Rules and Rule Markup Languages for the Semantic Web

Rules represent the next step for the Semantic Web. A number of use cases for Semantic Web Rules have been formally and informally proposed, including ontology extension, ontology translation, data expansion, portable axiomatic semantics, matching, monitoring, and profile and process descriptions for Semantic Web Services. This talk will describe each of these use cases, provide examples, and assess the degree to which each is addressed by the Semantic Web Rule Language (SWRL) and other current alternatives.

Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsistent information. Such reasoning is, among others, useful for ontology integration, where conflicting information arises naturally; and for the modeling of business rules and policies, where rules with exceptions are often used. This paper describes these scenarios in more detail, and reports on the implementation of a system for defeasible reasoning on the Web. The system (a) is syntactically compatible with RuleML; (b) features strict and defeasible rules and priorities; (c) is based on a translation to logic programming with declarative semantics; and (d) is flexible and adaptable to different intuitions within defeasible reasoning.

The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a computer. The problem of collecting product information from the Web and organizing it in an appropriate way for automated machine processing is a primary task of software shopping agents and has received a lot of attention during the last years. In this paper we assume that product information is represented as a set of feature-value pairs contained in an HTML product information sheet that is usually formatted using HTML tables. The paper presents a technique for learning extraction rules of product information from such product information sheets. The technique exploits the fact that the Web pages that represent product information of a certain producer are generated on the fly from the producer database and therefore they exhibit uniform structures. Consequently, while the extraction task is executed manually for a few information items by a human user, a general-purpose inductive learner (we have used FOIL in our experiments) can learn extraction rules that will be further applied to the current and other product information sheets to automatically extract other items. The input to the learning algorithm is a relational description of the HTML document tree that defines the HTML tree nodes types and the relationships between them. The approach is demonstrated with appropriate examples, experimental results, and software tools.

Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsistent information. Such reasoning is, among others, useful for ontology integration, where conflicting information arises naturally; and for the modeling of business rules and policies, where rules with exceptions are often used. This paper describes these scenarios in more detail, and reports on the implementation of a system for defeasible reasoning on the Web. The system is called DR-DEVICE and is capable of reasoning about RDF metadata over multiple Web sources using defeasible logic rules. The system is implemented on top of CLIPS production rule system and builds upon R-DEVICE, an earlier deductive rule system over RDF metadata that also supports derived attribute and aggregate attribute rules. Rules can be expressed either in a native CLIPS-like language, or in an extension of the OO-RuleML syntax. The operational semantics of defeasible logic are implemented through compilation into the generic rule language of R-DEVICE. The paper also briefly presents a semantic web broker example for apartment renting.

In this paper we present R-DEVICE, a deductive rule language for reasoning about RDF metadata. R-DEVICE includes features such as normal and generalized path expressions, stratified negation, aggregate, grouping, and sorting, functions. The rule language supports a second-order syntax, where variables can range over classes and properties. Users can define views which are materialized and, optionally, incrementally maintained by translating deductive rules into CLIPS production rules. Users can choose between an OPS5/CLIPS-like or a RuleML-like syntax. R-DEVICE is based on a OO RDF data model, different than the established graph model, which maps resources to objects and encapsulates properties inside resource objects, as traditional OO attributes. In this way, less joins are required to access the properties of a single resource resulting in better inferencing/querying performance. The descriptive semantics of RDF may call for dynamic re-definitions of resource classes and objects, which are handled by R-DEVICE effectively.

In previous work, towards the integration of rules and ontologies in the Semantic Web, we have proposed a combination of logic programming under the answer set semantics with the description logics \({\cal SHIF}({\mathbf{D}})\) and \({\cal SHOIN}({\mathbf{D}})\), which underly the Web ontology languages OWL Lite and OWL DL, respectively. More precisely, we have introduced description logic programs (or dl-programs), which consist of a description logic knowledge base L and a finite set of description logic rules P, and we have defined their answer set semantics. In this paper, we continue this line of research. Here, as a central contribution, we present the well-founded semantics for dl-programs, and we analyze its semantic properties. In particular, we show that it generalizes the well-founded semantics for ordinary normal programs. Furthermore, we show that in the general case, the well-founded semantics of dl-programs is a partial model that approximates the answer set semantics, whereas in the positive and the stratified case, it is a total model that coincides with the answer set semantics. Finally, we also provide complexity results for dl-programs under the well-founded semantics.

We propose to extend description logic with defeasible rules, and to use the inferential mechanism of defeasible logic to reason with description logic constructors.

We extend Answer Set Programming with, possibly infinite, open domains. Since this leads, in general, to undecidable reasoning, we restrict the syntax of programs, while carefully guarding useful knowledge representation mechanisms such as negation as failure and inequalities. Reasoning with the resulting Conceptual Logic Programs can be reduced to finite, normal Answer Set Programming, for which reasoners are available.

We argue that Conceptual Logic Programming is a useful tool for uniformly representing and reasoning with both ontologies and rules on the Semantic Web, as they can capture a large fragment of the OWL DL ontology language, while extending it in various aspects.

