A community with knowledge organisation based on ontologies will enable an increase in the computational intelligence of its information systems. However, due to the worldwide diversity of communities, a high number of knowledge representation elements, which are not semantically coincident, have appeared representing the same segment of reality, becoming a barrier to business communications. Even if a domain community uses the same kind of technologies in its information systems, such as ontologies, it doesn't solve its semantics differences. In order to solve this interoperability problem, a solution is to use a reference ontology as an intermediary in the communications between the community enterprises and the outside, while allowing the enterprises to keep their own ontology and semantics unchanged internally. This work proposes MENTOR, a methodology to support the development of a common reference ontology for a group of organisations sharing the same business domain. This methodology is based on the mediator ontology (MO) concept, which assists the semantic transformations among each enterprise's ontology and the referential one. The MO enables each organisation to keep its own terminology, glossary and ontological structures, while providing seamless communication and interaction with the others.

The current Internet-of-things (IoT) hype, pushed by the unprecedented rate of the technological enablers’ innovation, is threatening to leave behind some major, not so obvious, unresolved issues. IoT platforms will extend existing enterprise information systems (EIS) infrastructures to encompass cross-domain sensing and actuating capabilities, thus introducing additional complexity and major risks to the implementation. Furthermore, IoT platforms are typically driven by models of the trivial complexity; they support very simple data structures and almost no business logic implementation. Finally, IoT systems are today managed centrally, which often means less openness, less flexibility and greater change management costs. In this article, we provide the overview of the scientific disciplines which could contribute to the resolution of the IoT implementation problem, namely requirements engineering, change management/continuous improvement, model-based systems engineering, system architecture design, interoperability and policy and regulatory aspects. Then, we identify the challenges of these contributions in the context of IoT and finally make an attempt to identify research directions which could have a significant impact. The discussion of the challenges and opportunities is illustrated by the proposed domain framework for implementation of open IoT ecosystems.

In the last decades, the increasing complexity of industrial information technology has led to the emergence of new trends in manufacturing. Factories are using multiple Internet of Things (IoT) platforms to harvest sensor information to improve production. Such a transformation contributes to efficiency growth and reduced production costs. To deal with the heterogeneity of the services within an IoT system, Service-Oriented Architecture (SOA) is referred to in the literature as being advantageous for the design and development of software to support IoT-based production processes. The aim of SOA-based design is to provide the leverage to use and reuse loosely coupled IoT services at the middleware layer to minimise system integration problems. We propose a system architecture that follows the SOA architectural pattern and enables developers and business process designers to dynamically add, query or use instances of existing modular software in the IoT context. Furthermore, an analysis of utilization of modular software that presents some challenges and limitations of this approach is also in the scope of this work.