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NIST Big Data Interoperability Framework: Volume 2, Big Data Taxonomies
Published
Author(s)
Wo L. Chang, Nancy Grady
Abstract
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is outpacing scientific and technological advances in data analytics. To advance progress in Big Data, the NIST Big Data Public Working Group (NBD-PWG) is working to develop consensus on important, fundamental concepts related to Big Data. The results are reported in the NIST Big Data Interoperability Framework (NBDIF) series of volumes. This volume, Volume 2, contains the Big Data taxonomies developed by the NBD-PWG. These taxonomies organize the reference architecture components, fabrics, and other topics to lay the groundwork for discussions surrounding Big Data.
Big Data, Big Data Application Provider, Big Data characteristics, Big Data Framework Provider, Big Data taxonomy, Data Consumer, Data Provider, Data Science, Management Fabric, Reference Architecture, Security and Privacy Fabric, System Orchestrator, use cases.
Chang, W.
and Grady, N.
(2019),
NIST Big Data Interoperability Framework: Volume 2, Big Data Taxonomies, Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.SP.1500-2r2
(Accessed December 12, 2024)