Journal Article: “What Drives and Inhibits Researchers to Share and Use Open Research Data? A Systematic Literature Review to Analyze Factors Influencing Open Research Data Adoption”

The following systematic literature review was recently published by PLOS One.

Title

What Drives and Inhibits Researchers to Share and Use Open Research Data? A Systematic Literature Review to Analyze Factors Influencing Open Research Data Adoption

Authors

Anneke Zuiderwijk
Delft University of Technology

Rhythima Shinde
ETH Zürich

Wei Jeng
National Taiwan University

Source

PLoS ONE 15(9): e0239283
DOI: 10.1371/journal.pone.0239283

Abstract

Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers’ drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking. This study’s purpose is to systematically review the literature on individual researchers’ drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: ‘the researcher’s background’, ‘requirements and formal obligations’, ‘personal drivers and intrinsic motivations’, ‘facilitating conditions’, ‘trust’, ‘expected performance’, ‘social influence and affiliation’, ‘effort’, ‘the researcher’s experience and skills’, ‘legislation and regulation’, and ‘data characteristics.’ This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies. With such discussions, an overview of identified categories and factors can be further applied to examine both researchers’ drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What’s more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.

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