Development and Evaluation of a Software Requirements Ontology

Tan, He; Ismail, Muhammad; Tarasov, Vladimir; Adlemo, Anders; Johansson, Mats

doi:10.5220/0006079300110018

Cited by 12 publications

(16 citation statements)

References 20 publications

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“…From literature, some ontologies are designed by combining the activities of two methods such as Methontology, Gruninger and Fox methodologies [68,69,70].…”

Section: Literature Review: Ontology Development Methodologymentioning

confidence: 99%

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

Aminu¹,

Oyefolahan²,

Abdullahi³

et al. 2020

IJIEEB

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The success of machine represented web known as semantic web largely hinges on ontologies. Ontology is a data modeling technique for structured data repository premised on collection of concepts with their semantic relationships and constraints on domain. There are existing methodologies to aid ontology development process. However, there is no single correct ontology design methodology. Therefore, this paper aims to present a review on existing ontology development approaches for different domains with the goal of identifying individual methodology's weakness and suggests for hybridization in order to strengthen ontology development in terms of its content and constructions correctness. The analysis and comparison of the review were carried out by considering these criteria but not limited to: activities of each method, the initial domain of the methodology, ontology created from scratch or reuse, frequently used ontology management tools based on literature, subject granularity, and usage across different platforms. This review based on the literature showed some approaches that exhibit the required principles of ontology engineering in tandem with software development principles. Nonetheless, the review still noted some gaps among the methodologies that when bridged or hybridized a better correctness of ontology development would be achieved in building intelligent system.

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“…From literature, some ontologies are designed by combining the activities of two methods such as Methontology, Gruninger and Fox methodologies [68,69,70].…”

Section: Literature Review: Ontology Development Methodologymentioning

confidence: 99%

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

Aminu¹,

Oyefolahan²,

Abdullahi³

et al. 2020

IJIEEB

View full text Add to dashboard Cite

show abstract

“…One of the industrial cases was provided by the participating company, Saab Avionics and originated from the avionics domain. A software requirements ontology was developed representing the requirements of a software component pertaining to an embedded system located in an airplane [22]. The developed ontology includes three specific pieces of knowledge: (1) a meta model of the software requirements, (2) the domain knowledge of the application, e.g.…”

Section: Ostagmentioning

confidence: 99%

Ontology Development Strategies in Industrial Contexts

Tarasov

Seigerroth

Sandkuhl

2019

Business Information Systems Workshops

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Knowledge-based systems are used extensively to support functioning of enterprises. Such systems need to reflect the aligned business-IT view and create shared understanding of the domain. Ontologies are used as part of many knowledge-bases systems. The industrial context affects the process of ontology engineering in terms of business requirements and technical constraints. This paper presents a study of four industrial cases that included ontology development. The study resulted in identification of seven factors that were used to compare the industrial cases. The most influential factors were found to be reuse of ontologies/models, stakeholder groups involved, and level of applicability of ontology. Finally, four recommendation were formulated for projects intended to create shared understanding in an enterprise.

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“…In Figure 2, the rectangles represent the concepts of the ontology; the round rectangles represent the individuals; and the dashed rectangles provide the data values of datatype property for individuals. More details about the ontology can be found in [16].…”

Section: Representation Of Requirements With Requirements Specificatimentioning

confidence: 99%

Application of Inference Rules to a Software Requirements Ontology to Generate Software Test Cases

Tarasov

Tan

Ismail

et al. 2017

Lecture Notes in Computer Science

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Abstract. Testing of a software system is resource-consuming activity. One of the promising ways to improve the efficiency of the software testing process is to use ontologies for testing. This paper presents an approach to test case generation based on the use of an ontology and inference rules. The ontology represents requirements from a software requirements specification, and additional knowledge about components of the software system under development. The inference rules describe strategies for deriving test cases from the ontology. The inference rules are constructed based on the examination of the existing test documentation and acquisition of knowledge from experienced software testers. The inference rules are implemented in Prolog and applied to the ontology that is translated from OWL functional-style syntax to Prolog syntax. The first experiments with the implementation showed that it was possible to generate test cases with the same level of detail as the existing, manually produced, test cases.

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Development and Evaluation of a Software Requirements Ontology

Cited by 12 publications

References 20 publications

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

Ontology Development Strategies in Industrial Contexts

Application of Inference Rules to a Software Requirements Ontology to Generate Software Test Cases

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