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CREAM: creating relational metadata with a component-based, ontology-driven annotation framework

TLDR
CREAM (Creating RElational, Annotation-based Metadata), a framework for an annotation environment that allows to construct relational metadata, i.e. metadata that comprises class instances and relationship instances, is presented.
Abstract
Richly interlinked, machine-understandable data constitutes the basis for the Semantic Web. Annotating web documents is one of the major techniques for creating metadata on the Web. However, annotation tools so far are restricted in their capabilities of providing richly interlinked and truely machine-understandable data. They basically allow the user to annotate with plain text according to a template structure, such as Dublin Core. We here present CREAM (Creating RElational, Annotation-based Metadata), a framework for an annotation environment that allows to construct relational metadata, i.e. metadata that comprises class instances and relationship instances. These instances are not based on a fix structure, but on a domain ontology. We discuss some of the requirements one has to meet when developing such a framework, e.g. the integration of a metadata crawler, inference services, document management and information extraction, and describe its implementation, viz. Ont-O-Mat a component-based, ontology-driven annotation tool.

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Citations
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Proceedings ArticleDOI

EDUTELLA: a P2P networking infrastructure based on RDF

TL;DR: In this article, the authors discuss the open source project Edutella which builds upon metadata standards defined for the WWW and aims to provide an RDF-based metadata infrastructure for P2P applications, building on the recently announced JXTA Framework.
Proceedings ArticleDOI

Towards the self-annotating web

TL;DR: PANKOW (Pattern-based Annotation through Knowledge on theWeb), a method which employs an unsupervised, pattern-based approach to categorize instances with regard to an ontology, is proposed.
Book ChapterDOI

S-CREAM - Semi-automatic CREAtion of Metadata

TL;DR: OntoMat-Annotizer extract with the help of Amilcare knowledge structure from web pages through the use of knowledge extraction rules, the result of a learning-cycle based on already annotated pages.
Book ChapterDOI

MnM: Ontology Driven Semi-automatic and Automatic Support for Semantic Markup

TL;DR: M is presented, an annotation tool which provides both automated and semi-automated support for annotating web pages with semantic contents and integrates a web browser with an ontology editor and provides open APIs to link to ontology servers and for integrating information extraction tools.
References
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Journal ArticleDOI

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