Modern connected cyber-physical systems and their integrations to traditional information systems are increasingly dependant on data and data sharing management in their integrations. Many such systems are constantly changing and evolving their composition, often including integrations to third party (data-driven) services. This paper presents a model where a service framework, used to manage microservice configurations, is also utilized to manage access to MQTT Version 5 message topics. A proof of concept is provided demonstrating how Eclipse Arrowhead as the service management layer is capable of taking care of authentication and authorization of publish and subscribe actions to MQTT topics as individually managed data services. The study shows that JSON Web Tokens (JWT) from this service framework can be used in the MQTT Version 5 headers without violating the MQTT specification as demonstrated with HiveMQ as the message broker in the proof of concept implementation.

Superblocks, or large city-blocks with some degree of energy autonomy, have yet unanswered challenges related to data utilization. Within superblocks, a service-based data ecosystem could provide benefits in the form of higher-level control applications and flexibility for the energy community. In this paper, we use open data platforms and tools, namely FIWARE and Eclipse Arrowhead, to find a system design for energy data services. The research questions relate to recognizing what features and functions are required from data platforms to provide appropriate solution, and which of them are supported by the studied data platforms. The proposed solution is then tested with a prototype implementation in limited scale to gauge its viability. We conclude that FIWARE and Arrowhead complement each other and when used in unison fill most of the requirements established in this paper.

The future data-driven manufacturing ecosystems build upon data spaces where each participant controls how its own data are utilized. This goal is equally important in machinery where the networks comprise machine fleets and the data use cases range from local edge to various cloud systems and digital business integrations. These systems of systems require efficient, scalable data streaming with decoupled (e.g., publish-subscribe) platforms that enable the flexible connection of data producers and consumers in heterogeneous networks. This paper describes a work in progress about data autonomy, sovereignty, and trust in message brokers in machinery, aiming to contribute to initiatives, such as Gaia-X and International Data Spaces (IDS). First, the paper identifies requirements for platforms and communication that span edge and cloud. Second, it presents a technology survey about data autonomy in open, Internet-cabable brokers. These include Advanced Message Queueing Protocol (AMQP), MQ Telemetry Transport (MQTT), Apache Kafka and Apache Pulsar. It appears that there is little research about data autonomy in brokers and MQTT has the strongest base. The work continues to develop data autonomy into a message broker.

Interoperable communication technologies are of key importance in production systems with increasing needs for data in their adoption of data-driven methodologies and new, emerging applications. OPC UA PubSub defines an alternative to the traditional client-server communication with a publish-subscribe model for data to cater to scalability and data-driven cloud application needs. In this paper, the OPC UA PubSub model is compared to some other message broker and communication technologies and integrated with an existing message based integration model for evaluating the interoperability. A case example is presented where data payloads and information security practices are integrated using an adapter approach.

Efficiency of industrial processes and a high quality of the products can be achieved with advanced monitoring and control solutions. In addition, industrial processes often consume large amounts of energy and through their efficiency and use of resources also have a significant environmental impact. For industrial process optimisation it is necessary to integrate distributed data and functionality into plant-wide coordinating level solutions. From an implementation point of view this is challenging due to different communication protocols and messaging structures. In this paper an integration architecture is proposed that decouples control systems using a message bus mediator approach. The mediator acts as a unified point of access that through adapters facilitates integration of existing control systems to advanced plant-wide data-driven and event-driven control. It is demonstrated with a laboratory case presenting two examples applicable to real-life industrial problems.