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In e-government domain, an efficient semantic interoperability of services is a big challenge. In this context, semantic technologies play a fundamental role in numerous e-government programs. Indeed, these technologies enable enriching the public service description provided by different public administrations with additional semantic information, which allows automatic services processing and information exchange between involved members in comprehensive and interpretable manner, thus facilitating service integration and cooperation. The most frequently used technologies in this area are semantic web services (SWS) technology and ontology. Thus, for modelling efficiently public services, the authors have exploring, studying and analyzing some of e-government researches and projects that applied semantic technologies.

In this paper, the authors address how semantic technologies transform the e-government domain through exploring and studying the use of SWS and ontology in numerous researches and projects applying these technologies in this area. Then, the authors have compared them through a set of criteria defined according to e-government requirements such as the SWS modelling approach for describing semantically public services, ontologies for representing governmental specific features (e.g. regulation and organizational structures) and developed portal for supporting user ' s perspectives. Based on this study, the authors have identified the appropriate standards, frameworks, and models for developing the framework.

The authors have developed a framework for public services which enhances existing approaches with additional aspects. Thus, the approach comparing to other works improves the service ontology with a cognitive semantic approach to support the multiple usage contexts and situations of services. This semantic is developed in form of a Sit/Ctx ontology developed based on CSs model represented through conceptual graphs theory. The authors have used this model besides OWL-S, improving thus the level of automation of discovery and composition process of public services, which become more efficient with taken into consideration their interrelations and situations.

The approach comparing to other works improves the service ontology with a cognitive semantic approach to support the multiple usage contexts and situations of public services, providing thus the end-users (people and enterprises) a better orientation in discovery process.

XML Schema is used to define schema of XML documents that have become standards for data exchange in various Web-based information applications. The main problem of XML Schema is that it emphasizes syntax and format rather than semantics and knowledge representation. Hence, even though having the advantage of describing the structure and constraining the contents of XML documents, XML Schema lacks the computer-interpretability to support knowledge representation for existing information systems. The purpose of this study is to propose role-mapping annotations for XML Schema (RMAXS) to integrate Semantic Web with XML Schema, which allows the facilitation interoperability between adjoining layers of the Semantic Web stack.

The XML, XML Schema, ontology, and rule can be completely integrated into a multi-layered intelligent framework (MIF) for XML-based applications in the current web environment. This work presents a semantic-role-mapping intelligent system, called SRMIS, based on the MIF. SRMIS consists of XML-based document repository, search engine, inference engine and transformation engine, which provides different approaches to present the various metadata and knowledge representations.

The traditional Semantic Web stack has three gaps between adjoining layers. The first gap, between the XML and XML Schema layers can be bridged with an XMLSchema-instance mechanism. The third gap, between the ontology and rule layers can be connected by building rules on top of ontologies. This study proposes RMAXS to couple the second gap, between the XML schema and ontology layers. The proposed multi-layered intelligent framework (MIF) adopts these coupling technologies to facilitate interoperability between adjoining layers. Therefore, the XML, XML Schema, ontology, and rule can be completely integrated into the MIF for intelligent applications in the web environment.

To demonstrate the SRMIS applications, this work implements a prototype that helps researchers to find interested papers.

This work presents a semantic-role-mapping intelligent system, called SRMIS, based on the MIF. SRMIS consists of XML-based document repository, search engine, inference engine and transformation engine, which provides different approaches to present the various metadata and knowledge representations. The proposed SRMIS can be applied in various application domains.

Managing components' resources plays a critical role in the success of systems' architectures designed for cyber–physical systems (CPS). Performing the selection of candidate components to pursue a specific application's needs also involves identifying the relationships among architectural components, the network and the physical process, as the system characteristics and properties are related.

Using a Model-Driven Engineering (MDE) approach is a valuable asset therefore. Within this context, the authors present the so-called Systems Architecture Ontology (SAO), which allows the representation of a system architecture (SA), as well as the relationships, characteristics and properties of a CPS application.

SAO uses a common vocabulary inspired by the Architecture Analysis and Design Language (AADL) standard. To demonstrate SAO's applicability, this paper presents its use as an MDE approach combined with ontology-based modeling through the Ontology Web Language (OWL). From OWL models based on SAO, the authors propose a model transformation tool to extract data related to architectural modeling in AADL code, allowing the creation of a components' library and a property set model. Besides saving design time by automatically generating many lines of code, such code is less error-prone, that is, without inconsistencies.

To illustrate the proposal, the authors present a case study in the aerospace domain with the application of SAO and its transformation tool. As result, a library containing 74 components and a related set of properties are automatically generated to support architectural design and evaluation.

Institutional repositories (IR) are usually used to archive and manage digital collections including research results, educational material, etc. Learning management systems (LMS) form a popular basis for e-learning and blended learning. This paper aims to study how to integrate IR and LMS to support accessibility of disabled students and students with learning difficulties (dyslexic students) in higher education. Customised ontologies focusing on disabled students can be used to facilitate indexing, and access of items in the repository.

The authors propose a simple methodological approach to establish an integrating system for supporting accessibility. First, the authors review research works related to adaptive learning environments (ALEs) and blended learning, and discuss issues of the interoperability of IR and LMS. Then, based on the review, the authors discuss the use of an integrated ALE for supporting disabled students in the domain of higher technological education. The integrated system is based on IR, LMS and assistive and adaptive technology. The open source software platform DSpace is used to build up the repository applications Use of the web ontology language (OWL) ontologies is also proposed for indexing and accessing the various, heterogeneous items stored in the repository. Various open source LMS (e.g. openeclass) could be used to build up the integrated system. Finally, the authors describe experimentation with a prototype implemented to provide the mentioned capabilities.

