Raj Kumar Bhardwaj, Mohammad Nazim and Manoj Kumar Verma
The present study examines the features and services of four research data repositories (RDRs): Dataverse, Dryad, Zenodo and Figshare. The study explores whether these RDRs adhere…
Abstract
Purpose
The present study examines the features and services of four research data repositories (RDRs): Dataverse, Dryad, Zenodo and Figshare. The study explores whether these RDRs adhere to the FAIR principles and suggests the features and services that need to be added to enhance their functionality.
Design/methodology/approach
An online survey was conducted to identify the features of four popular RDRs. The study evaluates the features of four popular RDRs using the specially designed checklist method based on FAIR principles. The checklist is based on 11 construct progressions used to evaluate the features and services of four popular RDRs. The final checklist contains 11 constructs with 199 check spots.
Findings
Figshare has attained the highest features for findability, accessibility, interoperability and reusability. It is identified that Figshare, with 116 (58.3%) scored the highest points and ranked no 1. It has also been found that Figshare recorded the highest features in 6 constructs out of the 11. Dataverse, with 90 (45.2%) features, ranked 2nd; Zenodo, with 86 (43.2%), ranked 3rd. The lowest features are found in Dryad, with 85 (42.7%). Furthermore, the study found that all four popular RDRs have poor features relating to “research data access metrics” features 23.3%, “output, data license and other advanced features” 22.6%. The very less features recorded in the category “services in RDRs” are 15.9%. Therefore, the features of these three constructs framed under FAIR need to be upgraded to improve the functionalities of the four popular RDRs.
Practical implications
The findings of the study are useful for researchers in choosing the appropriate RDR for accessing and sharing data and can be used by data scientists, librarians and policymakers in starting the research data management services in academic and research institutions. Furthermore, the study can also help impart research data literacy instructions to researchers and faculty members.
Originality/value
This study has prepared a special checklist based on FAIR principles to evaluate the features and services of RDRs. No prior study has been conducted to explore the features of popular RDRs and their compliance with FAIR principles based on the checklist method.