Journal of Big Data
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 closely examines the challenges facing big data research 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.
As an open-access journal, the Journal of Big Data ensures that any published research will remain freely available to all readers, and enables authors to benefit from the widest distribution of their work. Academic and industrial researchers, as well as practitioners, will find the journal to be a definitive reference for all aspects of big data and its applications.
Gary Smith (September 2018)
- Journal Title
- Journal of Big Data
- Volume 1 / 2014 - Volume 5 / 2018
- Online ISSN
- Springer International Publishing
- Additional Links
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