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Future Research Directions for Dataspaces, Data Ecosystems, and Intelligent Systems

  • Edward CurryEmail author
Open Access
Chapter

Abstract

As we move toward 2030, today’s computing paradigms such as data-intensive computing (Big Data), Open Data [380], Knowledge Graphs, Machine Learning, Large-Scale Distributed Systems [381], Internet of Things (IoT), Physical-Cyber-Social Computing [14], Service-Oriented [382], and Cloud/Edge Computing [383] will be the foundations to the realisation of the vision of intelligent systems. In fact, real-world intelligent systems are being enabled by a combination of these paradigms using a mixture of architectures (centralised, decentralised, and a combination of both) and infrastructures such as Middleware and IoT platforms to support the development of intelligent systems and applications [13, 67, 295, 384].

Keywords

Dataspaces Data ecosystems Intelligent systems Research challenges Technology adoption Trusted data sharing Governance Incremental systems engineering Human-centricity 

Copyright information

© The Author(s) 2020

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Authors and Affiliations

  1. 1.National University of Ireland GalwayGalwayIreland

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