Scientific data citation: Scoping review

Abstract

Objective: This paper investigates the meaning assigned to data citation in order to follow the evolution of studies related to data citation, it tries to answer: 1) What are the motivations of researchers to cite scientific data?; 2) What are the data citation practices presented by the areas covered by this study?; 3) What are the metric analysis for data citation? Methods: It is a qualitative and descriptive research, being a scoping review of literature, by searching the Emerald, LISA, LIST, Scopus and Web of Science databases. Results: The studies investigated the correlation of citations increment to traditional publications by citing the data that supported them, many studies confirmed the correlation, others did not, and a common cause hypothesis arose: Research quality associated with more resources. As for practices, the community is aware that current citations to data are not standardized, and there is a tendency to adopt a citation standard that meets the demands of different types of data. This lack of standard hinders the metric analysis of citation to scientific data that still needs to be explored in research, given that there is a repetition in using the same techniques of traditional citation for this new source of information. Conclusions: Promoting the progress of science is the main advantage in making data available, but there are credit and technical difficulties that need to be tackled together by researchers, institutions, funding agencies, data repositories, and publishing editorial teams.