Tailoring ontology retrieval for supporting requirements analysis

• Published in: Advanced engineering informatics 2024-01, Vol.59, p.102231, Article 102231
• Main Authors: Beydoun, Ghassan, Low, Graham, Gill, Asif, Moniruzzaman, Monir, Shen, Jun
• Format: Article
• Language: English
• Subjects: Ontologies; Ontology retrieval; PageRank; Requirement analysis
• ISSN: 1474-0346; 1873-5320
• DOI: 10.1016/j.aei.2023.102231

It is well accepted that domain ontologies can support requirement analysis activities, particularly in detecting inconsistencies and incompleteness of requirement models. These benefits critically depend on the provision of a suitable ontology. We observe the context of supporting requirement analysis provides both opportunities and restrictions when choosing the most appropriate ontology retrieval mechanisms. Requirement models are the basis for retrieving the most influential ontologies and are not the typical retrieval domain ontologies. For instance, a retrieval ontology derived from the requirement is not expected only to be a hierarchical taxonomy, nor is it limited to the boundaries of a single domain, nor does it cover any particular domain completely. Hence, retrieval methods cannot be based on classes only and computational constraints do not necessarily apply as the retrieval process is expected to run only once at the outset of the analysis phase. It is also important to assume that the retrieval in this context is targeting multiple ontologies describing multiple but related domains. In this paper, we deduce that avoiding structural based retrieval mechanisms in fact benefits to the requirement models. Instead, we formulate a new retrieval method based on the PageRank algorithm that takes into account the indirect influences of various concepts within plausible supporting ontologies. This paper provides an empirical analysis that evidences the strength of our retrieval algorithm in supporting the identification of ontologies to support requirement analysis.