Sharing Ontologies and Rules Using Model Transformations

This paper presents a solution to bridging the abstract and concrete syntax of a Web rule languages by using model transformations. Current specifications of Web rule languages such as Semantic Web Rule Language (SWRL) or RuleML define their abstract syntax (e.g., metamodel) and concrete syntax (e.g., XML schema) separately. Although the recent research in the area of Model-Driven Engineering (MDE) demonstrates that such a separation of two types of syntax is a good practice (due to the complexity of languages), one should also have tools that check validity of rules written in a concrete syntax with respect to the abstract syntax of the rule language. In this study, we use the REWERSE I1 Rule Markup Language (R2ML), SWRL, and Object Constraint Language (OCL), whose abstract syntax is defined by using metamodeling, while their textual concrete syntax is defined by using either XML/RDF schema or Extended Backus-Naur Form (EBNF) syntax. We bridge this gap by a bi-directional transformation defined in a model transformation language (ATLAS Transformation Language, ATL). This transformation allowed us to discover a number of issues in both web rule language metamodels and their corresponding concrete syntax, and thus make them fully compatible. This solution also enables for sharing web rules between different web rule languages.

Purpose This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.Design/methodology/approach The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.Findings Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.Originality/value An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

Ontology-based service product configuration system modeling and development

An article tries to see a group of semantic web representation and communication means like description logics, semantic networks, RDF model and language, OWL language, RDF CFL etc. taking a part at the development of formal ontologies from a slightly higher (meta) level. A focus has been oriented towards properties that semantic web language ought to have to fulfill according to a semantic web idea. Consequently the article tries to draw by the help of the means above the trip towards a proper semantic-web ontology language fulfilling the main demands of expressivity and also easy-to-use conditions. Even if the development of a semantic web language was until now much more complicated with a taking part of a lot of people or companies the authors of the article try to contribute to an analyzing of the actual state by drawing it as a cloud of demands, streams, events or condition’s fulfilling that at the end would have brought into the world an easy-to-usable semantic web ontology language having all the demands fulfilled. The article moreover shows that a language RDF CFL belongs nowadays to the semantic web family as a unique well usable tool of reasoning within semantic web knowledge bases.

Semantic web reasoners and languages enable the semantic web to function. Some of the latest reasoning models developed in the last few years are: DLP, FaCT, RACER, Pellet, MSPASS, CEL, Cerebra Engine, QuOnto, KAON2, HermiT and others. Some software tools such as Protege, Jena and others also have been developed, which provide inferencing as well as ontology development and management environments. These reasoners usually differ in their inference procedures, supporting logic, completeness of reasoning, expressiveness and implementation languages. Various semantic web languages with increasing expressive power continue to be developed for describing web services. We survey the some of the more recent languages like OWL-S (Ontology Web Language-Schema), WSML (Web Service Modeling Language), SWRL (Semantic Web Rule Language) and others that have been tested in early use. We also survey semantic web reasoners and their relationship to these languages.

This paper proposes a solution for bridging abstract and concrete syntax of a Web rule language by using model transformations. Current specifications of Web rule languages such as Semantic Web Rule Language (SWRL) define its abstract syntax (e.g., EBNF notation) and concrete syntax (e.g., XML schema) separately. Although the recent research in the area of Model-Driven Engineering demonstrates that such a separation of two types of syntax is a good practice (due to the complexity of languages), one should also have tools that check validity of rules written in a concrete syntax with respect to the abstract syntax of the rule language. In this study, we use analyze the REWERSE I1 Rule Markup Language (R2ML) whose abstract syntax is defined by using metamodeling, while its textual concrete syntax is defined by using XML schema. We bridge this gap by a bi-directional transformation defined in a model transformation language (i.e., ATL).

Current standard models have improved interoperability in Product Lifecycle Management. But the increase of constrains surrounding information management in an industrial context, and notably for power plant design, like the increase of data, actors, systems and the need of automation and collaboration leads to an increasing use of ontology-based models. However, the design of power plants presents a specific issue, which is rules expression and validation. This need of rules is generated by safety, interoperability or collaboration constrains. The Semantic Web Rule Language (SWRL) is an ontological language based on OWL-DL that allows in addition rules expression. This paper presents SWRL rules and their industrial applications but also limits of this language in PLM applications. It proposes in consequence other rules languages.

A chronic disease dietary consultation system using OWL-based ontologies and semantic rules

This paper proposes a framework for building product information model (PIM) and product rule model (PRM), and integrated reasoning based on Description Frame Logic (DFL) [1] for collaborative product engineering environments. Most of the previous research has focused either on building ontology for PIM or on building a rule base for PRM respectively, not on both of them. Some research on product engineering has tried to build both ontology language and rule-language. But, the research is/has been limited to using both languages in a homogeneous approach under open world assumption (OWA) such as Web Ontology Language (OWL)/Semantic Web Rule Language (SWRL), which has some drawbacks to accommodate the requirements of enhanced expressivity for collaborative product engineering. We adopt Description Frame Logic (DFL) framework to integrate product semantics in PIM and engineering-specific knowledge in PRM based on description logic (DL) and logic programming (LP) under both open world assumption (OWA) and closed world assumption (CWA). This enables to secure seamless and interactive reasoning between PIM and PRM. We also include rule-expressions and constraint checking with DL for PIM while we include DL-expression in rules and LP’s non-logical features for PRM. This provides enhancement of expressiveness required for product engineering. Additionally, we show the benefits of the proposed framework with a case study.

