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The Journal of Big Data and Artificial Intelligence (JBDAI) (ISSN 2692-7977) is an open access peer-reviewed journal devoted to the publication of high-quality papers on theoretical and practical aspects of big data, AI and machine learning. JBDAI (formerly JBDTP) is the flagship journal of the New Jersey Big Data Alliance (NJBDA).

Submissions

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Submission Preparation Checklist

As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.
  • The submission has not been previously published, nor is it before another journal for consideration (or an explanation has been provided in Comments to the Editor).
  • The submission file is in Microsoft Word, PDF document file format.
  • Where available, URLs for the references have been provided.
  • The text is single-spaced; uses a 12-point font; uses 1 in margins; employs italics, rather than underlining (except with URL addresses); and all illustrations, figures, and tables are placed within the text at the appropriate points, rather than at the end.
  • The text adheres to the stylistic and bibliographic requirements outlined in the Submission Guidelines.

Author Guidelines

Authors are required to comply with the following guidelines. Submissions may be returned to authors that do not adhere to these guidelines.

Please use our official Overleaf template when preparing your manuscript in LaTeX: JBDAI Overleaf Template

Alternatively, please download our official .docx template here: JBDAI .docx Template

Cost to Publish / APC:  ZERO publishing cost to author -  JBDAI does not charge any publishing fees at any stage or in any way to the author/s. All publishing costs for all accepted high quality articles are covered by NJBDA (https://njbda.org/), a non-profit association, with leading US universities and other organizations. This is a unique open access feature of JBDAI. 

Copyright Notice

COPYRIGHT

Copyright for all articles published in the Journal of Big Data and Artificial Intelligence (JBDAI) is retained by the authors. Authors grant JBDAI the right of first publication and a non-exclusive license to publish the work under a CC BY (default) or CC-BY-NC (by author’s choice) licenses. The corresponding author is treated as the responsible author.

All articles published in JBDAI are fully open access, at no cost to authors.

LICENSING

OPEN ACCESS - JBDAI uses the CC BY (Attribution 4.0 International) license.

Articles published in JBDAI are, by default, distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits users to share, copy, distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, provided that appropriate credit is given to the original author(s).

Licensing Option: Authors may alternatively choose the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) at the time of submission of manuscript to JBDAI. Under this license, reuse is permitted for non-commercial purposes only, with appropriate attribution to the original authors(s).

For more details, please visit:  https://creativecommons.org/licenses/by/4.0/ 

Right to Deposit

After first publishing their work with JBDAI, authors are then free to deposit their research at any reputable repository or University library or institutional database.

  1. Submitted version: Authors are strongly discouraged from submitting to any repository or any public posting of their work, directly or indirectly, to facilitate strict compliance with the blind review process. 
  2. Accepted version: Authors are then free to deposit the accepted version of their research manuscripts at any reputable repository or University library or institutional database. 
  3. Published version: After first publishing their work with JBDAI, authors are then free to deposit their research at any reputable repository or University library, or institutional database.

Plagiarism is strictly prohibited, and articles identified as being plagiarized at any stage will be rejected.

Use of AI: AI-generated content is discouraged, and articles identified as being prominently generated by AI may be rejected. However, the use of AI with full disclosure of all details including LLM or AI application, prompt, query, date and such other details are allowable to the extent of the research topic. Furthermore, the use of AI tools in this regard is acceptable only with human oversight and accountability.

AI systems and tools cannot be listed or cited as authors and co-authors since authorship entails responsibility and accountability for the integrity and accuracy of the work, which can only be attributed to and assumed by human contributors.

Use of generative AI tools to create or alter content, including, but not limited to figures, images, or graphical abstracts, is not permitted, except where AI is an integral part of the research methodology. In such cases, the use of the generative AI tool must be described transparently, including the AI application, prompt, query, and date.

Generative AI tools are not to be used in any part of the peer review process or editorial decision-making, since reviews and editorial decisions must reflect independent human judgment. Furthermore, submitted manuscripts are confidential and must not be uploaded into AI systems for review, editing, or evaluation.

If generative AI tools are used in any limited capacity (e.g., for the purpose of improving grammar and readability), it must be disclosed.

Archival Policy – All published articles are to be archived with OJS (Open Journal System), in the NJBDA databases and in the databases of NJBDA associated university libraries.

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.