Subject analysis of LIS data archived in a Figshare using co-occurrence analysis

Abstract

Purpose

Based on the data from Figshare repositories, the purpose of this paper is to analyze which research data are actively produced and shared in the interdisciplinary field of library and information science (LIS).

Design/methodology/approach

Co-occurrence analysis was performed on keywords assigned to research data in the field of LIS, which were archived in the Figshare repository. By analyzing the keyword network using the pathfinder algorithm, the study identifies key areas where data production is actively conducted in LIS, and examines how these results differ from the conventional intellectual structure of LIS based on co-citation or bibliographic coupling analysis.

Findings

Four major domains – Open Access, Scholarly Communication, Data Science and Informatics – and 15 sub-domains were created. The keywords with the highest global influence appeared as follows, in descending order: “open access,” “scholarly communication” and “altmetrics.”

Originality/value

This is the first study to understand the key areas that actively produce and utilize data in the LIS field.

Citation

Cho, J. (2019), "Subject analysis of LIS data archived in a Figshare using co-occurrence analysis", Online Information Review, Vol. 43 No. 2, pp. 256-264. https://doi.org/10.1108/OIR-12-2017-0369