An open journal that studies the economy through data
Scientific e-journal · since 2026 · open access · a DOI for every article
About the journal Read more →
IQTIDATA is a peer-reviewed, open-access scientific e-journal publishing research at the intersection of economics and data science. Founded in 2026, the journal specialises in work that studies economic processes with modern data-analysis methods — econometrics, machine learning, big data and artificial intelligence.
The journal covers econometric and statistical modelling, machine learning and AI in economics, big data and economic analytics, the digital economy and platforms, financial technology, macro- and microeconomic analysis, data visualisation and data-driven economic policy.
All articles undergo double-blind peer review, are published under the Creative Commons CC BY 4.0 licence and receive a permanent DOI through Zenodo. The journal follows the principle of reproducible research: empirical articles are encouraged to be published with their data and code. Articles are accepted in Uzbek, Russian and English.
Why publish in IQTIDATA?
Fast turnaround
Electronic publication: an accepted article goes into the next issue — no waiting for print.
A DOI for every article
A permanent identifier registered through Zenodo, harvested automatically by OpenAIRE.
Free e-certificate
A publication certificate for every author — at no extra charge.
Open access
All articles are freely available worldwide under CC BY 4.0.
Double-blind peer review
Impartial assessment by independent reviewers.
Reproducible research
Published with data and code: every empirical result can be recomputed and verified.
Publication process
Author guidelines Read more →
Types of paper
- Research article
- Full results of original empirical or theoretical research (with data and code)
- Review article
- A critical review systematically assessing the literature and methods
- Data & code paper
- Description of a new dataset, software package or replication result
Article structure (IMRAD)
- JEL and UDC
- JEL classification codes and the UDC code are given at the head of the article
- Authors
- full name, degree, affiliation and e-mail — in three languages
- Title
- in Uzbek, Russian and English
- Abstract and keywords
- in three languages: aim, main results and conclusions
- Introduction
- relevance of the topic, aim and objectives
- Data and methodology
- data sources, sample, models and software; a link to code and data
- Analysis and results
- results substantiated with tables and figures
- Conclusions and proposals
- main conclusions and practical proposals
- References
- numbered list; in-text citations as [1], [2]
Technical requirements
- Language
- Uzbek · Russian · English
- File
- Microsoft Word (.docx) or LaTeX (.tex + PDF)
- Text
- A4, a single typeface and spacing; italics for emphasis
- Figures, tables and code
- in place in the text, editable; code and data in an open repository (GitHub, Zenodo, OSF)
- Submission
- previously unpublished; via the site (the “Submit” button) or by e-mail to the editorial office