Premium
Analyzing data citation practices using the data citation index
Author(s) -
RobinsonGarcía Nicolas,
JiménezContreras Evaristo,
TorresSalinas Daniel
Publication year - 2016
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23529
Subject(s) - citation , computer science , data science , citation index , citation analysis , information retrieval , library science
We present an analysis of data citation practices based on the Data Citation Index (DCI) ( T homson R euters). This database launched in 2012 links data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: Although in the areas of science and engineering & technology data sets were the most cited, in the social sciences and arts & humanities data studies play a greater role. A total of 88.1% of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data—a role that would enhance their value as a means of following the research process from data collection to publication.