Future Research Directions for Dataspaces, Data Ecosystems, and Intelligent Systems
As we move toward 2030, today’s computing paradigms such as data-intensive computing (Big Data), Open Data , Knowledge Graphs, Machine Learning, Large-Scale Distributed Systems , Internet of Things (IoT), Physical-Cyber-Social Computing , Service-Oriented , and Cloud/Edge Computing  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].
KeywordsDataspaces Data ecosystems Intelligent systems Research challenges Technology adoption Trusted data sharing Governance Incremental systems engineering Human-centricity
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