Recently, there has been a wide interest in using ontologies on the Web. As a basis for this, RDF Schema (RDFS) provides means to define vocabulary, structure and constraints for expressing metadata about Web resources. However, formal semantics are not provided, and the expressivity of it is not enough for full-fledged ontological modeling and reasoning. In this paper, we will show how RDFS can be extended in such a way that a full knowledge representation (KR) 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 RDFS. An important benefit of our approach is that it ensures maximal sharing of meta-data on the Web: even partial interpretation of an OIL ontology by less semantically aware processors will yield a correct partial interpretation of the meta-data. We conclude that our method of extending is equally applicable to other KR formalisms.

The World Wide Web (WWW) has drastically changed the availability of electronically accessible information. Currently there are around three billion static documents in the WWW that are used by more than 200 million users internationally, and this number is

. This paper discusses technology to support the use of UML for representing ontologies and domain knowledge in the Semantic Web. Two mappings have been defined and implemented using XSLT to produce Java classes and an RDF schema from an ontology represented as a UML class diagram and encoded using XMI. A Java application can encode domain knowledge as an object diagram realised as a network of instances of the generated classes. Support is provided for marshalling and unmarshalling this object-oriented knowledge to and from an RDF/XML serialisation. The paper also proposes an extension to RDF allowing the identification of property-- resource pairs in a model for which `closed world' reasoning cannot be used due to incomplete knowledge. 1

Abstract 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. 1

Currently computers are changing from single isolated devices to entry points into a worldwide network of information exchange and business transactions. Therefore, support in the exchange of data, information, and knowledge is becoming the key issue in computer technology today. Ontologies provide a shared and common understanding of a domain that can be communicated between people and across application systems. Ontologies will play a major role in supporting information exchange processes in various areas. A prerequisite for such a role is the development of a joint standard for specifying and exchanging Ontologies well-integrated with existing web standards. This paper deals with precisely this necessity. We will present OIL which is a proposal for such a standard enabling the semantic web, i.e. information with machine processable semantics. It is based on existing proposals such as OKBC, XOL and RDFS, and enriches them with necessary features for expressing rich ontologies. The paper presents the motivation, underlying rationale, modeling primitives, syntax, semantics, tool environment, and applications of OIL.

The paper presents a system architecture for the automatic generation of interface specifications from ontologies. The ensuing

The contributions of this thesis bridge two disciplines: environmental science (specifically, wastewater management) and computer science (specifically, artificial intelligence). Wastewater management as a discipline operates using a range of different approaches and methods which include: manual control, on-line automatic control, numerical or non-numerical models, statistical models and simulation models. The thesis characterizes an interdisciplinary research on artificial intelligence techniques (rule-based reasoning, case-based reasoning, ontologies and planning) applied to environmental decision-support systems. The integrated architecture's design of this application, the OntoWEDSS system, augments classic reasoning systems (rule-based reasoning and case-based reasoning) with a domain ontology about the management of wastewater treatment plants. The integration of the newly created WaWO ontology provides a more flexible management capability to OntoWEDSS. The construction of the OntoWEDSS decision support system is based on a specific case study but the system is also of general interest, given that its ontologyunderpinned architecture can be applied to any wastewater treatment plant and, at an appropriate level of abstraction, to other environmental domains. The OntoWEDSS system improves the diagnosis of the state of a treatment plant, provides support for wastewater-related complex problem-solving, and facilitates knowledge modelling and reuse by means of the WaWO ontology.

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The current web suffers information overloading: it is increasingly difficult and time consuming to obtain information desired. Ontologies, the key concept behind the Semantic Web, will provide the means to overcome such problem by providing meaning to the available data. An ontology provides a shared and common understanding of a domain and information machine-processable semantics. To make the Semantic Web a reality and lift current Web to its full potential, powerful and expressive languages are required. Such web ontology languages must be able to describe and organize knowledge in the Web in a machine understandable way. However, organizing knowledge requires the facilities of a logical formalism which can deal with temporal, spatial, epistemic, and inferential aspects of knowledge. Implementations of Web ontology languages must provide these inference services, making them much more than just simple data storage and retrieval systems. This paper presents a detailed comparison of the most relevant Semantic Web

In order to enrich XML with event driven, active behavior, the Active XML Schema approach defines active behavior within XML schemas along metadata, and stores traces of active behavior such as occurred events within XML documents along data. The semantic expressiveness of XML Schema, the schema language recommended by the W3C, however, is not sufficient to define the active semantics of Active XML Schema concepts. The contribution of this paper is to identify, explore, and evaluate approaches to implementing Active XML Schema with XML Schema, discussing the trade-off between semantic expressiveness and interoperability. Assuming that Active XML Schema may be seen as representative for tailored schema languages, the findings of this paper can be applied for arbitrary tailored schema languages. 1.