@misc{10481/77750,
year = {2022},
month = {10},
url = {https://hdl.handle.net/10481/77750},
abstract = {We model the growth of scientific literature related to COVID-19 and forecast the expected
growth from 1 June 2021. Considering the significant scientific and financial efforts made
by the research community to find solutions to end the COVID-19 pandemic, an unprecedented
volume of scientific outputs is being produced. This questions the capacity of scientists,
politicians and citizens to maintain infrastructure, digest content and take scientifically
informed decisions. A crucial aspect is to make predictions to prepare for such a large
corpus of scientific literature. Here we base our predictions on the Autoregressive Integrated
Moving Average (ARIMA) and exponential smoothing models using the Dimensions
database. This source has the particularity of including in the metadata information
on the date in which papers were indexed. We present global predictions, plus predictions
in three specific settings: by type of access (Open Access), by domain-specific repository
(SSRN and MedRxiv) and by several research fields. We conclude by discussing our
findings.},
organization = {Ramon y Cajal grant from the Spanish Ministry of Science and Innovation	RYC2019-027886-I},
organization = {University of Granada},
organization = {TU Delft COVID-19 Response Fund},
publisher = {Springer},
keywords = {COVID-19},
keywords = {Scientific publication},
keywords = {Growth of science},
keywords = {Dimensions},
keywords = {Open access},
title = {COVID‑19 and the scientific publishing system: growth, open access and scientific fields},
doi = {10.1007/s11192-022-04536-x},
author = {Nane, Gabriela F. and Robinson García, Nicolás and Torres Salinas, Daniel},
}