Logo - springer
Slogan - springer
Computer Science - Database Management & Information Retrieval | Journal of Big Data - a SpringerOpen journal

Database Management & Information Retrieval

Home > Computer Science > Database Management & Information Retrieval
Journal of Big Data

Journal of Big Data

Editor-in-Chief: B. Furht; T.M. Khoshgoftaar

ISSN: 2196-1115 (electronic version)

Journal no. 40537

Learn more about the metrics of this journal PB_Banner_Open_Access_13317_ani_575x60
The Journal of Big Data is a peer-reviewed open access journal published under the brand SpringerOpen.
  • Publishes scholarly research papers, methodologies and case studies on all aspects of big data and its applications
  • Provides a definitive reference to a broad, multidisciplinary community seeking practical solutions for present and future challenges
  • Covers big data technologies, architectures for massively parallel data processing, data mining tools and techniques, scalable storage systems, cloud computing platforms for big data analytics, data protection and privacy, social networks, visualization, and more

Journal of Big Data offers a forum for consolidating the state-of-the-art research in big data, for synthesizing new applications, and for providing practical solutions to a broad research community ranging from computer scientists to practitioners.

Related subjects » Applications - Computational Science & Engineering - Database Management & Information Retrieval - Signals & Communication

Abstracted/Indexed in 

SCOPUS, INSPEC, Google Scholar, CNKI, DOAJ, EBSCO Discovery Service, EBSCO TOC Premier, OCLC, ProQuest - Summon

Read this journal online

For authors and editors

  • Aims and Scope

    Aims and Scope

    Close
    The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. 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.
  • Submit Online
  • Instructions for Authors
  • Copyright and License Agreement

    Close
  • Sign Up for Article Alerts