In this paper, we describe our effort to build an inference engine for OWL reasoning based on the rule engine paradigm. Rule engines are very practical and effective for their representational simplicity and optimized performance, but their limited expressiveness and web unfriendliness restrict their usability for OWL reasoning. We enumerate and succinctly describe extended features implemented in our rule engine, Bossam, and show that these features are necessary to promote the effectiveness of any ordinary rule engine’s OWL reasoning capability. URI referencing and URI-based procedural attachment enhance web-friendliness. OWL importing, support for classical negation and relieved range restrictedness help correctly capture the semantics of OWL. Remote binding enables collaborated reasoning among multiple Bossam engines, which enhances the engine’s usability on the distributed semantic web environment. By applying our engine to the W3C’s OWL test cases, we got a plausible 70% average success rate for the three OWL species. Our contribution with this paper is to suggest a set of extended features that can enhance the reasoning capabilities of ordinary rule engines on the semantic web.

Drawing on experience gained over a series of distributed knowledge base and database projects, we argue for the utility of an expressive quantified constraint language for the Semantic Web logic layer. Our Constraint Interchange Format (CIF) is based on classical range-restricted FOL. CIF allows the expression of invariant conditions in Semantic Web data models, but the choice of how to implement the constraints is left to local reasoners.

We develop the quantified constraint representation as an extension of the current proposal for a Semantic Web Rule Language (SWRL). An RDF syntax for our extended CIF/SWRL is given in this paper. While our approach differs from SWRL in that existential quantifiers are handled explicitly rather than using OWL-DL constructs, we believe our proposal is still fully compatible with the use of the various OWL species as well as RDFS.

We demonstrate the use of the CIF/SWRL representation in the context of a practical Semantic Web reasoning application, based on the CS AKTive Space demonstrator (the 2003 Semantic Web Challenge winner). We indicate where in our application it makes sense to use the existing SWRL directly, and where our CIF/SWRL allows more complex constraints to be expressed in a natural manner.

In Semantic Web, using rules to add more expressive power has drawn considerable attention. Recently ORL (OWL Rules Language) has been presented where OWL is extended with Horn clause rules. In this paper we propose an extension to OWL with more general rules involving not only atoms but also literals with classical negation and negation as failure. We present first the abstract syntax for our OWL extension and then its semantics via the Answer Set Programming(ASP). Furthermore, we discuss the iterative procedures for reasoning between OWL axioms and ASP rules.

The importance of integrating rules and ontologies for the Semantic Web has been well addressed by many researchers. Defeasible Logic is a simple but efficient nonmonotonic language which can handle both defeasibility and priority. In this paper we propose a novel approach to combining Defeasible Logic with Description Logics by introducing the Description Defeasible Logic (DDL). DDL is similar to Defeasible Logic but it also contains queries to the Description Logic knowledge base. DDL allows nonmonotonic reasoning to be built on top of ontologies, and to a certain degree, allows ontologies to be built on top of nonmonotonic reasoning. We give some basic properties of DDL, one of which shows that DDL is a tractable language provided that the underlying Description Logic is tractable.

Web Services is transforming the information sharing Web into a heterogeneous, distributed resource integration platform, aiming at enabling a global service market in which individuals and organizations can offer their competitive services to potential clients across the Web. To succeed, if not just survive, in such an emerging Web Services market, companies need effective strategies and methods to help them design reusable Web services and build Web services-based applications rapidly. In this paper, we present a dynamic service customization and composition framework for Web services. In particular, we propose a rule-based service integration language with concepts borrowed from rewriting systems. We show how the language can be used to model complex collaboration patterns among services, and compare our framework with other service integration approaches.

This paper describes the design and implementation of SweetProlog, a system for translating Web rules into Prolog. It enables the integration of ontologies and rules on the Semantic Web. This is achieved via a translation of OWL ontologies described in Description Logics and rules expressed in OWLRuleML into a set of facts and rules described in Prolog. Finally, the resulting logic program is interrogated by a Prolog engine to deduce new knowledge.

This paper introduces an XML presentation syntax, SWRLp, that facilitates the reading and editing of SWRL rules. A description of the language design and motivation is presented along with a simple example of the improvement afforded in rule readability by the use of SWRLp. XSLT transformation scripts for translating to and from SWRLp and SWRL, RuleML, pseudo-Prolog and Jess are also described.

Although XET is a powerful rule language, a mechanism to provide an automatic update on an XML document according to monitored events cannot be realized easily under the common use of XET. Proposed in the paper is a simple XML-expression transformation by XET enabling applications to perform update actions on an XML document when an event is detected. As a case study, it will be shown that XET is capable of maintaining consistency between UML diagrams. The capabilities include inconsistency detection according to user changes and automatic resolution process.

This paper reports on a system for automated agent negotiation. The negotiation strategies are expressed in defeasible logic, and are applied using the implemented reasoning system DR-DEVICE. The overall system architecture is described, and a particular 1-1 negotiation scenario is presented in detail.