Wikipedia Citations: A comprehensive dataset of citations with identifiers extracted from English Wikipedia

Authors : Harshdeep Singh, Robert West, Giovanni Colavizza

Wikipedia’s contents are based on reliable and published sources. To this date, little is known about what sources Wikipedia relies on, in part because extracting citations and identifying cited sources is challenging. To close this gap, we release Wikipedia Citations, a comprehensive dataset of citations extracted from Wikipedia.

A total of 29.3M citations were extracted from 6.1M English Wikipedia articles as of May 2020, and classified as being to books, journal articles or Web contents. We were thus able to extract 4.0M citations to scholarly publications with known identifiers — including DOI, PMC, PMID, and ISBN — and further labeled an extra 261K citations with DOIs from Crossref.

As a result, we find that 6.7% of Wikipedia articles cite at least one journal article with an associated DOI. Scientific articles cited from Wikipedia correspond to 3.5% of all articles with a DOI currently indexed in the Web of Science. We release all our code to allow the community to extend upon our work and update the dataset in the future.


The citation advantage of linking publications to research data

Authors : Giovanni Colavizza, Iain Hrynaszkiewicz, Isla Staden, Kirstie Whitaker, Barbara McGillivray

Efforts to make research results open and reproducible are increasingly reflected by journal policies encouraging or mandating authors to provide data availability statements.

As a consequence of this, there has been a strong uptake of data availability statements in recent literature. Nevertheless, it is still unclear what proportion of these statements actually contain well-formed links to data, for example via a URL or permanent identifier, and if there is an added value in providing them.

We consider 531,889 journal articles published by PLOS and BMC which are part of the PubMed Open Access collection, categorize their data availability statements according to their content and analyze the citation advantage of different statement categories via regression.

We find that, following mandated publisher policies, data availability statements have become common by now, yet statements containing a link to a repository are still just a fraction of the total.

We also find that articles with these statements, in particular, can have up to 25.36% higher citation impact on average: an encouraging result for all publishers and authors who make the effort of sharing their data. All our data and code are made available in order to reproduce and extend our results.