Data Science and Engineering (DSE) is an international, peer-reviewed, open access journal published on behalf of the China Computer Federation (CCF), and is affiliated with CCF Technical Committee on Database (CCF TCDB). Focusing on the theoretical background and advanced engineering approaches, DSE aims to offer a prime forum for researchers, professionals, and industrial practitioners to share their knowledge in this rapidly growing area. It provides in-depth coverage of the latest advances in the closely related fields of data science and data engineering.

More specifically, DSE covers four areas: (i) the data itself, i.e., the nature and quality of the data, especially big data; (ii) the principles of information extraction from data, especially big data; (iii) the theory behind data-intensive computing; and (iv) the techniques and systems used to analyze and manage big data.

The journal publishes high-quality, original research papers, brief reports, and critical reviews in all theoretical, technological, and interdisciplinary studies that make up the fields of data science and engineering and its applications.  

The publication costs are covered by the sponsor Nanjing Sinovatio Technology Co. Ltd, so authors do not need to pay an article-processing charge.

DSE operates a double-blind peer-review system, where the reviewers do not know the names or affiliations of the authors and the reviewer reports provided to the authors are anonymous.

    An official publication of China Computer Federation (CCF)
    Open access and fully sponsored by CCF
    Integrates theories and methods from computer science, statistics, information science, and other fields
    Publishes original papers on data collection and management, data integration and correlation, information and knowledge extraction, and data applications, etc.
    Rapid review and publication of articles