The foundational model of anatomy in OWL: Experience and perspectives

We present the method developed for migrating the Foundational Model of Anatomy (FMA) from its representation with frames in Protégé to its logical representation in OWL and our experience in reasoning with it. Despite the extensive use of metaclasses in Protégé, it proved possible to convert the FMA from Protégé into OWL DL, while capturing most of its original features. The conversion relies on a set of translation and enrichment rules implemented with flexible options. Unsurprisingly, reasoning with the FMA in OWL proved to be a real challenge, due to its sheer size and complexity, and raised significant inference problems in terms of time and memory requirements. However, various smaller versions have been successfully handled by Racer. Some inconsistencies were identified and several classes reclassified. The results obtained so far show the advantage of OWL DL over frames and, more generally, the usefulness of DLs reasoners for building and maintaining the large-scale biomedical ontologies of the future Semantic Web.     

OWL DL的形式化基础研究

W3C正在制定的OWL DL是一种面向语义Web的知识表示标记语言，具有较强的知识表达能力并适合大规模应用的推理效率，是语义Web领域对适合语义Web应用的知识表示标记语言进行研究的最新综合．在知识表示领域，为了对知识表达能力和推理效率做合适的折衷，进行了大量关于描述逻辑的研究，本文以描述逻辑作为OWL DL的形式化基础，详细分析了OWL DL和描述逻辑间的对应关系，用描述逻辑的语义解释了OWL DL的各个基本元素，从而可以将描述逻辑领域研究的大量成果应用到OWL DL上来，为进一步研究OWL DL的知识表示、推理等问题奠定了基础．     

基于语义网规则语言的推理机制框架设计

分析了本体描述语言OWL DL在表达能力上局限于描述逻辑的缺陷以及语义网规则语言(semantic web rule language,SWRL)的特点,在已有时本体和规则结合推理的研究基础上,提出了一个基于SWRL的推理机制框架.该框架在OWL本体中引入了规则的表示,弥补了OWLDL在推理机制上的不足,经该框架推导出的新本体在原本体的基础上增加了概念间的语义关联,将隐性知识显示化,完善了本体知识库的内容.在语义Web领域,该框架的应用能够提高本体知识的利用率.     

基于本体论的语义建模研究

本体(Ontology)是下一代互联网(SemanticWeb)的基础,OWL语言是W3C组织定义的本体描述语言。鉴于当前互联网的规模越来越庞大,如何准确快速地获取信息正变得至关重要,而基于本体论的语义模型为信息的表示、交换和处理提供了一个较为合理的标准,从而使得网上信息的完全共享成为可能。文中阐述了本体的概念,重点探讨了基于本体论的语义建模方法和OWL语言对本体表示的支持,并且具体给出了一个基于OWL语言的建模实例。     

Ontological approach for DSL development

This paper presents a project whose main objective is to explore the ontological based development of Domain Specific Languages (DSL), more precisely, of their underlying Grammar. After reviewing the basic concepts characterizing Ontologies and DSLs, we introduce a tool, Onto2Gra, that takes profit of the knowledge described by the ontology and automatically generates a grammar for a DSL that allows to discourse about the domain described by that ontology. This approach represents a rigorous method to create, in a secure and effective way, a grammar for a new specialized language restricted to a concrete domain. The usual process of creating a grammar from the scratch is, as every creative action, difficult, slow and error prone; so this proposal is, from a grammar engineering point of view, of uttermost importance. After the grammar generation phase, the Grammar Engineer can manipulate it to add syntactic sugar to improve the final language quality or even to add specific semantic actions. The Onto2Gra project is composed of three engines. The main one is OWL2DSL, the component that converts an OWL ontology into a complete Attribute Grammar for the construction of an internal representation of all the input data. The two additional modules are Onto2OWL, converts ontologies written in OntoDL into standard OWL, and DDesc2OWL, converts domain instances written in the new DSL into the initial OWL ontology.     

