Frontiers in Big Data

Aims & Scope

Complementing the adage of "knowledge is power," with the voluminous data that encompasses our lives, we learn today that "data is the new oil." Big data is pervasive and innately interdisciplinary, and can only become bigger and more - it exhibits characteristics that go beyond scale: big data is multifaceted, it evolves in temporal or streaming forms, and it includes disparate dimensions such as social, spatial, relational, and educational.

Big data is not just confined in centralized database management systems, it can be produced anytime anywhere, shared explicitly or implicitly, linked automatically, and obtained by easy-to-use tools.

Moreover, the key role of big data does not only revolve around the amount of data, but also on how to develop and apply high-powered analytics for knowledge discovery.

Big data provides ammunition to powerful machine learning algorithms and manifests its impact and reach beyond any individual field.

Big data can not only benefit research, development, and industrial applications, but also invite collaborations and usher in new methodologies to advance data science, AI, data mining, and medical and health informatics.

Understanding and managing the power of big data, as well as acquiring intelligence from information, is key to face the biggest challenges of the humankind.

The pervasive big data has demonstrated its great potential in artificial intelligence research and advancement across many fields: from climate science to cybersecurity, to medicine and public health, to name but a few.

Committed to open access and transparent review processes, Frontiers in Big Data publishes rigorously peer-reviewed research on the cutting-edge, disruptive technological revolution of big data, through its various applications and forms.

Being interdisciplinary and innovative, the journal is at the forefront of disseminating scientific knowledge and impactful discoveries to academics, policy-makers, industry, and the public worldwide.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 1,175.00 CHF. Learn more.

Explore journals without APCs for alternative publishing options.