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  • × theme_ss:"Semantic Web"
  1. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.05 
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    Date
    31. 7.2010 16:58:22
    Source
    Semantic digital libraries. Eds.: S.R. Kruk, B. McDaniel
  2. Thuraisingham, B.: XML databases and the semantic Web (2002) 0.03 
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  3. Shoffner, M.; Greenberg, J.; Kramer-Duffield, J.; Woodbury, D.: Web 2.0 semantic systems : collaborative learning in science (2008) 0.03 
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    Abstract
    The basic goal of education within a discipline is to transform a novice into an expert. This entails moving the novice toward the "semantic space" that the expert inhabits-the space of concepts, meanings, vocabularies, and other intellectual constructs that comprise the discipline. Metadata is significant to this goal in digitally mediated education environments. Encoding the experts' semantic space not only enables the sharing of semantics among discipline scientists, but also creates an environment that bridges the semantic gap between the common vocabulary of the novice and the granular descriptive language of the seasoned scientist (Greenberg, et al, 2005). Developments underlying the Semantic Web, where vocabularies are formalized in the Web Ontology Language (OWL), and Web 2.0 approaches of user-generated folksonomies provide an infrastructure for linking vocabulary systems and promoting group learning via metadata literacy. Group learning is a pedagogical approach to teaching that harnesses the phenomenon of "collective intelligence" to increase learning by means of collaboration. Learning a new semantic system can be daunting for a novice, and yet it is integral to advance one's knowledge in a discipline and retain interest. These ideas are key to the "BOT 2.0: Botany through Web 2.0, the Memex and Social Learning" project (Bot 2.0).72 Bot 2.0 is a collaboration involving the North Carolina Botanical Garden, the UNC SILS Metadata Research center, and the Renaissance Computing Institute (RENCI). Bot 2.0 presents a curriculum utilizing a memex as a way for students to link and share digital information, working asynchronously in an environment beyond the traditional classroom. Our conception of a memex is not a centralized black box but rather a flexible, distributed framework that uses the most salient and easiest-to-use collaborative platforms (e.g., Facebook, Flickr, wiki and blog technology) for personal information management. By meeting students "where they live" digitally, we hope to attract students to the study of botanical science. A key aspect is to teach students scientific terminology and about the value of metadata, an inherent function in several of the technologies and in the instructional approach we are utilizing. This poster will report on a study examining the value of both folksonomies and taxonomies for post-secondary college students learning plant identification. Our data is drawn from a curriculum involving a virtual independent learning portion and a "BotCamp" weekend at UNC, where students work with digital plan specimens that they have captured. Results provide some insight into the importance of collaboration and shared vocabulary for gaining confidence and for student progression from novice to expert in botany.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  4. RDF Semantics (2004) 0.02 
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    Editor
    Hayes, P. u. B. McBride
  5. Call, A.; Gottlob, G.; Pieris, A.: ¬The return of the entity-relationship model : ontological query answering (2012) 0.02 
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    Abstract
    The Entity-Relationship (ER) model is a fundamental formalism for conceptual modeling in database design; it was introduced by Chen in his milestone paper, and it is now widely used, being flexible and easily understood by practitioners. With the rise of the Semantic Web, conceptual modeling formalisms have gained importance again as ontology formalisms, in the Semantic Web parlance. Ontologies and conceptual models are aimed at representing, rather than the structure of data, the domain of interest, that is, the fragment of the real world that is being represented by the data and the schema. A prominent formalism for modeling ontologies are Description Logics (DLs), which are decidable fragments of first-order logic, particularly suitable for ontological modeling and querying. In particular, DL ontologies are sets of assertions describing sets of objects and (usually binary) relations among such sets, exactly in the same fashion as the ER model. Recently, research on DLs has been focusing on the problem of answering queries under ontologies, that is, given a query q, an instance B, and an ontology X, answering q under B and amounts to compute the answers that are logically entailed from B by using the assertions of X. In this context, where data size is usually large, a central issue the data complexity of query answering, i.e., the computational complexity with respect to the data set B only, while the ontology X and the query q are fixed.
  6. Dellschaft, K.; Hachenberg, C.: Repräsentation von Wissensorganisationssystemen im Semantic Web : ein Best Practice Guide (2011) 0.02 
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    Abstract
    In diesem Dokument sollen Begriffe, Prinzipien und Methoden vorgestellt werden, die sich als hilfreich bei der Erstellung von Semantic Web konformen Repräsentationen von Wissensorganisationssystemen (KOS) erwiesen haben, wie z. B. Thesauri und Klassifikationssysteme. Das Dokument richtet sich an Organisationen wie z. B. Bibliotheken, die ihre traditionellen Wissensorganisationssysteme im Rahmen des Semantic Web veröffentlichen wollen. Die in diesem Dokument beschriebenen Vorgehensweisen und Prinzipien sind nicht als normativ anzusehen. Sie sollen nur dabei helfen, von bisher gemachten Erfahrungen zu profitieren und einen leichteren Einstieg in die wichtigsten Begriffichkeiten und Techniken des Semantic Web zu bekommen. An vielen Stellen wird zudem auf weiterführende Literatur zum Thema und auf relevante Standards und Spezifikationen aus dem Bereich des Semantic Web hingewiesen.
