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Introduction to the Special Issue on Data Science for Next Generation Big Data

Introduction to the Special Issue on Data Science for Next Generation Big Data Introduction to the Special Issue on Data Science for Next Generation Big Data The first age of Big Data started roughly ten years ago. It has had an enormous impact in many fields of science. It underlies the rapid development of data-driven applications and gives rise to many innovative data processing systems. Ten years on, Big Data is entering a new generation. In particular, data is being used at a much larger, global scale. Furthermore, there is a trend of multiple data owners coming together to perform collaborative data analytics, and many data- driven business decisions are made based on statistical analytics from multi-source, multimodal, and worldwide data. The new generation of Big Data opens the door for innovative data-driven applications that are not possible even in the early age of Big Data. However, the new scale, both in terms of the data and the number of participants, brings significant challenges ranging from secure data sharing to federated data analytics. At the same time, emerging technologies such as 5G, AI, and blockchains demand high-performance, scalable, and secure data management. It is therefore crucial to have new theories, algorithms, and systems, for future applications that make various trade-offs between security, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM/IMS Transactions on Data Science Association for Computing Machinery

Introduction to the Special Issue on Data Science for Next Generation Big Data

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2022 Copyright held by the owner/author(s).
ISSN
2691-1922
eISSN
2577-3224
DOI
10.1145/3507467
Publisher site
See Article on Publisher Site

Abstract

Introduction to the Special Issue on Data Science for Next Generation Big Data The first age of Big Data started roughly ten years ago. It has had an enormous impact in many fields of science. It underlies the rapid development of data-driven applications and gives rise to many innovative data processing systems. Ten years on, Big Data is entering a new generation. In particular, data is being used at a much larger, global scale. Furthermore, there is a trend of multiple data owners coming together to perform collaborative data analytics, and many data- driven business decisions are made based on statistical analytics from multi-source, multimodal, and worldwide data. The new generation of Big Data opens the door for innovative data-driven applications that are not possible even in the early age of Big Data. However, the new scale, both in terms of the data and the number of participants, brings significant challenges ranging from secure data sharing to federated data analytics. At the same time, emerging technologies such as 5G, AI, and blockchains demand high-performance, scalable, and secure data management. It is therefore crucial to have new theories, algorithms, and systems, for future applications that make various trade-offs between security,

Journal

ACM/IMS Transactions on Data ScienceAssociation for Computing Machinery

Published: Mar 17, 2022

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