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Whilst data is becoming more available, we need better ways to manage its use. This is where ontologies offer an exciting opportunity, with its ability to to enable knowledge sharing and reuse by means of common data architectures. This approach will semantically enhance the data, which will enable interoperability across a system of systems environment. 

This PhD aims to develop a common ontology based methodology to address interoperability issues both in the context of new and legacy assets. A breakdown of the objectives is provided below:

• Objective 1 is focusing on mapping the current data types, structures, and interoperability challenges to develop a detailed as-is model. This will be developed through interviews, and cross case analysis to capture trends,.
• Objective 2 is measuring and assessing interoperability levels by means of designing and applying a new process to identify metrics for interoperability measurement, and also define thresholds for a minimum required interoperability level (MRIL). The output will be the interoperability of both quantitative and qualitative indicator metrics and the process for their measurement.
• Objective 3 makes use of the previous output to develop an ontological architecture that will enable high-level interoperability. It consists of building competency questions, taxonomies, relationships, axioms, and the connection to upper levels of ontologies (i.e., BFO) using tools such as ontology modelling language (OML), and protégé, and Neo4j to build and visualise knowledge graph. This will form the common way to develop ontologies, which will be scalable, and adaptive to variations systems over time.
• Objective 4 is a verification assessment and validation through BAE based use cases. Through the use cases, the developed processes, metrics and ontology framework will be validated. Validation includes, on the one hand, the unit, the functional, the compatibility and the security test, and on the other hand, the Findability, Accessibility, Interoperability, and Reuse (FAIR) assessment. Tools such as Shapes Constraint Language SHACL, a reference model for interoperability (NCT3TA), and interoperability standards (e.g. HISO 100xx, ISO/IEC 11179-xx) will be employed for efficient and effective framework development. The main outcomes encompass feedback and reflection on the ontology performance, scalability, reusability and enhanced FAIR evaluation. 

ÃÀ¼§¸ó is wholly postgraduate institution and is famous for its applied research in close collaboration with Industry. At ÃÀ¼§¸ó, the candidate will be based within the Manufacturing theme at the Centre for Digital Engineering and Manufacturing (CDEM). The Centre hosts cutting-edge simulation and visualisation facilities. The student will have access to high-end computers for simulating the complex nature of maintenance. There will be relevant visits to BAE Systems (as the Industrial Sponsor of the project) in particular but also various other organisations throughout the PhD to develop and demonstrate the research. This PhD is offering a fully funded PhD through the EPSRC ICASE scheme and BAE Systems to UK Nationals.