Ontology is a formal specification of knowledge by a set of concepts with in a domain and their semantic relationship. Different Ontologies are devolved by developer for a same domain differently. Furthermore, ontology tools using different language. Ontology merging in semantic web is used to resolve the heterogeneity problem among the source ontology. The language level and ontology level mismatches are the heterogeneity problem in the ontology merging. Lexical matching strategies resolve the syntax based on Jaro distance. The word net is a lexical database with synset which solve the problem of semantic mismatches. A knowledge base is constructed by using Semantic Web Rule Language (SWRL) for ontology level mismatches. A merging framework identifies the similarities and dissimilarities of source ontologies are merged to resolve the heterogeneity problem. Keywords: Ontology, Heterogeneity problem, word net, Lexical, Semantic, SWRL

Objectives: This study presents the design and development of an AI-driven platform using natural language processing tools for personalized nutritional assessment namely NutriNLP, and a Telegram chatbot designed for the healthy menu recommendations. Method: This platform employs a Pellet-based nutritional ontology and Semantic Web Rule Language (SWRL) to provide weekly food menu suggestions based on user input, including weight, height, age, gender, activity level, and allergies. The chatbot were developed using the Methontology and Agile methodologies to generate personalized diet plans, and validated by nutritionists and respondents. Results: Results show the effectiveness of these systems in leveraging extensive nutritional databases and personalized algorithms to provide accurate and actionable dietary advice. According to the findings, nutritionists' acceptance is 70% while the general users' acceptance is 86.67% which indicates a moderate acceptance level and possibility for improvement, especially in system performance. Conclusions: The development of the NutriNLP chatbot marks a significant step forward in making personalized dietary recommendations accessible to the wider community. Its ability to calculate and classify food recommendations based on BMI, BMR, activity levels, and allergies demonstrates the practical benefits of combining artificial intelligence with semantic web technologies. Research Implications: These advancements highlight the transformative potential of AI in enhancing Sustainable Development Goals (SDGs), including SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-Being), and SDG 12 (Responsible Consumption and Production). Originality/Value: The developed chatbot extracts the effective personalized nutritional assessment called NutriNLP which is designed to assist families in identifying, addressing nutritional problems and improving dietary habits.

An NLP-guided ontology development and refinement approach to represent and query visual information

Lack of objective design change analysis model is a major problem for the accurate change impact prediction. To solve this problem, this paper proposes an ontology-based model named design change analysis model to organize the unstructured design properties as a basis for design change management. Design change analysis model is constructed by formalizing the mechanical design specifications in the form of design property network. Benefiting from the fine-grained organization, design change analysis model ensures the objectivity and accuracy of design change impact assessment. Since design change analysis model satisfies the attributions of small-world network, the change impact assessment should focus on more meaningful aspects including the linkage weight, node degree, and long-chain linkages of design change analysis model. With design change analysis model, the changeability of each design property which provides a quantified change propagation measurement could be evaluated. Additionally, different components could be distinguished in design change analysis model by using clustering algorithms without specializing them in advance. Design change analysis model modeled in web ontology language is a semantic enrichment model. It supports the semantic design change management due to the mathematic logic-based semantics of web ontology language and semantic web rule language. These lays a basis for updating changes among heterogeneous product development systems, and acquiring feasible change impacted properties.

As the complexity and tempo of world events increase, Command and Control (C2) systems must move to a new paradigm that supports the ability to dynamically modify system behavior in complex, changing environments. Historically, the behavior of Department of Defense (DoD) C2 systems has been embedded in executable code, providing static functionality that is difficult to change. We propose the use of semantic models to represent system behaviors abstracted from procedural code, and we demonstrate that this provides a well-defined foundation for dynamic Service Oriented Architectures. This paper describes an implementation that models a military convoy traveling through an unsecured area under changing conditions. The W3C standard Web Ontology Language (OWL) was used to describe the battlespace domain, and the proposed W3C Semantic Web Rule Language (SWRL) was used to capture recommended operating procedures for convoys in theater. In our experiment, two sets of rules were used: one set models rules of engagement for favorable visibility conditions on the battlefield, and the other models rules of engagement for poor visibility conditions. Ontologies and rule sets were translated into integrated knowledge bases that could be consulted as a service to derive alerts and recommendations for the convoy commander. Messages injected over an enterprise service bus (ESB) provide the changing conditions that affect the battlespace. We then were able to show that a dynamic event, such as an unexpected sandstorm, causes the appropriate set of rules of engagement grounded in the ontologies to be applied to the service to guide the convoy to safety. This paper describes the overall approach and the challenges we encountered. We outline the architectural options for constructing dynamic services and describe the semantic-based approach selected. We conclude with our findings and recommendations, including a set of requirements for a standard rule language needed to support agile services.

In reservoir engineering domain experts deal with many tasks and operations, ranging from reservoir simulation to well maintenance scheduling, with the goal of maximizing oil production. These operations involve different applications, and generate a large number of events at the time of their execution. Understanding these events and the relationships among them can aid the domain experts in decision making. The task of aggregating and analyzing the event information that is generated by different applications can be difficult and time consuming. In this paper, we discuss our approach on modeling events in reservoir engineering using Semantic Web techniques. We create an extensible event ontology using the Web Ontology Language (OWL) to model events in reservoir engineering. Event relationships are encoded using the Semantic Web Rule Language (SWRL). The work presented in this paper is an initial step towards a vision of integrated field event management, that uses semantic web technologies to create an efficient platform for event analysis.