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  • × type_ss:"a"
  • × author_ss:"Assem, M. van"
  • × theme_ss:"Wissensrepräsentation"
  1. Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004) 0.00
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    Abstract
    This paper describes a method for converting existing thesauri and related resources from their native format to RDF(S) and OWL. The method identifies four steps in the conversion process. In each step, decisions have to be taken with respect to the syntax or semantics of the resulting representation. Each step is supported through a number of guidelines. The method is illustrated through conversions of two large thesauri: MeSH and WordNet.
    Type
    a
  2. Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004) 0.00
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    Abstract
    Ontologies will play a central role in the development of the Semantic Web. It is unrealistic to assume that such ontologies will be developed from scratch. Rather, we assume that existing resources such as thesauri and lexical data bases will be reused in the development of ontologies for the Semantic Web. In this paper we describe a method for converting existing source material to a representation that is compatible with Semantic Web languages such as RDF(S) and OWL. The method is illustrated with three case studies: converting Wordnet, AAT and MeSH to RDF(S) and OWL.
    Type
    a
  3. Assem, M. van: Converting and integrating vocabularies for the Semantic Web (2010) 0.00
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    Abstract
    This thesis focuses on conversion of vocabularies for representation and integration of collections on the Semantic Web. A secondary focus is how to represent metadata schemas (RDF Schemas representing metadata element sets) such that they interoperate with vocabularies. The primary domain in which we operate is that of cultural heritage collections. The background worldview in which a solution is sought is that of the Semantic Web research paradigmwith its associated theories, methods, tools and use cases. In other words, we assume the SemanticWeb is in principle able to provide the context to realize interoperable collections. Interoperability is dependent on the interplay between representations and the applications that use them. We mean applications in the widest sense, such as "search" and "annotation". These applications or tasks are often present in software applications, such as the E-Culture application. It is therefore necessary that applications requirements on the vocabulary representation are met. This leads us to formulate the following problem statement: HOW CAN EXISTING VOCABULARIES BE MADE AVAILABLE TO SEMANTIC WEB APPLICATIONS?
    We refine the problem statement into three research questions. The first two focus on the problem of conversion of a vocabulary to a Semantic Web representation from its original format. Conversion of a vocabulary to a representation in a Semantic Web language is necessary to make the vocabulary available to SemanticWeb applications. In the last question we focus on integration of collection metadata schemas in a way that allows for vocabulary representations as produced by our methods. Academisch proefschrift ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, Dutch Research School for Information and Knowledge Systems.
    Type
    a
  4. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.00
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    Abstract
    Companies, governmental agencies and scientists produce a large amount of quantitative (research) data, consisting of measurements ranging from e.g. the surface temperatures of an ocean to the viscosity of a sample of mayonnaise. Such measurements are stored in tables in e.g. spreadsheet files and research reports. To integrate and reuse such data, it is necessary to have a semantic description of the data. However, the notation used is often ambiguous, making automatic interpretation and conversion to RDF or other suitable format diffiult. For example, the table header cell "f(Hz)" refers to frequency measured in Hertz, but the symbol "f" can also refer to the unit farad or the quantities force or luminous flux. Current annotation tools for this task either work on less ambiguous data or perform a more limited task. We introduce new disambiguation strategies based on an ontology, which allows to improve performance on "sloppy" datasets not yet targeted by existing systems.
    Type
    a