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