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Expertise bewerben und finden im Social Semantic Web

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Social Semantic Web

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Zusammenfassung

Im vorliegenden Beitrag diskutieren wir Rahmenbedingungen zur Kombination, Wiederverwendung und Erweiterung bestehender RDFVokabulare im Social Semantic Web. Hierbei konzentrieren wir uns auf das Anwendungsszenario des Auffindens und Bewerbens von Experten im Web oder Intranet. Wir präsentieren, wie RDF-Vokabulare einerseits und de facto Standardformate andererseits, die von täglich verwendeten Applikationen benutzt werden (z. B. vCard, iCal oder Dublin Core), kombiniert werden können, um konkrete Anwendungsfälle der Expertensuche und zum Management von Expertise zu lösen. Unser Fokus liegt darauf aufzuzeigen, dass für praktische Anwendungsszenarien nicht notwendigerweise neue Ontologien entwickelt werden müssen, sondern der Schlüssel vielmehr in der Integration von bestehenden, weit verbreiteten und sich ergänzenden Formaten zu einem kohärenten Netzwerk von Ontologien liegt. Dieser Ansatz garantiert sowohl direkte Anwendbarkeit von als auch niedrige Einstiegsbarrieren in Semantic Web-Technologien sowie einfache Integrierbarkeit in bestehende Applikationen. Die im Web verfügbaren und verwendeten RDFFormate decken zwar einen großen Bereich der Aspekte zur Beschreibung von Personen und Expertisen ab, zeigen aber auch signifikante Überlappungen. Bisher gibt es wenig systematische Ansätze, um diese Vokabulare zu verbinden, sei es in Form von allgemeingültigen Praktiken, die definieren, wann welches Format zu benutzen ist, oder in Form von Regeln, die Überlappungen zwischen einzelnen Formaten formalisieren. Der vorliegende Artikel analysiert, wie bestehende Formate zur Beschreibung von Personen, Organisationen und deren Expertise kombiniert und, wo nötig, erweitert werden können. Darüber hinaus diskutieren wir Regelsprachen zur Beschreibung von Formatüberlappungen sowie deren praktische Verwendbarkeit zur Erstellung eines Ontologie-Netzwerks zur Beschreibung von Experten.

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Polleres, A., Mochol, M. (2009). Expertise bewerben und finden im Social Semantic Web. In: Blumauer, A., Pellegrini, T. (eds) Social Semantic Web. X.media.press. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72216-8_10

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