Data-Driven Research Across Disciplines: Methods, Applications and Emerging Challenges

Dear Colleagues,

The collection, processing, and analysis of data are increasingly important in today’s world. Whether in engineering, finance, computer science, or the natural sciences, the importance of data is clear. Furthermore, the current revolution in Artificial Intelligence (AI) is not only founded on data; it also facilitates research involving large amounts of data.

This Special Issue explores the transformative impact of data-driven methodologies across the mathematical, physical, and natural sciences while also embracing technological innovations—from machine learning to computing and robotics.

We invite contributions related to (i) foundational methods, encompassing probabilistic modeling, Bayesian inference, inverse problems, uncertainty quantification, and the development of interpretable machine learning architectures grounded in mathematical rigor; (ii) scientific and technological applications, featuring studies where data-driven approaches have enabled breakthroughs in fields such as climate science, astrophysics, quantum chemistry, systems biology, and materials discovery, as well as innovations in intelligent sensing and autonomous experimentation; and (iii) emerging challenges, in which we look at issues of model identifiability, error propagation, reproducibility, and algorithmic bias, as well as the ethical deployment of AI in high-stakes scientific contexts.

We welcome original research, methodological developments, and case studies that demonstrate both theoretical depth and practical impact. 

Dr. Kamal Dingle
Dr. Ziad Salem
Prof. Dr. Omer Rana
Dr. Michael Sylvester Packianather
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.