Ranking the ontology development methodologies using the weighted decision matrix

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
P. K. Sinha, Biswanath Dutta, Udaya Varadarajan
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引用次数: 0

Abstract

PurposeThe current work provides a framework for the ranking of ontology development methodologies (ODMs).Design/methodology/approachThe framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.FindingsState-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.Originality/valueThere is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.
使用加权决策矩阵对本体开发方法进行排序
目的本研究为本体开发方法(odm)的排序提供了一个框架。设计/方法/方法该框架是一种循序渐进的方法,由一系列排名特征和量化工具加权决策矩阵加强。一项广泛的文献调查揭示了调节odm的一系列方面。方面和现有的最先进的估计有助于提取特征。为了确定每个特征的权重,我们实施了一项在线调查,以确保来自语义Web社区的证据。为了演示该框架,作者进行了一项试点研究,其中使用了2000-2019年报告的一系列领域odm。最新的研究表明,已经积累、调查和评估了ODM,以规定本体开发的最佳ODM。但是,没有一项主流研究提供odm的排名机制。推荐的框架克服了这一限制,并提供了对odm进行排序的系统和统一的方法。初步研究表明,NeOn是近二十年来排名第一的ODM。原创性/价值文献中没有研究odm排名的工作。因此,这是ODM研究领域的首次此类工作。该框架支持从具有大量本体开发功能的文献中识别最顶级的odm。它还支持为本体开发选择最好的ODM。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data Technologies and Applications
Data Technologies and Applications Social Sciences-Library and Information Sciences
CiteScore
3.80
自引率
6.20%
发文量
29
期刊介绍: Previously published as: Program Online from: 2018 Subject Area: Information & Knowledge Management, Library Studies
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