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Journal Photo for Journal of Big Data
Peer reviewed only Open Access

Journal of Big Data (JBD)

Publisher : Springer Nature
Computer Science Hardware Architecture
Claim Your Journal Get PRC Visit Website
e-ISSN 2196-1115
Issue Frequency Monthly
Impact Factor 8.1
Est. Year 2014
Mobile 4408002605666
Country India
Language English
APC YES
Impact Factor Assignee Google Scholar
Email bfurht@fau.edu

Journal Descriptions

The Journal of Big Data publishes open-access original research on data science and data analytics. Deep learning algorithms and all applications of big data are welcomed. Survey papers and case studies are also considered. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.

Journal of Big Data (JBD) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Computer Science, Hardware, Architecture, Computer Networks and Communications, Information Systems, Decision Sciences , Online , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2196-1115, Established: 2014, Impact Factor: 8.1
  • Does Not Provide Crossref DOI

  • Indexed in: Scopus, WoS, DOAJ

  • Not indexed in PubMed, UGC CARE

Indexing

Publications of JBD

Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction
Mohammad Ali Moni February, 2024
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activit...
A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions
Ketan Kotecha January, 2024
Deep learning has seen significant growth recently and is now applied to a wide range of conventional use cases, including graphs. Graph data provides relational information between elements...
Disaggregating IMERG satellite precipitation over Czech Republic: an innovative approach using hybrid Extreme Gradient Boosting based on Fuzzy Spatial...
Dr. Kiran Jalem June, 2025
Accurate precipitation estimation at high spatial and temporal resolutions is essential for hydrological and meteorological applications, especially in regions experiencing water resource de...
HEC-HMS Based Rainfall-Runoff Model for Araku Valley, Visakhapatnam, Andhra Pradesh, India
Dr. Kiran Jalem June, 2025
It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall tocalculate the required quantities of water storage in river basin and to determine the likeli...