Image – Getty: Nico El Nino
By Porter Anderson, Editor-in-Chief | @Porter_Anderson
Article Publication Charges Waived Through 2025
It’s been interesting to see academic publishers of journals create new titles related to artificial intelligence. One of these, on which we reported last month, is The Journal of Psychology and AI from the academic research publisher Taylor & Francis.
And today (August 6), we’re looking at the creation of three new journals from the United Kingdom’s Bristol-based IOP publishing.
The three new titles are based on a fourth, which is not new. In fact, Machine Learning: Science and Technology, was first published in 2019.
What’s new is a trio of complementary journals now being released on specific associated topics:
- Machine Learning: Engineering is ” dedicated to the application of machine learning (ML), artificial intelligence (AI) and data-driven computational methods across all areas of engineering.”
- Machine Learning: Earth is about “the application of machine learning (ML), artificial intelligence (AI) and data-driven computational methods across all areas of earth, environmental and climate sciences including efforts to ensure a sustainable future.”
- Machine Learning: Health focuses on “the application of machine learning (ML), artificial intelligence (AI) and data-driven computational methods across healthcare and the medical, biological, clinical, and health sciences.”
‘Reproducibility, Integrity and Trust’
On this page, you see the full series of four associated journals, and three of their editors-in-chief and the universities they’re associated with, all three so far in the States. (IOP has offices not only in Bristol’s Avon Street but also in Beijing, Tokyo, and Philadelphia.)
A fourth editor-in-chief, for the journal on health, has not yet been identified.
According to IOP’s media messaging, its decision to create a series of journals from the original machine-learning title has to do with a “surge of output in this research area which saw more than 280,000 articles published in 2023 and a seven-fold increase in funding since 2015.
“The appetite for open access in the field is also high,” the company writes, “with the proportion of ML/AI articles published on an open-access basis increasing from approximately 20 percent in 2015 to around 40 percent in 2022.”
The three new journals in what is now a four-title series are to open for submissions later this year. The original journal is represented by the blue icon, the new Earth-focused journal by the green icon, of course; the health-focused journal by the magenta icon; and the engineering journal by the orange icon.
“In addition to research articles and reviews,” the pre-publication text tells us, “the series will also uniquely publish dataset, benchmark, and challenge articles to meet the diverse needs of research communities working at the interface of ML, AI and the sciences.”
Tim Smith
Tim Smith is the lead on portfolio development at IOP, and he says, “It’s clear that ML and AI have the potential to be transformational in accelerating the advance of new scientific knowledge and discovery.
“Through our new machine learning series, we’re committed to creating a world-leading publishing home that represents the many areas of science where ML is already playing a critical role.
“We’re excited to introduce even more article formats supporting our open-science goals as a publisher and ensuring the reproducibility, integrity and trust of peer-reviewed research.”
Writers publishing in IOP’s three new machine-learning journals are to have free open-access publishing throughout 2025, with all article publication charges covered by IOP. As many of our readers will remember, profits generated by IOP are reinvested into the source of the name’s initials, the Institute of Physics.
More from Publishing Perspectives on scholarly and research publishing is here, more on the work of the IOP Publishing suite of society journals is here, more on artificial intelligence is here, and more on academic publishing in general is here.