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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.
Current Specialty Sections include:
1) Medicine and Public Health
2) Big Data Networks
3) Cybersecurity and Privacy
4) Data Mining and Management
5) Data-driven Climate Sciences
6) Machine Learning and Artificial Intelligence
7) Big Data and AI in High Energy Physics
There are a number of ways you can contribute to the journal:
· Propose a Research Topic
· Submit a manuscript to the journal
· Apply to join the Editorial Board of a section as Associate or Review Editor
· Recommend a new Specialty Section for inclusion in the journal
Frontiers in Big Data is a member of the Committee on Publication Ethics.
Short Name: Front. Big Data
Electronic ISSN: 2624-909X
Indexed in: Google Scholar, DOAJ, CrossRef, Digital Biography & Library Project (dblp), CLOCKSS, OpenAIRE
Frontiers in Big Data is composed of the following Specialty Sections:
The specialty sections of Frontiers in Big Data welcome submission of the following article types: Brief Research Report, Clinical Trial, Community Case Study, Conceptual Analysis, Correction, Data Report, Editorial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Policy and Practice Reviews, Review, Specialty Grand Challenge, Study Protocol, Systematic Review and Technology and Code.
When submitting a manuscript to Frontiers in Big Data, authors must submit the material directly to one of the specialty sections. Manuscripts are peer-reviewed by the Associate and Review Editors of the respective specialty section.
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For all queries regarding manuscripts in Review and potential conflicts of interest, please contact email@example.com
For queries regarding Research Topics, Editorial Board applications, and journal development, please contact firstname.lastname@example.org