  7. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.02 
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  8. Wohlkinger, B.; Pellegrini, T.: Semantic Systems Technologiepolitik in der Europäischen Union (2006) 0.02 
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  9. Granitzer, M.: Statistische Verfahren der Textanalyse (2006) 0.02 
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    Abstract
    Der vorliegende Artikel bietet einen Überblick über statistische Verfahren der Textanalyse im Kontext des Semantic Webs. Als Einleitung erfolgt die Diskussion von Methoden und gängigen Techniken zur Vorverarbeitung von Texten wie z. B. Stemming oder Part-of-Speech Tagging. Die so eingeführten Repräsentationsformen dienen als Basis für statistische Merkmalsanalysen sowie für weiterführende Techniken wie Information Extraction und maschinelle Lernverfahren. Die Darstellung dieser speziellen Techniken erfolgt im Überblick, wobei auf die wichtigsten Aspekte in Bezug auf das Semantic Web detailliert eingegangen wird. Die Anwendung der vorgestellten Techniken zur Erstellung und Wartung von Ontologien sowie der Verweis auf weiterführende Literatur bilden den Abschluss dieses Artikels.
  10. Voß, J.: Vom Social Tagging zum Semantic Tagging (2008) 0.02 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  11. Semantische Technologien : Grundlagen - Konzepte - Anwendungen (2012) 0.02 
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    Content
    Inhalt: 1. Einleitung (A. Dengel, A. Bernardi) 2. Wissensrepräsentation (A. Dengel, A. Bernardi, L. van Elst) 3. Semantische Netze, Thesauri und Topic Maps (O. Rostanin, G. Weber) 4. Das Ressource Description Framework (T. Roth-Berghofer) 5. Ontologien und Ontologie-Abgleich in verteilten Informationssystemen (L. van Elst) 6. Anfragesprachen und Reasoning (M. Sintek) 7. Linked Open Data, Semantic Web Datensätze (G.A. Grimnes, O. Hartig, M. Kiesel, M. Liwicki) 8. Semantik in der Informationsextraktion (B. Adrian, B. Endres-Niggemeyer) 9. Semantische Suche (K. Schumacher, B. Forcher, T. Tran) 10. Erklärungsfähigkeit semantischer Systeme (B. Forcher, T. Roth-Berghofer, S. Agne) 11. Semantische Webservices zur Steuerung von Prooduktionsprozessen (M. Loskyll, J. Schlick, S. Hodeck, L. Ollinger, C. Maxeiner) 12. Wissensarbeit am Desktop (S. Schwarz, H. Maus, M. Kiesel, L. Sauermann) 13. Semantische Suche für medizinische Bilder (MEDICO) (M. Möller, M. Sintek) 14. Semantische Musikempfehlungen (S. Baumann, A. Passant) 15. Optimierung von Instandhaltungsprozessen durch Semantische Technologien (P. Stephan, M. Loskyll, C. Stahl, J. Schlick)
  12. Spree, U.; Feißt, N.; Lühr, A.; Piesztal, B.; Schroeder, N.; Wollschläger, P.: Semantic search : State-of-the-Art-Überblick zu semantischen Suchlösungen im WWW (2011) 0.02 
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  13. Dextre Clarke, S.G.: Challenges and opportunities for KOS standards (2007) 0.02 
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    Date
    22. 9.2007 15:41:14
  14. Liang, A.; Salokhe, G.; Sini, M.; Keizer, J.: Towards an infrastructure for semantic applications : methodologies for semantic integration of heterogeneous resources (2006) 0.01 
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    Abstract
    The semantic heterogeneity presented by Web information in the Agricultural domain presents tremendous information retrieval challenges. This article presents work taking place at the Food and Agriculture Organizations (FAO) which addresses this challenge. Based on the analysis of resources in the domain of agriculture, this paper proposes (a) an application profile (AP) for dealing with the problem of heterogeneity originating from differences in terminologies, domain coverage, and domain modelling, and (b) a root application ontology (AAO) based on the application profile which can serve as a basis for extending knowledge of the domain. The paper explains how even a small investment in the enhancement of relations between vocabularies, both metadata and domain-specific, yields a relatively large return on investment.
  15. Vatant, B.: Porting library vocabularies to the Semantic Web, and back : a win-win round trip (2010) 0.01 
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  16. Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004) 0.01 
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  17. Glimm, B.; Hogan, A.; Krötzsch, M.; Polleres, A.: OWL: Yet to arrive on the Web of Data? (2012) 0.01 
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  18. Zapilko, B.; Sure, Y.: Neue Möglichkeiten für die Wissensorganisation durch die Kombination von Digital Library Verfahren mit Standards des Semantic Web (2013) 0.01 
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  19. Sartini, B.; Erp, M. van; Gangemi, A.: Marriage is a peach and a chalice : modelling cultural symbolism on the Semantic Web (2021) 0.01 
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    Date
    22. 9.2007 15:41:14

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