New Article (Preprint): “Datacite as a Novel Bibliometric Source: Coverage, Strengths and Limitations”

The following article was recently shared on arXiv and has been accepted for publication in the Journal of Infometrics. 
Title
Datacite as a Novel Bibliometric Source: Coverage, Strengths and Limitations
Authors
Nicolas Robinson-Garcia
Universitat Politècnica de València
Philippe Mongeon
Université de Montréal
Wei Jeng
National Taiwan University
Rodrigo Costas
Leiden University
Stellenbosch Universitu
Source
via arXiv
July 19, 2017
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.

Direct to Full Text Article (21 pages; PDF)

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