The technology is mature enough for building up integrated systems, combining capabilities of IR and LMS, for supporting disabled students. The use of ontologies focused on disabled students could facilitate the use of such integrated systems. Customisation and operation of a platform, for the selection and use of portions of OWL ontologies, could be based on the open source software Protégé. Such a platform forms a basis to create an appropriate ontology suitable for specific domains, e.g. the domain of technological education. Finally, the authors argue that the combined use of the OWL platform and the DSpace repository with open source LMS platforms could support domain experts for creating customised ontologies and facilitating searching.

A new perception of the term integrated system for supporting disabled students in the higher education context is presented. This perception tries to combine the IR technology that supports the self-archiving approach of information, open LMS technology and the user-centred approach to support students and manage the “life of information”.

Web applications are subject to continuous changes and rapid evolution triggered by increasing competition, especially in commercial domains such as electronic commerce. Unfortunately, usually they are implemented without producing any useful documentation for subsequent maintenance and evolution. Thereof, the maintenance of such systems becomes a challenging problem as the complexity of the web application grows. Reverse engineering has been heralded as one of the most promising technologies to support effective web application maintenance. This paper aims to present a reverse engineering approach that helps understanding existing undocumented web applications to be maintained or evolved.

The proposed approach provides reverse engineering rules to generate a conceptual schema from a given domain ontology by using a set of transformation rules. The reverse engineering process consists of four phases: extracting useful information; identifying a set of ontological constructs representing the concepts of interest; enriching the identified set by additional constructs; and finally deriving a conceptual schema.

The advantage of using ontology for conceptual data modeling is the reusability of domain knowledge. As a result, the conceptual data model will be made faster, easier and with fewer errors than creating it in usual way. Designers can use the extracted conceptual schema to gain a better understanding of web applications and to assist in their maintenance.

The strong point of this approach is that it relies on a very rich semantic reference that is domain ontology. However, it is not possible to make a straightforward transformation of all elements from a domain ontology into a conceptual data model because ontology is semantically richer than data conceptual models.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

Nowadays, the use of WCMS (web content management systems) is widespread. The conversion of this infrastructure into its semantic equivalent (semantic WCMS) is a critical issue, as this enables the benefits of the semantic web to be extended. The purpose of this paper is to present a FLERSA (Flexible Range Semantic Annotation) for flexible range semantic annotation.

A FLERSA is presented as a user‐centred annotation tool for Web content expressed in natural language. The tool has been built in order to illustrate how a WCMS called Joomla! can be converted into its semantic equivalent.

The development of the tool shows that it is possible to build a semantic WCMS through a combination of semantic components and other resources such as ontologies and emergence technologies, including XML, RDF, RDFa and OWL.

The paper provides a starting‐point for further research in which the principles and techniques of the FLERSA tool can be applied to any WCMS.

The tool allows both manual and automatic semantic annotations, as well as providing enhanced search capabilities. For manual annotation, a new flexible range markup technique is used, based on the RDFa standard, to support the evolution of annotated Web documents more effectively than XPointer. For automatic annotation, a hybrid approach based on machine learning techniques (Vector‐Space Model + n‐grams) is used to determine the concepts that the content of a Web document deals with (from an ontology which provides a taxonomy), based on previous annotations that are used as a training corpus.

Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects.

In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies.

The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework.

The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

The purpose of this paper is to explore the feasibility that an ontological approach can be applied to formalize the construction regulation constraint knowledge in a computer-interpretable way, for construction quality checking, during construction stage.

The ontological and semantic web technologies are used to model the construction quality constraints knowledge into Axioms/OWL and SWRL rules. Protégé platform is selected to illustrate how the construction quality checking, based on the Axioms/OWL and SWRL rules, is achieved.

The ontology and semantic web technologies can be an alternative way for modeling the construction regulation constraints in a computer-interpretable way, and can be implemented for the regulation-based construction quality checking.

The approach is illustrated only with given specific technical constraints examples, the generality and practicality of the approach need further investigation.

The paper introduces an ontological and semantic approach to model and formalize the construction regulation constraints for construction quality checking, and proves the feasibility by the case studies. The proposed approach enables the regulations can be understood and retrieved semantically by computers, which facilitates the using of regulation codes.

The purpose of this paper is to present an ontology‐based approach of context‐sensitive computing for the optimization of flexible manufacturing systems (FMS).

A context‐sensitive computing approach is presented, integrated on top of FMS control platform. The approach addresses how to extract manufacturing contexts at source, how to process contextual entities by developing an ontology‐based context model and how to utilize this approach for real time decision making to optimize the key performance indicators (KPIs). A framework for such an optimization support system is proposed. A practical FMS use case within SOA‐based control architecture is considered as an illustrative example and the implementation of the core functionalities to the use case is reported.

Continuous improvement of the factory can be enhanced utilizing context‐sensitive support applications, which provides an intelligent interface for knowledge acquisition and elicitation. This can be used for improved data analysis and diagnostics, real time feedback control and support for optimization.

The performance of context‐sensitive computing increases with the extraction, modeling and reasoning of as much contexts as possible. However, more computational resources and processing times are associated to this. Hence, the trade‐off should be in between the extent of context processing and the required outcome of the support applications.

This paper includes the practical implications of context‐sensitive applications development in manufacturing, especially in the dynamic operating environment of FMS.

Reported results provide a modular approach of context‐sensitive computing and a practical use case implementation to achieve context awareness in FMS. The results are seen extendable to other manufacturing domains.