An Ontology-based Approach for Sharing, Integrating, and Retrieving Architectural Knowledge

Roldán, María Luciana; Gonnet, Silvio; Leone, Horacio Pascual

doi:10.1016/j.entcs.2018.06.004

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Artificial Intelligence [35], [26], [33], [18], [8], [27], [25], [28], [11], [17], [30], [3] 12 35.29% Documentation Model [42], [38], [13], [21], [37], [45] 6 17.65%…”

Section: Papers Count Percentagementioning

confidence: 99%

“…Development Tools [17], [30], [3], [45], [16], [36], [4], [50] By crossing the results of the approaches (X-axis) and the artefacts (Y-axis) linked in the bubble diagram presented in Figure 5, we can make interesting observations regarding the relationship between the different categories. For example, the number of works that develop System Tools are more focused on Developer Tools than on Requirements.…”

Section: Artifactmentioning

confidence: 99%

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Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

Hyun,

Hurtado

2023

Foundations of Computing and Decision Sciences

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The definition of architecture is a crucial task in software development, where the architect is responsible for making the right decisions to meet specific functional and quality requirements. These architectural design decisions form the foundation that shapes the arrangement of elements within a system. Unfortunately, these decisions are often poorly documented, implicit in various artifacts, or inadequately updated, leading to negative consequences on the maintainability of a system and resulting in rework and cost overruns. The objective of this systematic mapping study is to comprehend the current state regarding approaches for traceability of architectural design decisions and how these decisions are linked with the different artifacts used in software development. To achieve this, an information extraction protocol is followed, utilizing databases with search strings, inclusion, and exclusion criteria. The findings demonstrate that this knowledge is highly relevant; however, it is rarely explicitly documented. As a result, most works propose diverse approaches to extract this knowledge from existing technical documentation, commonly used tools, and other sources of product and process information. In contrast, it is evident that there is no standard for documenting design decisions, leading each author to present a subjective version of what is important and where to trace these decisions. This suggests that there is still a significant amount of research to be conducted regarding the traceability of these architectural design decisions and their connection with software artifacts. Such research could lead to intriguing new proposals for investigation.

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“…Artificial Intelligence [35], [26], [33], [18], [8], [27], [25], [28], [11], [17], [30], [3] 12 35.29% Documentation Model [42], [38], [13], [21], [37], [45] 6 17.65%…”

Section: Papers Count Percentagementioning

confidence: 99%

Section: Artifactmentioning

confidence: 99%

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

Hyun,

Hurtado

2023

Foundations of Computing and Decision Sciences

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“…Knowledge representation is responsible for managing the exchange of knowledge sources into a form that the computer can understand. One of the knowledge representation techniques, ontology, is used in various application domains by facilitating a common understanding of the information structures [17]. Apart from that, ontologies should play a direct role in knowledge sharing activities and represent the knowledge in a specific domain [18], [19], as study shows that ontology can support all knowledge management processes [20], [21].…”

Section: Introductionmentioning

confidence: 99%

Ontology-Based Knowledge Management Tools for Knowledge Sharing in Organization—A Review

2022

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Knowledge management (KM) comprises several processes, and one of the most important is the knowledge sharing activities. The ability of an organization to manage its organizational knowledge, specifically in the context of knowledge sharing, may enhance the organization's overall performance. Various approaches and technologies have been introduced to assist the process in achieving that target. Ontology as one of the knowledge representation methods has been becoming popular to assist knowledge sharing in the organization. Previous reviews have mainly focused on general KM issues, with little emphasis on the use of ontology in knowledge sharing. Thus, this article presents a review of several ontology-based KM tools that can support knowledge-sharing activities to provide some insight into future research in this area. Thirteen ontology-based KM tools were reviewed using ten elements' comparison criteria: the motivation, domain, source of knowledge, type of knowledge, knowledge extraction, knowledge input process, knowledge retrieval process, knowledge sharing technology, source of ontology component, and ontology methodology. The review found that several elements can be further studied to improve KM implementation in the organization, especially on the knowledge sharing dimension. This includes simplifying the knowledge extraction and retrieval process to explore a diverse range of knowledge domains from implicit knowledge sources. The review's outcome also includes proposed components and functions of an ideal ontology-based KM tool.

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Ontology-based systems engineering: A state-of-the-art review

Yang

Cormican

2019

Computers in Industry

111

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An Ontology-based Approach for Sharing, Integrating, and Retrieving Architectural Knowledge

Cited by 5 publications

References 15 publications

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

Ontology-Based Knowledge Management Tools for Knowledge Sharing in Organization—A Review

Ontology-based systems engineering: A state-of-the-art review

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