Quality model and metrics of ontology for semantic descriptions of web services

Zhu, Hong; Liu, Dongmei; Bayley, Ian; Aldea, Arantza; Yang, Yusi; Chen, Ying

doi:10.23919/tst.2017.7914198

Cited by 25 publications

(45 citation statements)

References 21 publications

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“…Quality model and metrics of ontology for semantic descriptions of web services [ 9] Zhu, et al, discussed a web service called ASWebService that supports their own set of ontology metrics grouped into a set of aspects - Content, Presentation, Usage. The evaluation utilized the metrics to compare an ontology with a gold standard ontology to measure each quality attribute from their metrics.…”

Section: Introductionmentioning

confidence: 99%

Architecture and usability of OntoKeeper, an ontology evaluation tool

Amith

Manion

Liang

et al. 2019

BMC Med Inform Decis Mak

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Background The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers. Method We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment. Results In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research. Conclusion To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.

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Section: Introductionmentioning

confidence: 99%

Architecture and usability of OntoKeeper, an ontology evaluation tool

Amith

Manion

Liang

et al. 2019

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

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“…Quality measurement frameworks by various researchers like Semantic Web Application Quality Evaluation (SWAQ), which includes the fuzzy logic for evaluating SW applications' quality attributes, are proposed in [28]. Similarly, Zhu et al [29] proposed some performance parameters to evaluate the developed ontology for the application domain by choosing the respective Golden Standard (GS) ontology. A novel iterative framework like RiMOM-Instance Matching (RiMOM-IM) helps to match instances in the ontology by discovering the corresponding examples in the knowledge base [30].…”

Section: Literature Reviewmentioning

confidence: 99%

Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

Velu¹,

Thangavelu²

2022

Computers, Materials &Amp; Continua

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The drastic growth of coastal observation sensors results in copious data that provide weather information. The intricacies in sensor-generated big data are heterogeneity and interpretation, driving high-end Information Retrieval (IR) systems. The Semantic Web (SW) can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval. This paper focuses on exploiting the SW base system to provide interoperability through ontologies by combining the data concepts with ontology classes. This paper presents a 4-phase weather data model: data processing, ontology creation, SW processing, and query engine. The developed Oceanographic Weather Ontology helps to enhance data analysis, discovery, IR, and decision making. In addition to that, it also evaluates the developed ontology with other state-of-the-art ontologies. The proposed ontology's quality has improved by 39.28% in terms of completeness, and structural complexity has decreased by 45.29%, 11% and 37.7% in Precision and Accuracy. Indian Meteorological Satellite INSAT-3D's ocean data is a typical example of testing the proposed model. The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.

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“…OntoMetric [44] OntoQA Measure definitions [43] An online tool for evaluating the internal ontology quality YES Internal Quality OOP [30] ontology theories in [50] OQuaRE [40] is a framework for evaluating the quality of ontologies that has been constructed based upon the SQuaRE standard [37]. Mainly, the OQuaRE provides a quality model which comprises the same set of quality characteristics defined in the SQuaRE standard such as reliability, operability, maintainability, compatibility, transferability and functional adequacy.…”

Section: Yes Internal Qualitymentioning

confidence: 99%

Towards a Usable Ontology: The Identification of Quality Characteristics for an Ontology-Driven Decision Support System

et al. 2022

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Achieving quality in use (i.e., the higher-level quality objectives) is now widely accepted for building a usable system and software product. However, ontology engineering is a discipline for which the quality theories are not yet well developed and adapted and thus, ontology engineering still does not have an agreed methodology and standards for ontology evaluation. As a result, an ontology-driven system may consist of a badly engineered ontology that is not usable. This will in turn cause an adverse effect on the quality in use of the corresponding system. It is necessary to alleviate this problem by formulating an evaluation methodology and standards towards producing a usable ontology particularly targeting an ontology-driven system. It is evident through the literature as well as our practical experience through an agricultural ontology-driven Decision Support System (DSS) that quality in use of the system is tightly coupled with the quality of the ontology. As the first step towards this, we explored the well-established quality theories in system and software engineering to adapt and enhance the quality concepts defined so far in the ontology engineering domain. In the light of this study, we devised an ontology quality approach that guides developers to produce ontologies by avoiding quality issues to make ontology-driven DSSs usable. The proposed approach was exemplified using a use case from the agriculture domain. This research could be a foundation to inspire and assist ontology engineers to rethink about ontology quality from a broader view in developing a usable ontology.

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Quality model and metrics of ontology for semantic descriptions of web services

Cited by 25 publications

References 21 publications

Architecture and usability of OntoKeeper, an ontology evaluation tool

Architecture and usability of OntoKeeper, an ontology evaluation tool

Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

Towards a Usable Ontology: The Identification of Quality Characteristics for an Ontology-Driven Decision Support System

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