Journal of Big Data Research

Aims and Scope


Journal of Big Data Research (JBR) is an open access, peer-reviewed journal devoted to the science and technology of big data and its associated areas. JBR aims to become the premier outlet for research advances in big data, including advances in data science, data mining, analytics, and associated technologies. JBR is dedicated to publishing the latest developments in the field and to encouraging research to enable the development of more effective and efficient techniques and tools. JBR seeks to provide a platform for scholars, practitioners, and decision-makers to share and exchange research results, experiences, and ideas.

JBR focuses on the science and technology of big data, as well as its applications in various fields, including business, public administration, healthcare, engineering, medical and life sciences, computer science, and artificial intelligence. The scope of coverage encompasses the whole range of big data, from theoretical aspects and algorithmic developments to implementations and usage in the real world. JBR also emphasizes the ethical considerations that come with the collection and analysis of large data sets.

JBR is dedicated to the dissemination of scholarly research and the latest developments in big data research. The journal encourages the exchange of ideas among a wide range of disciplines, promoting high-quality research. It focuses on both theoretical and practical aspects of big data research and it is focused on the challenges that big data facing today to move forward encompassing but not restricted to: big data technologies, big data analytics, data storage, data capture, and data mining, machine learning algorithms for big data, cloud computing platforms, data visualization, architectures for massively parallel processing, distributed file systems, and databases and scalable storage systems.

JBR accepts and publishes contributions in the form of Original Research, Reviews, Literature reviews, Conference proceedings, Case reports, Short communication, Theses, letters to the editor, and Editorials.

A few keywords were outlined, which define the scope of the journal. If you have any queries, do contact us at [email protected]


  • Big data
  • Health care
  • E-Commerce
  • Data visualization
  • Visualization and design
  • Data capture and storage
  • Databases
  • Social networking
  • Parallel processing
  • Big data analytics
  • Machine learning algorithms
  • Geoscience
  • Data protection
  • Machine learning algorithms
  • Data acquisition
  • New technologies
  • Big data analysis
  • Data mining tools
  • Big data technologies
  • Data visualization
  • Cloud computing platforms
  • Deep learning algorithms
  • Physics and Astronomy
  • Big data analytics in healthcare
  • Big data healthcare
  • Distributed file systems
  • Big data as a service
  • Big data research
  • Big data ethics
  • Big data industry
  • Big data health
  • Data-intensive computing
  • Big data analytics in healthcare promise and potential
  • Big data cancer
  • Medical big data
  • Environment and Climate
  • Big data industry standards
  • Big data medicine
  • Mobility and big data
  • Big data analytics in small business enterprises (smes)
  • Big data search architectures scalability and efficiency
  • Data acquisition integration cleaning and best practices
  • Distributed and peer-to-peer search
  • Energy-efficient computing for big data
  • Multimedia and multi-structured data- big variety data
  • Social web search and mining
  • Visualization analytics for big data
  • Big Data And Analytics In Healthcare
  • Big Data Analytics In Transportation
  • Artificial Intelligence And Big Data


Journals By Subject

Life Sciences
Medical Sciences