Guest Editorial: Data-Centric Big Services

Quan Z. Sheng, Xiaofei Xu, Rong N. Chang, Liang-Jie Zhang

Abstract: The papers in this special section focus on data centric big data services. As an overwhelming amount of data is generated at a faster rate every day from all sources, and applications such as cloud services, the Internet of Things (IoT), social network services and intelligent terminals, it has become more urgent than ever to design, deploy and provision services more wisely so that the provisioned services could support effective acquisition, storage, transformation, process, management and utilization of such data. Manipulating and getting the most out of the Big Data can bring unprecedented value and new opportunities that are critical to business success. Services should be ideally provisioned in a way that speeds up data processing, scales up with data volume, and improves the adaptability and extensibility over data diversity and uncertainties, and finally turns low-level data into actionable knowledge towards better understanding and manipulation of the Big Data. Datacentric big service is an inevitable evolution of services with the emergence of big data in the last decade.

External IDs:dblp:journals/tsc/ShengXCZ19