Ontology-Driven Architectures and Applications of the Semantic Web

Dear Colleagues,

To guarantee adequate levels of quality, the manufacturing and service industries are increasingly moving towards the constant and systematic monitoring of all aspects concerning their products, facilitated by commonly used tools (such as smartphones, smartwatches, etc.) that contribute to the production of more or less explicit information.

This projection, which could be minimal (e.g., remote control of production progress) or complete (e.g., the provision of automatically generated services from existing Web services), requires the Web as a means of sharing and exchanging information and the Semantic Web for automatic retrieval and combination in processes that can elaborate this information. Through the specification of standard languages, the Semantic Web enables the association between semantics and the data and the services/processes that manipulate this data. To date, the predominant use of technologies developed within the Semantic Web concerns the retrieval of information for direct human use, but in the vision of the Semantic Web, the goal is to enable conscious communication between machines to enhance what they can do for humans. Consequently, the knowledge engineering skills required for the conception and use of new applications will become progressively less specific. The means of progressing in this direction always appears to be the same: in the beginning, there was a need for hardware-specific skills; subsequently, it was necessary to know how to write programmes and data on punch cards; even later, there was a complete detachment from specific knowledge of storage media for the development of software applications. Progress continues, more or less consciously, in the same way through the implementation of ever-higher levels of abstraction in machines: in the near future, it will not be necessary to be a knowledge engineer to be able to develop intelligent applications because machines will be able to abstract. Automated reasoning in machines is useful to progress in this direction.

The development of automatic reasoners that enable the discovery of implicit knowledge in knowledge bases written with standard Semantic Web languages also makes it possible to combine the pieces of knowledge provided by Web services or components of processes that implement such services. Moreover, with the advent of mobile applications, the sources of data production on the Web are increasing each day, together with the need for new, increasingly refined applications.

However, regarding the Semantic Web principles, there are certain limits to the ontological representation of the decidable OWL fragment, reflected in what an automatic reasoner can infer. However, there may be application scenarios where, to achieve specific functionalities, particular types of inference must be applied, which require knowledge representation primitives outside the decidable OWL fragments.

The questions that arise from the perspective of the Semantic Web concern the possibility of combining different types of knowledge representation to offer new application functionalities and the constraints ontology-driven architectures must fulfil in order to support this type of applications. This Special Issue focuses on theoretical and practical problems related to architectures and techniques, as well as the automatic generation of ontology-driven processes, looking at what we may consider to be new information sources, as well as tools for the realization of software applications that are capable of implementing them.

Topics of interest include but are not limited to the following:

• Specification and design of formal and informal ontology representation schemes;
• Ontology-driven framework enhanced with logical rules’ integration;
• Tools and environments to support ontology-based system development;
• Enhanced ontology-driven architecture involving emotional states’ management;
• Domain modelling and analysis for the application of extra SW inferences;
• Ontology-based application innovative use cases;
• Development methodologies, environments and tools;
• Ontology architectures including explanation capabilities;
• Ontology-based applications for process management and orchestration;
• Design and management of extra ontology artefacts (constraints, mappings, data sources, queries, M2M interfaces, etc.);
• Ontology-driven architecture for virtual sensor applications;
• Combining OWL reasoners with different types of logical inferences;
• Ontology alignment and integration capabilities;
• Ontology-based applications for data management.

Dr. Domenico Redavid
Dr. Stefano Ferilli
Guest Editors

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• semantic web
• knowledge representation
• automatic reasoning
• ontology architectures
• ontology applications
• process orchestration
• virtual sensors
• ontology modelling
• logical rules