Welcome to the online submission and editorial system for International Journal of Data and Network Science


International Journal of Data and Network Science is an online international journal for publishing high quality peer reviewed papers in the field of theoretical and applied data science affairs. The primary objective of this journal is to exchange ideas about processing big data, social network, etc. Subject areas include, but are not limited to the following fields:

The primary aim of this publishing company is to perform fast and reliable process for contributors. Once a paper is accepted, our staffs work hard to provide online version of the papers as quickly as possible. All papers are assigned valid DOI number once they appear online just to make sure that the other people researchers cite them while no volume and numbers are still assigned to the papers. We believe this could help the existing knowledge grow faster; however, the actual publication of a paper with volume and number will not exceed more than 4 months.

International Journal of Data and Network Science is an open access journal, which provides instant access to the full text of research papers without any need for a subscription to the journal where the papers are published. Therefore, anyone has the opportunity to copy, use, redistribute, transmit/display the work publicly and to distribute derivative works, in any sort of digital form for any responsible purpose, subject to appropriate attribution of authorship. Authors who publish their articles may also maintain the copyright of their articles.

International Journal of Data and Network Science applies the Creative Commons Attribution (CC BY) license to works we publish (read the human-readable summary or the full license legal code). Under this license, authors keep ownership of the copyright for their content, but permit anyone to download, reuse, reprint, modify, distribute and/or copy the content as long as the original authors and source are cited. No permission is needed from the authors or the publishers. Appropriate attribution can be provided by simply citing the original article (e.g., Orouji, M. (2017). Social media in Canada. International Journal of Data and Network Science, 1(1), 1-4. DOI: 10.5267/j.ijdns.2017.1.001). For any reuse or redistribution of a work, users have to also make clear the license terms under which the work was published. This broad license was developed to facilitate free access to, and unrestricted reuse of, original works of all kinds. Applying this standard license to your own work will ensure that it is freely and openly available in perpetuity.