Rule Interchange Research Articles

Automated Expert System Knowledge Base Development Method for Information Security Risk Analysis

Information security risk analysis is a compulsory requirement both from the side of regulating documents and information security management decision making process. Some researchers propose using expert systems (ES) for process automation, but this approach requires the creation of a high-quality knowledge base. A knowledge base can be formed both from expert knowledge or information collected from other sources of information. The problem of such approach is that experts or good quality knowledge sources are expensive. In this paper we propose the problem solution by providing an automated ES knowledge base development method. The method proposed is novel since unlike other methods it does not integrate ontology directly but utilizes automated transformation of existing information security ontology elements into ES rules: The Web Ontology Rule Language (OWL RL) subset of ontology is segregated into Resource Description Framework (RDF) triplets, that are transformed into Rule Interchange Format (RIF); RIF rules are converted into Java Expert System Shell (JESS) knowledge base rules. The experiments performed have shown the principal method applicability. The created knowledge base was later verified by performing comparative risk analysis in a sample company.

Comprehensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines.

The over-use of antibiotics in clinical domains is causing an alarming increase in bacterial resistance, thus endangering their effectiveness as regards the treatment of highly recurring severe infectious diseases. Whilst Clinical Guidelines (CGs) focus on the correct prescription of antibiotics in a narrative form, Clinical Decision Support Systems (CDSS) operationalize the knowledge contained in CGs in the form of rules at the point of care. Despite the efforts made to computerize CGs, there is still a gap between CGs and the myriad of rule technologies (based on different logic formalisms) that are available to implement CDSSs in real clinical settings. To helpCDSS designers to determine the most suitable rule-based technology (medical-oriented rules, production rules and semantic web rules) with which to model knowledge from CGs for the prescription of antibiotics. We propose a framework of criteria for this purpose that is extensible to more generic CGs. Our proposal is based on the identification of core technical requirements extracted from both literature and the analysis of CGs for antibiotics, establishing three dimensions for analysis: language expressivity, interoperability and industrial aspects. We present a case study regarding the John Hopkins Hospital (JHH) Antibiotic Guidelines for Urinary Tract Infection (UTI), a highly recurring hospital acquired infection. We have adopted our framework of criteria in order to analyse and implement these CGs using various rule technologies: HL7 Arden Syntax, general-purpose Production Rules System (Drools), HL7 standard Rule Interchange Format (RIF), Semantic Web Rule Language (SWRL) and SParql Inference Notation (SPIN) rule extensions (implementing our own ontology for UTI). We have identified the main criteria required to attain a maintainable and cost-affordable computable knowledge representation for CGs. We have represented the JHH UTI CGs knowledge in a total of 12 Arden Syntax MLMs, 81 Drools rules and 154 ontology classes, properties and individuals. Our experiments confirm the relevance of the proposed set of criteria and show the level of compliance of the different rule technologies with the JHH UTI CGs knowledge representation. The proposed framework of criteria may help clinical institutions to select the most suitable rule technology for the representation of CGs in general, and for the antibiotic prescription domain in particular, depicting the main aspects that lead to Computer Interpretable Guidelines (CIGs), such as Logic expressivity (Open/Closed World Assumption, Negation-As-Failure), Temporal Reasoning and Interoperability with existing HIS and clinical workflow. Future work will focus on providing clinicians with suggestions regarding new potential steps for CGs, considering process mining approaches and CGs Process Workflows, the use of HL7 FHIR for HIS interoperability and the representation of Knowledge-as- a-Service (KaaS).

Authorization Conflict Problems in Combining RIF Rules with RDF Data

Resource Description Framework (RDF) access control suffers from an authorization conflict problem caused by RDF inference. When an access authorization is specified, it can lie in conflict with other access authorizations that have the opposite security sign as a result of RDF inference. In our former study, we analyzed the authorization conflict problem caused by subsumption inference, which is the key inference in RDF. The Rule Interchange Format (RIF) is a Web standard rule language recommended by W3C, and can be combined with RDF data. Therefore, as in RDF inference, an authorization conflict can be caused by RIF inference. In addition, this authorization conflict can arise as a result of the interaction of RIF inference and RDF inference rather than of RIF inference alone. In this paper, we analyze the authorization conflict problem caused by RIF inference and suggest an efficient authorization conflict detection algorithm. The algorithm exploits the graph labeling-based algorithm proposed in our earlier paper. Through experiments, we show that the performance of the graph labeling-based algorithm is outstanding for large RDF data.

