thanks to CiteSeerX, citation data in computer science have been freely available for several years,
Similar access is now coming for other fields of scholarship, particularly for the biological sciences through CiteXplore. However, in none of these cases are the citation data available as Linked Open Data, and there are no convenient free tools, accessible to working research biologists, that permit them to visualize and navigate the literature by means of its citation network, or that permit knowledge analysts to pose generic questions over the whole corpus, such as determining whether those who publish in Open Access journals are more prone to cite other Open Access articles, in comparison with those who do not.
This project will produce citation information as Open, Linked Data which will address the short-comings of the current situation, aiming to provide researchers with the tools to explore the citation network.
OpenCitations blog 