York Sure

Knowledge processes and ontologies

In this article, we present an approach for ontology-based knowledge management (KM) that includes a tool suite and a methodology for developing ontology-based KM systems. It builds on the distinction between knowledge processes and knowledge metaprocesses, and is illustrated by CHAR (Corporate History AnalyzeR), a KM system for corporate history analysis.

Ontology Mapping – An Integrated Approach

Ontology mapping is important when working with more than one ontology. Typically similarity considerations are the basis for this. In this paper an approach to integrate various similarity methods is presented. In brief, we determine similarity through rules which have been encoded by ontology experts. These rules are then combined for one overall result. Several boosting small actions are added. All this is thoroughly evaluated with very promising results.

OntoEdit: Collaborative Ontology Development for the Semantic Web

Ontologies now play an important role for enabling the semantic web. They provide a source of precisely defined terms e.g. for knowledge-intensive applications. The terms are used for concise communication across people and applications. Typically the development of ontologies involves collaborative efforts of multiple persons. OntoEdit is an ontology editor that integrates numerous aspects of ontology engineering. This paper focuses on collaborative development of ontologies with OntoEdit which is guided by a comprehensive methodology.

KAON - Towards a Large Scale Semantic Web

The Semantic Web will bring structure to the content of Web pages, being an extension of the current Web, in which information is given a well-defined meaning. Especially within e-commerce applications, Semantic Web technologies in the form of ontologies and metadata are becoming increasingly prevalent and important. This paper introduce KAON - the Karlsruhe Ontology and Semantic WebTool Suite. KAON is developed jointly within several EU-funded projects and specifically designed to provide the ontology and metadata infrastructure needed for building, using and accessing semantics-driven applications on the Web and on your desktop.

Semantic community Web portals

Abstract Community Web portals serve as portals for the information needs of particular communities on the Web. We here discuss how a comprehensive and flexible strategy for building and maintaining a high-value community Web portal has been conceived and implemented. The strategy includes collaborative information provisioning by the community members. It is based on an ontology as a semantic backbone for accessing information on the portal, for contributing information, as well as for developing and maintaining the portal. We have also implemented a set of ontology-based tools that have facilitated the construction of our show case — the community Web portal of the knowledge acquisition community.

Bootstrapping ontology alignment methods with APFEL

Ontology alignment is a prerequisite in order to allow for interoperation between different ontologies and many alignment strategies have been proposed to facilitate the alignment task by (semi-)automatic means. Due to the complexity of the alignment task, manually defined methods for (semi-)automatic alignment rarely constitute an optimal configuration of substrategies from which they have been built. In fact, scrutinizing current ontology alignment methods, one may recognize that most are not optimized for given ontologies. Some few include machine learning for automating the task, but their optimization by machine learning means is mostly restricted to the extensional definition of ontology concepts. With APFEL (Alignment Process Feature Estimation and Learning) we present a machine learning approach that explores the user validation of initial alignments for optimizing alignment methods. The methods are based on extensional and intensional ontology definitions. Core to APFEL is the idea of a generic alignment process, the steps of which may be represented explicitly. APFEL then generates new hypotheses for what might be useful features and similarity assessments and weights them by machine learning approaches. APFEL compares favorably in our experiments to competing approaches.

SEAL: a framework for developing SEmantic PortALs

The core idea of the Semantic Web is to make information accessible to human and software agents on a semantic basis. Hence, Web sites may feed directly from the Semantic Web exploiting the underlying structures for human and machine access. We have developed a domain-independent approach for developing semantic portals, viz. SEAL (SEmantic portAL), that exploits semantics for providing and accessing information at a portal as well as constructing and maintaining the portal. In this paper we focus on semantics-based means that make semantic Web sites accessible from the outside, i.e. semantics-based browsing, semantic querying, querying with semantic similarity, and machine access to semantic information. In particular, we focus on methods for acquiring and structuring community information as well as methods for sharing information.As a case study we refer to the AIFB portal - a place that is increasingly driven by Semantic Web technologies. We also discuss lessons learned from the ontology development of the AIFB portal..

The SWRC ontology – semantic web for research communities

Representing knowledge about researchers and research communities is a prime use case for distributed, locally maintained, interlinked and highly structured information in the spirit of the Semantic Web. In this paper we describe the publicly available ‘Semantic Web for Research Communities’ (SWRC) ontology, in which research communities and relevant related concepts are modelled. We describe the design decisions that underlie the ontology and report on both experiences with and known usages of the SWRC Ontology. We believe that for making the Semantic Web reality the re-usage of ontologies and their continuous improvement by user communities is crucial. Our contribution aims to provide a description and usage guidelines to make the value of the SWRC explicit and to facilitate its re-use.

OntoEdit: Guiding Ontology Development by Methodology and Inferencing

Ontologies now play an important role for many knowledge-intensive applications for which they provide a source of precisely defined terms. The terms are used for concise communication across people and applications. OntoEdit is an ontology editor that has been developed keeping five main objectives in mind: 1. Ease of use. 2. Methodology-guided development of ontologies. 3. Ontology development with help of inferencing. 4. Development of ontology axioms. 5. Extensibility through plug-in structure. This paper is about the first four of these items.

On-To-Knowledge Methodology (OTKM)

In this chapter we present the On-To-Knowledge Methodology (OTKM) for introducing and maintaining ontology based knowledge management applications into enterprises with a focus on Knowledge Processes and Knowledge Meta Processes. While the former process circles around the usage of ontologies, the latter process guides their initial set up. We illustrate our methodology by an example from a case study on skills management.