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The purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.

propose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.

The findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.

Limited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.

The SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

The SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

This work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.

The study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.

It was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.

This paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.

This systematic literature review (SLR) paper presents the overview and analysis of the existing ontologies application in the SE domain. It discusses the main challenges in terms of its ontologies development and highlights the key knowledge areas for subdomains in the SE domain that provides a direction to develop ontologies application for SE systematically. The SE is not as straightforward as the traditional economy. It transforms the existing economy ecosystem through peer-to-peer collaborations mediated by the technology. Hence, the complexity of the SE domain accentuates the need to make the SE domain knowledge more explicit.

For the review, the authors only focus on the journal articles published from 2010 to 2020 and mentioned ontology as a solution to overcome the issues specific for the SE domain. The initial identification process produced 3,326 papers from 10 different databases.

After applying the inclusion and exclusion criteria, a final set of 11 articles were then analyzed and classified. In SE, good ontology design and development is essential to manage digital platforms, deal with data heterogeneity and govern the interoperability of the SE systems. Yet the preference to build an application ontology, lack of perdurant design and minimal use of the existing standard for building SE common knowledge are deterring the ontology development in this domain. From this review, an anatomy of the SE key subdomain areas is visualized as a reference to further develop the domain ontology for the SE domain systematically.

With the arrival of the Fourth Industrial Revolution (4IR), the sharing economy (SE) has become one of the important domains whose impact has been explosive, and its domain knowledge is complex. Yet, a comprehensive overview and analysis of the ontology applications in the SE domain is not available or well presented to the research community.

The purpose of this paper is to review ontologies and data models currently in use for augmented reality (AR) applications, in the cultural heritage (CH) domain, specifically in an urban environment. The aim is to see the current trends in ontologies and data models used and investigate their applications in real world scenarios. Some special cases of applications or ontologies are also discussed, as being interesting enough to merit special consideration.

A search using Google Scholar, Scopus, ScienceDirect and IEEE Xplore was done in order to find articles that describe ontologies and data models in AR CH applications. The authors identified the articles that analyze the use of ontologies and/or data models, as well as articles that were deemed to be of special interest.

This review found that CIDOC-CRM is the most popular ontology closely followed by Historical Context Ontology (HiCO). Also, a combination of current ontologies seems to be the most complete way to fully describe a CH object or site. A layered ontology model is suggested, which can be expanded according to the specific project.

This study provides an overview of ontologies and data models for AR CH applications in urban environments. There are several ontologies currently in use in the CH domain, with none having been universally adopted, while new ontologies or extensions to existing ones are being created, in the attempt to fully describe a CH object or site. Also, this study suggests a combination of popular ontologies in a multi-layer model.

Selecting the optimal supplier is a challenging managerial decision that involves several dimensions that vary over time. Despite the considerable attention devoted to this issue, knowledge is required to be updated and analyzed in this field. This paper reveals new opportunities to advance supplier selection (SS) research from a multidimensional perspective. Moreover, this study aims to formalise SS knowledge to enable the appropriate selection of sustainable, resilient and circular criteria.

This study is developed in two stages: first, a systematic literature review is conducted to select relevant papers. Descriptive and thematic analyses are employed to analyze criteria, solving approaches and case studies. Second, a criterion knowledge-based framework is developed and validated by experts to be implemented as ontology using Protégé software.

Evaluating the viability of suppliers need further studies to integrate other criteria and to align SS objectives with research advancement. Artificial intelligence tools are needed to revolutionize and optimize the traditional techniques used to solve this problem. Literature lucks frameworks for specific sectors. The proposed ontology provides a consistent criteria knowledge base.

For academics, the results of this study highlight opportunities to improve the viable SS process. From a managerial perspective, the proposed ontology can assist managers in selecting the appropriate criteria. Future works can enrich the proposed ontology and integrate this knowledge base into an information system.

This study contributes to promoting knowledge about viable SS. Capitalizing the knowledge base of criteria in a computer-interpretable manner supports the digitalization of this critical decision.

The purpose of this paper is to formulate apposite criteria for ontology evaluation and test them through assessments of existing ontologies.

A literature review provided the basis from which to extract the categories relevant to an evaluation of internal ontology components. According to the ontology evaluation categories, a panel of experts provided the evaluation criteria for each category via Delphi survey. Reliability was gauged by applying the criteria to assessments of existing smartphone ontologies.

