Search (109 results, page 6 of 6)

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Theme

Semantic Web

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Abstract

Within the cultural heritage field, proprietary metadata and vocabularies are being transformed into public Linked Data. These efforts have mostly been at the level of large-scale aggregators such as Europeana where the original data is abstracted to a common format and schema. Although this approach ensures a level of consistency and interoperability, the richness of the original data is lost in the process. In this paper, we present a transparent and interactive methodology for ingesting, converting and linking cultural heritage metadata into Linked Data. The methodology is designed to maintain the richness and detail of the original metadata. We introduce the XMLRDF conversion tool and describe how it is integrated in the ClioPatria semantic web toolkit. The methodology and the tools have been validated by converting the Amsterdam Museum metadata to a Linked Data version. In this way, the Amsterdam Museum became the first 'small' cultural heritage institution with a node in the Linked Data cloud.

Source

9th Extended Semantic Web Conference (ESWC), 2012-05-27/2012-05-31 in Hersonissos, Crete, Greece. Eds.: Elena Simperl et al

Theme

Semantic Web

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Content

Inhalt: 1. From traditional Knowledge Organization Systems (authority files, classifications, thesauri) towards ontologies on the web (Alexander Sigel) (Tutorial. Paper with Slides interspersed) pp. 3-53 2. Introduction to Integrative Cross-Language Ontology (ICLO): Formalizing and interrelating textual knowledge to enable intelligent action and knowledge sharing (Winfried Schmitz-Esser) pp. 54-113 3. First Idea Sketch on Modelling ICLO with Topic Maps (Alexander Sigel) (Work in progress paper. Topic maps available from the author) pp. 114-130

Theme

Semantic Web

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Semantic Web

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Semantic Web

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Theme

Semantic Web

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Semantic Web

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Abstract

Developing ontologies is central to our vision of Semantic Web-based knowledge management. The methodology described in Chapter 3 guides the development of ontologies for different applications. However, because of the size of ontologies, their complexity, their formal underpinnings and the necessity to come towards a shared understanding within a group of people when defining an ontology, ontology construction is still far from being a well-understood process. Concerning the methodology, OntoEdit focuses on three of the main steps for ontology development (the methodology is described in Chapter 3), viz. the kick off, refinement, and evaluation. We describe the steps supported by OntoEdit and focus on collaborative aspects that occur during each of the step. First, all requirements of the envisaged ontology are collected during the kick off phase. Typically for ontology engineering, ontology engineers and domain experts are joined in a team that works together on a description of the domain and the goal of the ontology, design guidelines, available knowledge sources (e.g. re-usable ontologies and thesauri, etc.), potential users and use cases and applications supported by the ontology. The output of this phase is a semiformal description of the ontology. Second, during the refinement phase, the team extends the semi-formal description in several iterations and formalizes it in an appropriate representation language like RDF(S) or, more advanced, DAML1OIL. The output of this phase is a mature ontology (the 'target ontology'). Third, the target ontology needs to be evaluated according to the requirement specifications. Typically this phase serves as a proof for the usefulness of ontologies (and ontology-based applications) and may involve the engineering team as well as end users of the targeted application. The output of this phase is an evaluated ontology, ready for roll-out into a productive environment. Support for these collaborative development steps within the ontology development methodology is crucial in order to meet the conflicting needs for ease of use and construction of complex ontology structures. We now illustrate OntoEdit's support for each of the supported steps. The examples shown are taken from the Swiss Life case study on skills management (cf. Chapter 12).

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Semantic Web