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Frontiers in Big Data (FBD)

Publisher :

Frontiers Media S.A.

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Big Data Networks
  • Big Data AI In High Energy Physics
  • Cybersecurity

    • +10

e-ISSN :

2624-909X

Issue Frequency :

Monthly

Impact Factor :

2.4

Est. Year :

2025

Mobile :

410215101700

Country :

Switzerland

Language :

English

APC :

YES

Impact Factor Assignee :

Google Scholar

Email :

bigdata.editorial.office@frontiersin.org, bigdata@frontiersin.org

Journal Descriptions

Frontiers in Big Data is an interdisciplinary journal that focuses on the advancements and applications of big data. Led by Field Chief Editor, Dr Huan Liu (Arizona State University, USA) the journal focuses on understanding and managing the power of big data, as well as acquiring intelligence from information to address and solve the biggest challenges of humankind. Frontiers in Big Data welcomes research contributions across the multifaceted and vast field, which advance new methodologies and develops data science, AI, data mining, and medical health informatics. Topics include, but are not limited to: big data networks big data and AI in high energy physics cybersecurity and privacy data analytics for social impact data mining and management data science data-driven climate sciences machine learning and artificial intelligence medicine and public health. In particular, the journal welcomes submissions that support and advance the UN’s Sustainable Development Goals (SDGs), notably SDG 9: industry, innovation and infrastructure. Frontiers in Big Data is committed to advancing developments in the field by allowing unrestricted access to articles, and communicating scientific knowledge to researchers and the public alike, to enable the scientific breakthroughs of the future.


Frontiers in Big Data (FBD) is :

International, Peer-Reviewed, Open Access, Refereed, Big Data Networks, Big Data AI In High Energy Physics, Cybersecurity, Privacy, Data Analytics For Social Impact, Data Mining, Management, Data Science, Data-Driven Climate Sciences, Machine Learning, Artificial Intelligence, Medicine, Public Health , Online Monthly Journal

UGC Approved, ISSN Approved: P-ISSN , E-ISSN - 2624-909X, Established in - 2025, Impact Factor - 2.4

Not Provide Crossref DOI

Indexed in Scopus, WoS, DOAJ, PubMed

Not indexed in UGC CARE

Indexing

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Google Scholar
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Scopus
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WoS

+8 More

Publications of FBD

  • dott image September, 2022

A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth

Recent years have seen an increase in the application of machine learning to the analysis of physical and biological systems, including cancer progression. A fundamental downside to these to...

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