Bridging Concrete and Abstract Syntax of Web Rule Languages

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.

Web Ontology Language (OWL), Semantic Web Rule Language (SWRL) and Model-Driven Engineering (MDE) are technologies being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far stressed this problem and have proposed several solutions. The result of these efforts is the recent OMG’s initiative for defining an ontology development platform. However, the problem of transformation between Semantic Web ontology and rule languages and MDE-based languages has been solved using rather partial and ad hoc solutions, most often by XSLT. In this paper, we relations between the Semantic Web languages and MDE-compliant languages as separate technical spaces. In order to achieve a synergy between these technical spaces, we present ontology and rule languages in terms of MDE standards, recognize relations between the OWL and SWRL langauges and MDE-based ontology languages, and propose mapping techniques. In order to illustrate the approach, we use an MDE-defined architecture that includes the ontology and rule metamodels and ontology UML Profile. We also show how MDE techniques, such as model transformations, can be used to enable sharing rules and ontologies by using REWERSE Rule Markup Language (R2ML), a proposal for a general rule language. The main benefit of this approach is that it keeps the focus on the language concepts (i.e., languages’ abstract syntax - metamodels) rather than on technical issues caused by different concrete syntax. Yet, we also provide transformations that bridge between both languages’ concrete (XML) and abstract (MOF) syntax.

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.

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

Model transformations are among the key concepts of model-driven engineering (MDE), and dedicated model transformation languages (MTLs) emerged with the popularity of the MDE pssaradigm about 15 to 20 years ago. MTLs claim to increase the ease of development of model transformations by abstracting from recurring transformation aspects and hiding complex semantics behind a simple and intuitive syntax. Nonetheless, MTLs are rarely adopted in practice, there is still no empirical evidence for the claim of easier development, and the argument of abstraction deserves a fresh look in the light of modern general purpose languages (GPLs) which have undergone a significant evolution in the last two decades. In this paper, we report about a study in which we compare the complexity and size of model transformations written in three different languages, namely (i) the Atlas Transformation Language (ATL), (ii) Java SE5 (2004–2009), and (iii) Java SE14 (2020); the Java transformations are derived from an ATL specification using a translation schema we developed for our study. In a nutshell, we found that some of the new features in Java SE14 compared to Java SE5 help to significantly reduce the complexity of transformations written in Java by as much as 45%. At the same time, however, the relative amount of complexity that stems from aspects that ATL can hide from the developer, which is about 40% of the total complexity, stays about the same. Furthermore we discovered that while transformation code in Java SE14 requires up to 25% less lines of code, the number of words written in both versions stays about the same. And while the written number of words stays about the same their distribution throughout the code changes significantly. Based on these results, we discuss the concrete advancements in newer Java versions. We also discuss to which extent new language advancements justify writing transformations in a general purpose language rather than a dedicated transformation language. We further indicate potential avenues for future research on the comparison of MTLs and GPLs in a model transformation context.

Ontology-based service product configuration system modeling and development

Formal Concept Analysis (FCA) has been widely applied in many fields recently. In this paper, we introduce how a domain ontology can be constructed based on FCA. The consequential ontology constructed in this way is graphically represented as a concept lattice. After constructing FCA-based ontologies, it is necessary to represent the FCAbased ontologies in a formalism for sharing and reasoning. Semantic Web Rule Language(SWRL), a W3C proposal, is an extension with Horn clause rules on OWL. We represent the FCA-based ontologies in SWRL with some extension, which can be more suitable for reasoning.

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.

Model-Driven Development (MDD) aims at developing software more productively by using models as the main artifacts. Here, the models with high abstraction levels must be transformed into lower levels and finally executable models, i.e., source code. As a result, model transformation languages/tools play a main role on realizing the MDD goal. The Object-Management Group (OMG) presented the Query/View/Transformation (QVT) as a standard for the Meta-Object Facility (MOF)-based model transformation languages.However, implementing a model transformation language, which supports the full features of the QVT proposal requires a formal model of the underlying concepts. Having common terminology and a formal, precise, and consistent specification facilitates developing dependable transformation languages/tools.This paper aims to provide a formal specification of the main characteristics of a QVT-Relations (QVTr) model transformation language using the Z notation. The proposed formal model can be adapted for formalizing other domain and language concepts too. To show the applicability of the proposed formalism, a simplified version of the classic object-relational transformation is specified. Additionally, we show how the semantics clarifies some outstanding semantic issues in QVTr. The proposed formalism of this paper will pave the way to building support tools for model transformations in a unified manner in MDD.

Type 2 diabetes is a chronic and progressive disease with a large number of management strategies and treatment options. Doctors face a problem to concern many patients with different disease factors and many anti-diabetics drugs options to prescript treatment. Various researches have been considered the treatment of type 2 diabetes, but the individualization of the treatment that effectively control diabetes and avoids its complication has not been considered. In this paper, we present IRS-T2D, a recommendation system for individualizing the treatment of type 2 diabetes that utilized ontology and SWRL. The official documents management of type 2 diabetes were used as criteria and adapted to build ontologies. Thus, we built two OWL ontologies one for patient profiles and one for anti-diabetic drugs. The medication constraints were represented by Semantic Web Rule Language (SWRL). Finally, OWL/SWRL knowledge base is transformed to Jess reasoning engine format to build the IRS-T2D system.

Mereotopological assembly joint information representation for collaborative product design

Privacy preservation in a data-sharing computing environment is becoming a challenging problem. A purpose is defined as the intention of data accesses or usages and purpose-based access control (PBAC) has been proposed to extend traditional models for privacy-preserving. However, in existing research, the purpose is often to bind to data by using labeling schemes or building privacy metadata databases separately, which leads to redundancy of data tables and decreasing of query efficiency. Moreover, privacy policies involving purpose lack sufficient semantics. In this paper, we present a semantic model for the role-involved conditional purpose-based access control (RCPBAC) with ontology. Purpose, data, and role are represented by ontology and their relationships are described with object or data properties, which is based on Web Ontology Language (OWL). We use Semantic Web Rule Language (SWRL) to represent privacy policies for reasoning. This model can help data providers to define and share their own information more easily and securely.

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

Model transformation (MT) of very large models (VLMs), with millions of elements, is a challenging cornerstone for applying Model-Driven Engineering (MDE) technology in industry. Recent research efforts that tackle this problem have been directed at distributing MT on the Cloud, either directly, by managing clusters explicitly, or indirectly, via external NoSQL data stores. In this paper, we draw attention back to improving efficiency of model transformations that use EMF natively and that run on non-distributed environments, showing that substantial performance gains can still be reaped on that ground. We present Yet Another Model Transformation Language (YAMTL), a new internal domain-specific language (DSL) of Xtend for defining declarative MT, and its execution engine. The part of the DSL for defining MT is similar to ATL in terms of expressiveness, including support for advanced modelling contructs, such as multiple rule inheritance and module composition. In addition, YAMTL provides support for specifying execution control strategies. We experimentally demonstrate that the presented transformation engine outperforms other representative MT engines by using the batch transformation component of the VIATRA CPS benchmark. The improvement is, at least, one order of magnitude over the up-to-now fastest solution in all of the assessed scenarios. The software artefacts accompanying this work have been approved by the artefact evaluation committee and are available at http://remodd.org/node/585.