Effect of impact factor and discipline on journal data sharing policies

Abstract

Data sharing is crucial to the advancement of science because it facilitates collaboration, transparency, reproducibility, criticism, and re-analysis. Publishers are well-positioned to promote sharing of research data by implementing data sharing policies. While there is an increasing trend toward requiring data sharing, not all journals mandate that data be shared at the time of publication. In this study, we extended previous work to analyze the data sharing policies of 447 journals across several scientific disciplines, including biology, clinical sciences, mathematics, physics, and social sciences. Our results showed that only a small percentage of journals require data sharing as a condition of publication, and that this varies across disciplines and Impact Factors. Both Impact Factor and discipline are associated the presence of a data sharing policy. Our results suggest that journals with higher Impact Factors are more likely to have data sharing policies; use shared data in peer review; require deposit of specific data types into publicly available data banks; and refer to reproducibility as a rationale for sharing data. Biological science journals are more likely than social science and mathematics journals to require data sharing.

Journal research data sharing policies: a study of highly-cited journals in neuroscience, physics, and operations research

“…As can be seen from Table 1 research on the topic has been active during the last 10 years. Journal research data policies have previously been studied in the fields of environmental sciences (Weber et al 2010), political science (Gherghina and Katsanidou 2013), genetics (Moles 2014), social sciences (Herndon and O'Reilly 2016;Crosas et al 2018), biomedical sciences (Vasilevsky et al 2017) and through multidisciplinary approaches (Piwowar and Chapman 2008;Sturges et al 2015;Blahous et al 2016;Naughton and Kernohan 2016;Castro et al 2017;Resnik et al 2019). Within the findings of recent multidisciplinary studies on journal research data policies, circa 50-65% of journals had a research data policy and 20-30% of these policies were either classified as strong policies or mandated data sharing into a public repository (Sturges et al 2015;Blahous et al 2016;Naughton and Kernohan 2016).…”

“…Within the findings of recent multidisciplinary studies on journal research data policies, circa 50-65% of journals had a research data policy and 20-30% of these policies were either classified as strong policies or mandated data sharing into a public repository (Sturges et al 2015;Blahous et al 2016;Naughton and Kernohan 2016). Furthermore, studies suggest that journals with high Impact Factors also have the strongest data sharing policies (Vasilevsky et al 2017;Resnik et al 2019).…”

“…Prior studies have presented various classification frameworks for evaluation of journal' research data policies (Piwowar and Chapman 2008;Moles 2014;Sturges et al 2015;Herndon and O'Reilly 2016;Blahous et al 2016;Crosas et al 2018;Resnik et al 2019). As an overall trend, the classification frameworks of research data policies have become more detailed and intricate over time.…”

“…Stodden, Guo and Ma 2013;Moles 2014;Vasilevsky et al 2017;Resnik et al 2019). In most recent studies, specific data types, such as life science data, are acknowledged as factors affecting journal data policies and included as variables in classification schemes (Vasilevsky et al 2017;Resnik et al 2019). Journal research data policies related to fields of neuroscience, physics and operations research have previously been examined as follows.…”

“…The connection between a research article and its underlying data is strong and direct for authors involved in the preparation process of article manuscripts, but the immediate link can weaken or become completely absent as the article gets published without any data to support the reported findings being made available for readers to access. Journal policies for research data sharing have been developing actively since over two decades ago (Piwowar and Chapman 2008), but only more recently has uptake among journals gained wider support, with progress so far having been observed to be uneven across disciplines (Resnik et al 2019). Journal data sharing policies becoming more common and detailed can be perceived as part of the larger push towards open science driven by science policy as well as individual researchers, where open data sharing is a central element for making research more transparent, reproducible, and increasing its potential impact (McKiernan et al 2016).…”