Data Publications Correlate with Citation Impact

Abstract

Neuroscience and molecular biology have been generating large datasets over the past years that are reshaping how research is being conducted. In their wake, open data sharing has been singled out as a major challenge for the future of research. We conducted a comparative study of citations of data publications in both fields, showing that the average publication tagged with a data-related term by the NCBI MeSH (Medical Subject Headings) curators achieves a significantly larger citation impact than the average in either field. We introduce a new metric, the data article citation index (DAC-index), to identify the most prolific authors among those data-related publications. The study is fully reproducible from an executable Rmd (R Markdown) script together with all the citation datasets. We hope these results can encourage authors to more openly publish their data.

Keywords: DAC-index; citations; data article citation index; data publications; data sharing; open data.

Figure 1

Comparative study of empirical data (red) and random article (blue) citation distributions for neuroscience (top, A–C) and molecular biology (bottom, D–F). Left (A,D): Histogram of the number of data articles published per year. Middle (B,E): Cumulative distribution function (CDF) over the first few citation counts C (x-axis), showing the observed probability for the median citation value of average articles (C = 6 and C = 11, respectively). Right (C,F): Log-log plots of the complementary (1 - CDF) visualizing the growing gap between the data and random citation distributions in the heavy tails. The small horizontal black line marks the observed citation count difference for articles in the top decile (P = 0.1; i.e., the 10% most cited articles).