A RIF Based Mapping of RDB2RDF

Mapping RDB to RDF (i.e., RDB2RDF) is the key to constructing the Semantic Web, hence has been an active research field during the last decade. Many technically heterogeneous RDB2RDF tools resulted in non-interchangeable and unreusable RDB2RDF mapping descriptions. In 2009, the W3C RDB2RDF Incubator Group Report once strongly suggested that the RDB2RDF mapping language be expressed in rules as defined by the W3C Rule Interchange Format (RIF) Working Group, because rules are an effective way to express mappings between information models, and RIF, as part of the infrastructure for the Semantic Web, is now a standard for exchanging rules among Web rule systems. This paper addresses the issue of RIF-based RDB2RDF mapping and proposes a database semantics-driven, RIF Production Rule Dialect (RIF-PRD) based mapping description approach. The work includes defining a set of generic RIF-PRD mapping rules for RDB2RDF, developing a prototype mapping engine called RIFD2RME (stands for RIF-based RDB2RDF Mapping Engine), and conducting case study experiments with the prototype. The experimental results indicate that the proposed mapping approach is achievable and effective.

F-RIF metamodel-centered fuzzy rule interchange in the Semantic Web

RIF (Rule Interchange Format), the rule interchange recommendation of the W3C (WWW Consortium), fails to represent and interchange fuzzy and nonmonotonic knowledge that pervades the Semantic Web. What’s more, current rule languages capable of representing fuzzy and nonmonotonic knowledge have heterogeneity in the aspects of syntaxes and semantics, which results in difficulties of communication among various systems. Therefore, in-depth studies on technologies of fuzzy rule interchange have become an important issue in the Semantic Web. Based on the above, we start with the investigation of general rule interchange format capable of interchanging fuzzy and nonmonotonic knowledge. First we propose f-RIF (fuzzy RIF), visually model f-RIF, and define its concrete syntax and semantics. Secondly, centered on f-RIF metamodel, we construct a fuzzy rule interchange architecture f-RIA (fuzzy Rule Interchange Architecture). The architecture supports fuzzy rule interchange between metamodels of different rule languages, and between abstract syntaxes and concrete syntaxes in the same rule languages. Thirdly, we deeply analyze the issue of information loss which is unavoidable in the process of fuzzy rule interchange, and present corresponding remedial measures to reduce adverse effects. Finally, we implement a prototype system f-RIA 1.0, and give experimental analyses. The constructed interchange architecture and the implemented prototype system can effectively solve the communication issue of current heterogeneous systems and enhance the capabilities of rules and rule systems in the aspects of representing and interchanging fuzzy and nonmonotonic knowledge. The current work lays a solid foundation on fuzzy rule reasoning in the Semantic Web.

Spatial inference with an interchangeable rule format

Rule interchange between information systems is expanding as new interoperable rule formats are emerging from research. However, existing spatial inference systems generally operate on locally stored data with an internal rule format. Consequently, their design offers little support or facilities for rule interchange. This article presents the requirements, components and design for a spatial inference system with rule interchange. Computational efficiency and overall functionality of the design are considered separately, with the latter demonstrated using encoded agricultural legislation and data. A spatial inference system with rule interchange is based on three primary components: rule representation, spatial functionality and data integration. Of these, the interoperable rule representation and data integration distinctly differ from existing spatial inference systems. The presented inference system combines a spatial superset of the W3C Rule Interchange Format (RIF) with full Open Geospatial Consortium simple feature access (OGC SFA) functionality and on-demand data integration utilising Resource Deception Framework (RDF). The design was found to be effective with a computational efficiency depending predominantly on the spatial operations. This design could be further adapted to implement spatial extensions for existing inference systems. Considerable benefits were also discovered when RIF was used as the native language for the inference engine, thereby removing the need for rule transformations and facilitating on-demand data integration with the GML.