Existing research tends to approach ontology evaluation through comparison with well-engineered ontologies, implementation in target applications and appropriateness/interconnection appraisals in relation to raw data, but such methodologies fall short of shedding light on the internal workings of ontologies, such as structure, semantic representation and interoperability. This study adopts its evaluation categories from previous research while also collecting concrete evaluation criteria from an expert panel and verifying the reliability of the resulting 53 criteria.

This is the first published study to extract ontology evaluation criteria in terms of syntax, semantics and pragmatics. The results can be used as an evaluation index following ontology construction.

The purpose of this paper is to demonstrate the construction of a core ontology for food. To construct the core ontology, the authors propose here an approach called, yet another methodology for ontology plus (YAMO+). The goal is to exhibit the construction of a core ontology for a domain, which can be further extended and converted into application ontologies.

To motivate the construction of the core ontology for food, the authors have first articulated a set of application scenarios. The idea is that the constructed core ontology can be used to build application-specific ontologies for those scenarios. As part of the developmental approach to core ontology, the authors have proposed a methodology called YAMO+. It is designed following the theory of analytico-synthetic classification. YAMO+ is generic in nature and can be applied to build core ontologies for any domain.

Construction of a core ontology needs a thorough understanding of the domain and domain requirements. There are various challenges involved in constructing a core ontology as discussed in this paper. The proposed approach has proven to be sturdy enough to face the challenges that the construction of a core ontology poses. It is observed that core ontology is amenable to conversion to an application ontology.

The constructed core ontology for domain food can be readily used for developing application ontologies related to food. The proposed methodology YAMO+ can be applied to build core ontologies for any domain.

As per the knowledge, the proposed approach is the first attempt based on the study of the state of the art literature, in terms of, a formal approach to the design of a core ontology. Also, the constructed core ontology for food is the first one as there is no such ontology available on the web for domain food.

This study applies digital humanity tools (Gephi and Protégé) for establishing and visualizing ontologies in the cultural heritage domain. According to that, this study aims to develop a novel evaluation approach using five ontology indicators (data overview, visual presentation, highlight links, scalability and querying) to evaluate the knowledge structure presentation of cultural heritage ontology.

The researchers collected and organized 824 pieces of government’s open data (GOD), converted GOD into the resource description framework format, applied Protégé and Gephi to establish and visualize cultural heritage ontology. After ontology is built, this study recruited 60 ontology participants (30 from information and communications technology background; 30 from cultural heritage background) to operate this ontology and gather their different perspectives of visual ontology.

Based on the ontology participant’s feedback, this study discovered that Gephi is more supporting than Protégé when visualizing ontology. Especially in data overview, visual presentation and highlight links dimensions, which is supported visualization and demonstrated ontology class hierarchy and property relation, facilitated the wider application of ontology.

This study offers two contributions. First, the researchers analyzed data on East Asian architecture with novel digital humanities tools to visualize ontology for cultural heritage. Second, the study collected participant’s feedback regarding the visualized ontology to enhance its design, which can serve as a reference for future ontological development.

The purpose of this paper is to develop and apply an ontology-supported asset information integrator system (AIIS) in the domain of infrastructure management. The two objectives are: first, to describe how different ontologies developed as part of this research support the design of message templates (MTs) that were implemented in the AIIS; and second, to explain the development and application of the prototype system for tangible capital asset (TCA) reporting.

The proposed system was developed in the MS SharePoint platform using a four-step methodology: create a web site and library; review and modify MTs; design and configure workflows; and add functionalities.

First, the architecture, methodology, and evaluation of the two ontologies: Transaction Domain Ontology and Tangible Capital Asset Ontology, developed as part of this research work were briefly introduced to describe how both the ontologies supported the design of MTs that were implemented in the AIIS. Second, the AIIS was successfully developed and applied in the domain of infrastructure management for the Asset Inventory and Condition Assessment Reporting.

The development of the AIIS would enable industry experts to exchange the tangible capital information. The built-in search engine and history services would help the experts to search a transaction and track the transaction history. The real-time visualisation of the data would help in decision making.

Infrastructure agencies use diversified information systems to manage infrastructure systems. Due to propriety nature of the information systems, the TCA data generated is heterogeneous and inconsistent, which make it difficult to exchange with other organisations. Also, the existing applications focus on processing and managing the TCA data for a variety of tasks; however, lack to support data exchange with other organisations. This emphasises the gap that requires the development of an ontology-supported collaboration system in the domain of infrastructure asset management.