The RDF schema specification revisited

2000

RDF Schema provides means to define vocabulary, structure and constraints for expressing metadata about Web resources. However, formal semantics for the primitives defined in RDF Schema are not provided, and the expressivity of these primitives is not enough for full-fledged ontological modeling and reasoning. To perform these tasks, an additional layer on top of RDF Schema is needed. In this paper, we will show how RDF Schema can be extended in such a way that a full knowledge representation language can be expressed in it, thus enriching it with the required additional expressivity and the semantics of this language. We do this by describing the ontology language OIL as an extension of RDF Schema. First, we give a short introduction to both RDF Schema and OIL. We then proceed to define a Schema to express OIL ontologies in RDF, where the aim is to use existing RDF terminology where possible, and extending RDF(S) where necessary. The result is an RDF Schema definition of OIL primitives, which allows one to express any OIL ontology in RDF syntax, thus enabling the added benefits of OIL, such as reasoning support and formal semantics, to be used on the Web. We conclude that our method of extending is equally applicable to other knowledge representation formalisms.

Encyclopedia of GIS, 2008

The Resource Description Framework (RDF) is the standard knowledge representation language for the Semantic Web, an evolution of the World Wide Web that aims to provide a well-founded infrastructure for publishing, sharing and querying structured data. This article provides an introduction to RDF and its related vocabulary definition language RDF Schema, and explains its relationship with the OWL Web Ontology Language. Finally, it provides an overview of the historical development of RDF and related languages for Web metadata.

The Resource Description Framework (RDF[9]) has been developed to fulfil the need for a mechanism for resource description within the Web's architecture. With over 320 million[10] individually accessible objects on the Web, the ability to describe each one so that it can be conceptualized without being accessed and analyzed is increasingly important. This paper describes how an automatic classifier[8], that classifies Web pages according to Dewey Decimal Classification[6], can be used to automatically extract various metadata elements in addition to the classification classmarks. This metadata is then presented in RDF format. The classifier is written in Java and has been developed to form part of a distributed automated search engine. The use of automatic classification is intended to combine the well organized, intuitive to use, accurate features of classified directories with the comprehensive coverage and speed of automated search engines. An appropriate metadata element set for use within an automated search engine is defined which is an interoperable subset of the Dublin Core[14] elements. An RDF data model[9] and schema[1] are defined along with examples of automatically generated RDF for a range of resources. Automatically generated metadata of this kind has considerable potential for describing shared resources between subject gateways and could also encourage information sharing between automated search engines. Resource descriptions are also important for content rating and authentication and as such the automatic generation of RDF metadata is arguably an essential prerequisite for a comprehensive 'Web of Trust'.

… Modeling for E- …, 2000

Proc. of WebNet, 2000

International Journal on Semantic Web …, 2006

In this paper we present R-DEVICE, a deductive object-oriented knowledge base system for reasoning over RDF metadata. R-DEVICE imports RDF documents into the CLIPS production rule system by transforming RDF triples into COOL objects and uses a deductive rule language for reasoning about them. R-DEVICE is based on an OO RDF data model, different than the established triple-based model, which maps resources to objects and encapsulates properties inside resource objects, as traditional OO attributes. In this way, fewer joins are required to access the properties of a single resource resulting in better inferencing/querying performance, as it is experimentally shown in the paper. Furthermore, RDF can interoperate seamlessly with other web data models and languages. The descriptive semantics of RDF may call for dynamic redefinitions of resource classes, which are handled by R-DEVICE effectively. Furthermore, R-DEVICE features a powerful deductive rule language for reasoning on top of RDF metadata. The rule language includes features such as normal and generalized path expressions, stratified negation, aggregate, grouping, and sorting, functions. The rule language supports a second-order syntax, which is efficiently translated into sets of firstorder logic rules using metadata, where variables can range over classes and properties, so that reasoning over the RDF schema can be made. Users can define views which are materialized and incrementally maintained by translating deductive rules into CLIPS production rules that preserve truth. Users can choose between an OPS5/CLIPS-like and a RuleML-like syntax. Finally, users can define and use functions through the CLIPS host language.

International Journal on Semantic Web and Information Systems, 2006

In this paper we present R-DEVICE, a deductive object-oriented knowledge base system for reasoning over RDF metadata. R-DEVICE imports RDF documents into the CLIPS production rule system by transforming RDF triples into COOL objects and uses a deductive rule language for reasoning about them. R-DEVICE is based on an OO RDF data model, different than the established triple-based model, which maps resources to objects and encapsulates properties inside resource objects, as traditional OO attributes. In this way, fewer joins are required to access the properties of a single resource resulting in better inferencing/querying performance, as it is experimentally shown in the paper. Furthermore, RDF can interoperate seamlessly with other web data models and languages. The descriptive semantics of RDF may call for dynamic redefinitions of resource classes, which are handled by R-DEVICE effectively. Furthermore, R-DEVICE features a powerful deductive rule language for reasoning on top of RDF metadata. The rule language includes features such as normal and generalized path expressions, stratified negation, aggregate, grouping, and sorting, functions. The rule language supports a second-order syntax, which is efficiently translated into sets of firstorder logic rules using metadata, where variables can range over classes and properties, so that reasoning over the RDF schema can be made. Users can define views which are materialized and incrementally maintained by translating deductive rules into CLIPS production rules that preserve truth. Users can choose between an OPS5/CLIPS-like and a RuleML-like syntax. Finally, users can define and use functions through the CLIPS host language.

IEEE Internet Computing, 2000

2001

The term "application profile" has recently become highly topical. Heery and Patel [1] define application profiles as metadata schemas which consist of metadata elements drawn from one or more namespaces, combined together by implementers and optimised for a particular local application. They state that the principal characteristics of an application profile are that: it may draw on one or more existing namespaces; does not introduce new metadata elements; it can specify permitted schemes and values; and it can refine standard metadata elements. Significant new initiatives such as TV-Anytime [2], MPEG-21 [3] and the Open Archives Initiative (OAI) [4] are demanding application profiles which combine elements from a number of different existing standardized metadata schemas whilst maintaining interoperability and satisfying their own specific requirements through refinements, extensions and additions. So far approaches to application profiles have been based on either RDF Schemas or XML Schemas . The SCHEMAS project [9] has adopted a purely RDF Schema approach. Justification for a pure XML Schema approach to application profiles is given in . Despite high level assurances of unification from the W3C [11, 12], a purist and competitive attitude has prevailed amongst implementers. This has been because the demarcation of roles and the interface between these two disparate W3C Candidate Recommendations has been fuzzy; no low level details or implementations describing interface mechanisms have been provided; and implementers have been afraid of compromising interoperability. In this paper we describe a hybrid collaborative approach which combines the semantic knowledge of RDF Schemas with the explicit structural, cardinality and datatyping constraints provided by XML Schemas in a complementary manner. First we describe our view of how XML Schema and RDF Schema fit into the overall web metadata architecture. We then describe possible schema interface mechanisms.

Electronic Transactions on Artificial Intelligence, 2000

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