Rule Interchange in the Semantic Web

Rule interchange has become one of the most important issues in the Semantic Web. As a recommendation of the W3C (WWW Consortium), RIF (Rule Interchange Format) is dedicated to rule interchange between different rule languages. To be a general rule interchange format, RIF should first support rule interchange with SWRL (Semantic Web Rule Language), RuleML (Rule Markup Language), R2ML (REWERSE Rule Markup Language) and F-logic (Frame Logic), before completely implementing rule interchange with other rule languages. In the paper, we propose and construct RIA(subscript XML) (Rule Interchange Architecture based on XML Syntaxes) - a rule interchange structure centered on RIF, which enables bidirectional rule interchange between RIF and SWRL, RuleML, R2ML and F-logic. Furthermore, we explore the issue of information loss and present corresponding remedial measures. More importantly, we design and implement a prototype system of RIA(subscript XML), and give its experimental analysis.

Perception framework for supporting development of context‐aware web services

PurposeContext‐awareness is an essential property of any pervasive system perceiving its environment. Such a system captures and processes context, i.e. the features describing the relevant aspects of environment state and user behaviour. However, development of these systems still requires solving a number of research and engineering challenges. The purpose of this paper is to propose perception framework, a RESTful middleware which simplifies and accelerates the development of pervasive systems. Perception framework allows constructing services' application logic using rules and context. Moreover, it collects sensor data and produces the context information that is required for the rules. The authors present the architecture, design, complete implementation, and prototype‐based verification of perception framework.Design/methodology/approachDevelopment of context‐aware services is achieved with a novel architecture supporting building of the logic of web services using rules which directly manipulate the available elementary context represented with the Web Ontology Language (OWL) ontology. These rules are described using the Rule Interchange Format (RIF) with support for different rule languages. The implementation of this framework is aligned with RESTful principles, providing a lightweight and flexible solution for large‐scale context‐aware systems.FindingsThe fully implemented prototype verifies the feasibility of constructing the logic of context‐aware web services with the rules supported by perception framework.Originality/valueThe contributions of this paper include: the requirement specification for a generic context‐aware pervasive middleware; and the design and implementation of the framework (i.e. perception framework) supporting the development of context‐aware web services. The perception framework includes a generic rule‐based reasoner allowing developers to use several RIF‐compliant rule description languages.

Integrating Semantic Web and Software Agents

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules among disparate systems. Yet, the contribution of RIF in rules exchange between Semantic Web and software agents is unclear. The BDI architectural style is regarded as the predominant approach for the implementation of intelligent agents. This paper proposes a development for integrating RIF and BDI agents to enhance agent reasoning capabilities. This approach consists of an integration architecture and equivalence principles for rule translation. The equivalence principles are demonstrated using examples. The results show that the approach allows the integration of RIF with BDI agent programming and realize the translation between the two systems.

A Guide to the Basic Logic Dialect for Rule Interchange on the Web

The W3C Rule Interchange Format (RIF) is a forthcoming standard for exchanging rules among different systems and developing intelligent rule-based applications for the Semantic Web. The RIF architecture is conceived as a family of languages, called dialects. A RIF dialect is a rule-based language with an XML syntax and a well-defined semantics. The RIF Basic Logic Dialect (RIF-BLD) semantically corresponds to a Horn rule language with equality. RIF-BLD has a number of syntactic extensions with respect to traditional textbook Horn logic, which include F-logic frames and predicates with named arguments. RIF-BLD is also well integrated with the relevant Web standards. It provides Internationalized Resource Identifiers (IRIs), XML Schema datatypes, and is aligned with RDF and OWL. This paper is a guide to the essentials of RIF-BLD, its syntax, semantics, and XML serialization. At the same time, some important RIF-BLD features are omitted due to the space limitations, including datatypes, built-ins, and the integration with RDF and OWL.

Call for Papers for Special Issue on Rule Representation, Interchange, and Reasoning in Distributed, Heterogeneous Environments

Call for Papers for Special Issue on Rule Representation, Interchange, and Reasoning in Distributed, Heterogeneous Environments