Contextualizing ontologies

Ontologies are shared models of a domain that encode a view which is common to a set of different parties. Contexts are local models that encode a party’s subjective view of a domain. In this paper, we show how ontologies can be contextualized, thus acquiring certain useful properties that a pure shared approach cannot provide. We say that an ontology is contextualized or, also, that it is a contextual ontology, when its contents are kept local, and therefore not shared with other ontologies, and mapped with the contents of other ontologies via explicit (context) mappings. The result is Context OWL (C-OWL), a language whose syntax and semantics have been obtained by extending the OWL syntax and semantics to allow for the representation of contextual ontologies.     

基于Web本体语言OWL的知识表示

知识表示的方法论研究是知识管理系统研究中重要的问题,提出将Web本体语言OWL应用到知识表示中。为此,从OwL语言的表示能力,针对不同用户群的分层,可操作性,可扩充性等方面进行了简要地分析。然后,以高校教育资源的知识表示为例,说明了OWL的知识表示过程。基于OWL的知识表示是一种表达能力较强,语法独立,可扩充的,适用于分布式系统的知识表示方法。     

A Rule-Based Object-Oriented OWL Reasoner

In this paper, we describe O-DEVICE, a memory-based knowledge-based system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an object-oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.     

OWL rules: A proposal and prototype implementation

Although the OWL Web Ontology Language adds considerable expressive power to the Semantic Web it does have expressive limitations, particularly with respect to what can be said about properties. We present the Semantic Web Rule Language (SWRL), a Horn clause rules extension to OWL that overcomes many of these limitations. SWRL extends OWL in a syntactically and semantically coherent manner: the basic syntax for SWRL rules is an extension of the abstract syntax for OWL DL and OWL Lite; SWRL rules are given formal meaning via an extension of the OWL DL model-theoretic semantics; SWRL rules are given an XML syntax based on the OWL XML presentation syntax; and a mapping from SWRL rules to RDF graphs is given based on the OWL RDF/XML exchange syntax. We discuss the expressive power of SWRL, showing that the ontology consistency problem is undecidable, provide several examples of SWRL usage, and discuss a prototype implementation of reasoning support for SWRL.     

A parallel computing architecture for high-performance OWL reasoning

The Web Ontology Language (OWL) is a widely used knowledge representation language for describing knowledge in application domains by using classes, properties, and individuals. Ontology classification is an important and widely used service that computes a taxonomy of all classes occurring in an ontology. It can require significant amounts of runtime, but most OWL reasoners do not support any kind of parallel processing. We present a novel thread-level parallel architecture for ontology classification, which is ideally suited for shared-memory SMP servers, but does not rely on locking techniques and thus avoids possible race conditions. We evaluated our prototype implementation with a set of real-world ontologies. Our experiments demonstrate a very good scalability resulting in a speedup that is linear to the number of available cores.     

Identification and resolution of conflicts during ontological integration using rules

Abstract: Integration of ontologies of information sources and consumers is an important phase in achieving web‐based interoperability. The present work describes an approach for identifying certain semantic conflicts while integrating ontologies of heterogeneous information sources. This paper is focused on the identification of homonymy and synonymy between elements in ontologies. In the present work the concepts of homonymy and synonymy are synonymous to naming conflicts and entity identifier conflicts, respectively, and partial synonymy is synonymous to schema isomorphism conflicts. The concept of the mask of interoperability is introduced for the identification of synonymy. The mask of interoperability is expressed in a declarative way as a set of rules, which can then be used for resolution of conflicts during integration of ontologies. As proof of concept, ontologies are implemented using the XML‐based ontology language Ontology Web Language (OWL), and the rules are implemented using the emerging rule language Semantic Web Rule Language (SWRL). This representation in OWL and SWRL allows the ontology to be executable, flexibly extendable and platform‐independent. The OWL facts and SWRL rules are used by the Jess and Bossam reasoning engine to identify semantic homonymy and synonymy.