About the Journal
A peer-reviewed, open-access journal of artificial intelligence, machine learning and data science.
Double-anonymous review. No article processing charges. Published under the Creative Commons Attribution 4.0 licence.
Aims and scope
JIDLS publishes original research, short communications and reviews on methods and systems that learn from data: machine learning, deep learning, natural language processing, computer vision, uncertainty and calibration, fairness and interpretability, and learning systems in practice. Applied work in health, science and engineering is welcome where it reports a reproducible evaluation.
Article types
- Research articles, up to 8,000 words.
- Short communications, up to 3,000 words, including replications and negative results.
- Review articles with a critical assessment of the evidence.
Peer review and publication
Research articles are reviewed double-anonymously by at least two reviewers. Accepted articles are published online on acceptance under the CC BY 4.0 licence. There are no submission or publication fees.
Call for papers, Volume 1 (2026). Submissions are open for the inaugural volume. See the author guidelines.
