Over the years, a growing number of semantic data repositories have been made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user’s expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this difficulty have suggested using question answering (QA) systems to provide user‐friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full‐text articles published since 2015 on methods and systems for KBQAs. Sixty‐six articles were reviewed to describe their underlying reference architectures.

The world is assisting to the fourth industrial revolution, with several domains of science and technology being strongly developed and, specially, being integrated with each other, allowing to build evolvable complex systems. Data digitization, big-data analysis, distributed control, Industrial Internet of Things, Cyber-Physical Systems and self-organization, amongst others, are playing an important role in this journey. This paper considers the best practices from previous successful European projects addressing distributed control systems to develop an innovative architecture that can be industrially deployed. For this purpose, a particular design process has to be addressed in order to consider the requirements and functionalities from various use cases. To investigate the known practices, four use cases are enlighted in this paper, which cover a wide spectrum of the European industrial force, as well as industrial standards to support a smooth migration from traditional systems to the emergent distributed systems.

The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS‐FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine‐to‐machine operations. We applied a set of metrics to evaluate its “FAIRness” and created an application scenario in the rare diseases domain.

Empowering distributed entities with decisional and adaptation capabilities is the current trend in control systems operating in highly changing environments. Cyber-Physical Systems (CPS) is a paradigm addressing this challenge as it allows the integration of both physical and decisional parts. By acting in highly changing environments, these complex control systems must be resilient. This paper proposes a trust and risk management mechanism to be deployed in CPS for resilience improvement. This mechanism, inspired by social and biological behaviour, is deployed in a smart-grid demonstrator. The preliminary results show that embedding this mechanism into distributed entities can lead to an increase of the system stability and efficiency dealing with system uncertainty and perturbations, and consequently improving the system resilience.

Multi-agent system (MAS) is being pointed out as a suitable technology to develop systems that demand flexibility, robustness and re-configurability. Consequently, a significant effort has been noticed to apply MAS to industrial domains exhibiting these characteristics, like manufacturing and smart grids. In spite of the adequacy of the MAS principles to solve the industrial requirements, the truly deployment of MAS for industrial applications is far to be solved. This paper discusses the current challenges for the deployment of MAS in the context of industrial applications, mainly focusing the integration of agents with physical equipment and the ability to run agents directly in industrial or low cost controllers. An experimental MAS solution for a smart grid case study was deployed aiming to support the discussion.