7.5.1 An incremental hybridisation of heterogeneous case studies to develop an ontology for capability engineering
Summary (3 min read)
Introduction
- This paper is primarily based on the research conducted by the INCOSE UK Capability Working Group (CWG) which identified eight perspectives of capability and developed an entity relationship diagram for the concept of capability engineering (Henshaw et al. 2010).
- The holistic thinking mindset, socio-technical nature and similarity in scope to views of systems engineering are emphasised to elaborate the significant difference from product systems engineering and broader characteristics to process perspective of systems engineering.
- The scope of capability engineering is large and there are challenges in producing an all-embracing model with a vocabulary agreed by all parties.
- A case study based information extraction approach that looked at the problem space in chunks is described within this paper.
Objectives
- A set of high level objectives are derived through analysis of the CWG workshop discussions and prior meetings with the CWG ontology work stream members: Objective 1: to develop a sector-independent ontology by extracting and classifying information from case studies across heterogeneous domains to explicitly specify the concept of capability engineering.
- To evaluate (verify and validate) the ontology through expert reviews and application to a case study, also known as Objective 3.
- The next section discusses the current ontology-based approaches and proposes a flow chart for the development of the capability engineering ontology.
Ontology-Based Approaches
- Ontology-based modelling for information and knowledge management has been widely used (Hughes et al.
- These are discussed later within the requirements analysis section.
- A variety of methods, methodologies, tools and languages for ontology development have already been analysed by various authors (Corcho et al.
- The pre-analysis phase predominantly focuses on case studies.
Case Studies
- Appropriateness of case study material Case studies are relatively important when extracting the necessary information and evaluating the ontology developed.
- A mark-up tool is used to extract important terminology from the case studies and Protégé to construct the ontology i.e. concepts and their relationships.
- Examples from these case studies are used to explore and illustrate their relation to the worldviews (Ws) of capability (Table 1) as described by the INCOSE UK Capability Working Group (Henshaw et al. 2010).
- W2. Capability Planning – A set of explicit user wants e.g. “delivering 50K passengers an hour in the peak” is translated into a written set of solution independent requirements and systems design options to satisfy the capability needs e.g. 24 trains per hour, new signalling, automatic train operation, new rolling stock and new franchises.
- An enterprise of users and suppliers including the MoD and industry develop and operate carrier strike capability solution (that aims to project UK Air Power on an expeditionary basis) across all contributing components of capability from equipment to infrastructure (i.e. JCA integration with the ship, dockyard developments) by deploying all appropriate systems engineering approaches and techniques from cradle to grave.
Requirements Analysis
- This section reports on the requirements of the overall study.
- This involves employing an iterative requirements analysis approach to capture, analyse, and synthesise the key stakeholder requirements.
- Since this is not a product or software development project, the requirements analysis study used techniques from a synthesis of approaches including the Quality Function Deployment (QFD), Unified Modelling Language (UML) and the Volere Requirements Specification (VRS).
- The requirements specification pro-forma listing these requirements is extracted from the hybrid of STA and VRS template as shown in Figure 3.
- The stakeholders are divided into three groups; professional body, industrial and academic.
Ontology Development
- This section exploits the process flow chart illustrated in Figure 1 to develop an ontology.
- The pre-analysis, modelling and post-analysis phases are described further.
Pre-analysis
- The pre-analysis involved a literature review, requirements analysis and resource identification as described earlier.
- Examination of the case studies, reports and documents to check their relevance and richness for information extraction has already been discussed.
- Existing ontologies and approaches e.g. ontology for product-service system (Annamalai et al. 2010) have been analysed to build a process flow chart that encapsulated a procedure for ontology development.
Ontology modelling
- The ontology modelling phase involved information extraction and classification.
- Protégé is “a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies” (Protégé 2011).
- This task involved importing the terms or concepts extracted through the mark-up tool into MS Excel for further analysis.
- The analysis comprised subsequent grouping of these terms into more general concepts; generating statements showing the relationship and context of use of the terms; adding new concepts that are not capture by the ERD classification; and also generating RDF n-triples by using the subject-predicate-object expressions to denote the relationships.
- A total of 157 n-triples were created for INCOSE CWG perspective analysis case study on its own.
Post-analysis
- The post-analysis phase is concerned with ontology evaluation and therefore comprises the validation of the ontology through expert reviews, user feedback and application to a case study to check its suitability.
- The evolution of the ontology is significantly important as procedures need to be put in place for keeping the ontology revised and up to date i.e. adding, deleting or modifying the ontology to incorporate boundary changes.
- The outcome of the three phases resulted in the initial ontology as discussed in the next section.
Analysis of initial results
- The term extraction results for three of the case studies are summarised in Figure 7.
- The NPfIT and CSAR case studies are parked to be used when evaluating the finalised ontology.
- Figure 9 shows the initial results for capability engineering ontology v1.1.
- The use of ‘AnEnterprise’ and ‘Organisations’ can be expressed through the cardinality constraints.
Discussion
- This research proposed a process flow chart for incremental ontology development though using case study material from heterogeneous domains.
- It also presents and discusses initial findings from a study that develops an ontology for capability engineering.
- The RDF n-triples results are from three case studies with two of them being validated through expert focus groups.
- This task is partly automated but predicates such as ‘subClassOf’, ‘consistsOf’, ‘comprise’ and ‘encompasses’ require further human assisted analysis for insertion into Protégé.
- The final version of the ontology can be an enabler to develop such tools.
Conclusion
- This paper presents the first steps towards establishing an ontology to enable semantic interoperability in order to support institutionalisation of the concept of capability engineering.
- The task of coming up with a common set of concepts, properties and relationships to enable a standard domain terminology and common understanding within heterogeneous domains is significant, because this will be an enabler of cross-domain knowledge sharing.
- The capability engineering paradigm is gaining attention in several domains and signals increased efforts to manage large and complex systems more effectively from the acquisition and operational perspectives.
- The remaining challenges for this work include getting general acceptance and development of a hierarchy.
- The final version of the ontology will be imported into Protégé to support collaborative discussions i.e. seeking international feedback over the internet.
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"7.5.1 An incremental hybridisation ..." refers background in this paper
...Generally, an ontology is defined as an explicit specification of a conceptualisation where concepts and their relations are extracted from the real world (Studer et al. 1998; Duan et al. 2009)....
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...Ontology-based modelling for information and knowledge management has been widely used (Hughes et al. 2009; Duan et al. 2009; Dongmin et al. 2010; Liu et al. 2010)....
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...…knowledge modelling framework for intangible cultural heritage (Tan et al. 2009); • domain ontology life-cycle engineering framework for modular product design (Duan et al., 2009; Liu et al. 2011); and • ontology for product-service system by Cranfield University (Annamalai et al. 2010)....
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...2009); • domain ontology life-cycle engineering framework for modular product design (Duan et al., 2009; Liu et al. 2011); and • ontology for product-service system by Cranfield University (Annamalai et al....
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4 citations
"7.5.1 An incremental hybridisation ..." refers background in this paper
...Johnson (2009) defined CSAR as a specific task performed by rescue forces to effect the recovery of assets (including humans, platforms and data) isolated in hostile territory....
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2 citations
"7.5.1 An incremental hybridisation ..." refers background in this paper
...• ontology-based conceptual knowledge representation model (Kourlimpinis et al. 2008); • ontology-based information model development for science information reuse and integration (Hughes et al....
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...…for capability engineering as a result of analysing a variety of developments including • ontology-based conceptual knowledge representation model (Kourlimpinis et al. 2008); • ontology-based information model development for science information reuse and integration (Hughes et al. 2009); •…...
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