Ribonucleic acid (RNA) virus and coronavirus in Google Dataset Search: their scope and epidemiological correlation

TL;DR

This study analyzes RNA virus datasets in Google Dataset Search, revealing limited reusability, increasing publication trends related to epidemics, and highlighting challenges in dataset filtering and monitoring for open science advancement.

Contribution

It provides a comprehensive evaluation of RNA virus datasets in Google Dataset Search, focusing on scope, reuse capacity, and correlation with pandemics, which is a novel analysis in this context.

Findings

Only 52% of datasets are related to scientific research.

Just 15% of datasets are reusable.

Publication of datasets has increased, especially during major epidemics.

Abstract

This paper presents an analysis of the publication of datasets collected via Google Dataset Search, specialized in families of RNA viruses, whose terminology was obtained from the National Cancer Institute (NCI) thesaurus developed by the US Department of Health and Human Services. The objective is to determine the scope and reuse capacity of the available data, determine the number of datasets and their free access, the proportion in reusable download formats, the main providers, their publication chronology, and to verify their scientific provenance. On the other hand, we also define possible relationships between the publication of datasets and the main pandemics that have occurred during the last 10 years. The results obtained highlight that only 52% of the datasets are related to scientific research, while an even smaller fraction (15%) are reusable. There is also an upward trend in the publication of datasets, especially related to the impact of the main epidemics, as clearly confirmed for the Ebola virus, Zika, SARS-CoV, H1N1, H1N5, and especially the SARS-CoV-2 coronavirus. Finally, it is observed that the search engine has not yet implemented adequate methods for filtering and monitoring the datasets. These results reveal some of the difficulties facing open science in the dataset field.