DataCite as a novel bibliometric source: Coverage, strengths and limitations. Issue 3 (August 2017)

• Record Type: Journal Article
• Authors: Robinson-Garcia, Nicolas; Mongeon, Philippe; Jeng, Wei; Costas, Rodrigo
• Is Part Of: Journal of informetrics. Volume 11:Issue 3(2017:Jul.)
• Page Start: 841
• Page End: 854
• Publication Date: 2017-08
• Subjects: Data sharing -- Data citations -- Bibliometric sources -- Open data -- Data infrastructure -- Data metrics -- DataCite; Library statistics -- Periodicals; Information science -- Statistical methods -- Periodicals; Bibliometrics -- Periodicals; Bibliothèques -- Statistiques -- Périodiques; Sciences de l'information -- Méthodes statistiques -- Périodiques; Bibliométrie -- Périodiques; 020.727
• DOI: 10.1016/j.joi.2017.07.003
• Languages: English
• ISSNs: 1751-1577

Abstract

Highlights: DataCite contains 6, 348, 284 records almost doubling the figures last reported for the Data Citation Index. 42% of the records are categorized as datasets, following by text (18%), image (14%), and collection (7%). Data-Planet is the largest data center in DataCite, providing 20% of all the records. The size and richness of DataCite data offer greater possibilities as a bibliometric source for developing open data metrics. Abstract: This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led to a pressing demand for the development of data metrics. As a very first step towards reliable data metrics, we need to better comprehend the limitations and caveats of the information provided by sources of open data. In this paper, we critically examine records downloaded from the DataCite's OAI API and elaborate a series of recommendations regarding the use of this source for bibliometric analyses of open data. We highlight issues related to metadata incompleteness, lack of standardization, and ambiguous definitions of several fields. Despite these limitations, we emphasize DataCite's value and potential to become one of the main sources for data metrics development.