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  • × theme_ss:"Semantic Web"
  1. Papadakis, I. et al.: Highlighting timely information in libraries through social and semantic Web technologies (2016) 0.21
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    Language
    e
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  2. Reasoning Web : Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures (2017) 0.16
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    Content
    Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining
    Editor
    Ianni, G. et al.
    Language
    e
  3. Metadata and semantics research : 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings (2016) 0.15
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    Editor
    Garoufallou, E. et al.
    Language
    e
  4. Subirats, I.; Prasad, A.R.D.; Keizer, J.; Bagdanov, A.: Implementation of rich metadata formats and demantic tools using DSpace (2008) 0.11
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    Abstract
    This poster explores the customization of DSpace to allow the use of the AGRIS Application Profile metadata standard and the AGROVOC thesaurus. The objective is the adaptation of DSpace, through the least invasive code changes either in the form of plug-ins or add-ons, to the specific needs of the Agricultural Sciences and Technology community. Metadata standards such as AGRIS AP, and Knowledge Organization Systems such as the AGROVOC thesaurus, provide mechanisms for sharing information in a standardized manner by recommending the use of common semantics and interoperable syntax (Subirats et al., 2007). AGRIS AP was created to enhance the description, exchange and subsequent retrieval of agricultural Document-like Information Objects (DLIOs). It is a metadata schema which draws from Metadata standards such as Dublin Core (DC), the Australian Government Locator Service Metadata (AGLS) and the Agricultural Metadata Element Set (AgMES) namespaces. It allows sharing of information across dispersed bibliographic systems (FAO, 2005). AGROVOC68 is a multilingual structured thesaurus covering agricultural and related domains. Its main role is to standardize the indexing process in order to make searching simpler and more efficient. AGROVOC is developed by FAO (Lauser et al., 2006). The customization of the DSpace is taking place in several phases. First, the AGRIS AP metadata schema was mapped onto the metadata DSpace model, with several enhancements implemented to support AGRIS AP elements. Next, AGROVOC will be integrated as a controlled vocabulary accessed through a local SKOS or OWL file. Eventually the system will be configurable to access AGROVOC through local files or remotely via webservices. Finally, spell checking and tooltips will be incorporated in the user interface to support metadata editing. Adapting DSpace to support AGRIS AP and annotation using the semantically-rich AGROVOC thesaurus transform DSpace into a powerful, domain-specific system for annotation and exchange of bibliographic metadata in the agricultural domain.
    Language
    e
    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
  5. Stamou, G.; Chortaras, A.: Ontological query answering over semantic data (2017) 0.10
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    Language
    e
    Source
    Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al
  6. Leskinen, P.; Hyvönen, E.: Extracting genealogical networks of linked data from biographical texts (2019) 0.09
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    Language
    e
    Source
    ¬The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Ed.: P. Hitzler et al
  7. Lukasiewicz, T.: Uncertainty reasoning for the Semantic Web (2017) 0.09
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    Language
    e
    Source
    Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al
  8. Blanco, L.; Bronzi, M.; Crescenzi, V.; Merialdo, P.; Papotti, P.: Flint: from Web pages to probabilistic semantic data (2012) 0.09
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    Abstract
    The Web is a surprisingly extensive source of information: it offers a huge number of sites containing data about a disparate range of topics. Although Web pages are built for human fruition, not for automatic processing of the data, we observe that an increasing number of Web sites deliver pages containing structured information about recognizable concepts, relevant to specific application domains, such as movies, finance, sport, products, etc. The development of scalable techniques to discover, extract, and integrate data from fairly structured large corpora available on the Web is a challenging issue, because to face the Web scale, these activities should be accomplished automatically by domain-independent techniques. To cope with the complexity and the heterogeneity of Web data, state-of-the-art approaches focus on information organized according to specific patterns that frequently occur on the Web. Meaningful examples are WebTables, which focuses on data published in HTML tables, and information extraction systems, such as TextRunner, which exploits lexical-syntactic patterns. As noticed by Cafarella et al., even if a small fraction of the Web is organized according to these patterns, due to the Web scale, the amount of data involved is impressive. In this chapter, we focus on methods and techniques to wring out value from the data delivered by large data-intensive Web sites.
    Language
    e
    Source
    Semantic search over the Web. Eds.: R. De Virgilio, et al
  9. Shoffner, M.; Greenberg, J.; Kramer-Duffield, J.; Woodbury, D.: Web 2.0 semantic systems : collaborative learning in science (2008) 0.08
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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.
    Language
    e
    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
  10. Assumpção, F.S.; Santarem Segundo, J.E.; Ventura Amorim da Costa Santos, P.L.: RDA element sets and RDA value vocabularies : vocabularies for resource description in the Semantic Web (2015) 0.08
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    Language
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    Source
    Metadata and semantics research: 9th Research Conference, MTSR 2015, Manchester, UK, September 9-11, 2015, Proceedings. Eds.: E. Garoufallou et al
  11. Metadata and semantics research : 9th Research Conference, MTSR 2015, Manchester, UK, September 9-11, 2015, Proceedings (2015) 0.08
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    Editor
    Garoufallou, E. et al.
    Language
    e
  12. Auer, S.; Bizer, C.; Kobilarov, G.; Lehmann, J.; Cyganiak, R.; Ives, Z.: DBpedia: a nucleus for a Web of open data (2007) 0.08
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    Language
    e
    Source
    ¬The Semantic Web : 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007 : proceedings. Ed.: Karl Aberer et al
  13. Semantic Web services challenge : results from the first year (2009) 0.08
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    Editor
    Petrie, C. et al.
    Language
    e
  14. Cali, A.: Ontology querying : datalog strikes back (2017) 0.08
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    Language
    e
    Source
    Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al
  15. Sequeda, J.F.: Integrating relational databases with the Semantic Web : a reflection (2017) 0.08
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    e
    Source
    Reasoning Web: Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures. Eds.: Ianni, G. et al
  16. Hyvönen, E.; Leskinen, P.; Tamper, M.; Keravuori, K.; Rantala, H.; Ikkala, E.; Tuominen, J.: BiographySampo - publishing and enriching biographies on the Semantic Web for digital humanities research (2019) 0.07
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    Footnote
    Volltext unter: hyvonen-et-al-eswc-2019.pdf.
    Language
    e
  17. Allocca, C.; Aquin, M.d'; Motta, E.: Impact of using relationships between ontologies to enhance the ontology search results (2012) 0.06
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    Language
    e
    Source
    9th Extended Semantic Web Conference (ESWC), 2012-05-27/2012-05-31 in Hersonissos, Crete, Greece. Eds.: Elena Simperl et al
  18. Zenz, G.; Zhou, X.; Minack, E.; Siberski, W.; Nejdl, W.: Interactive query construction for keyword search on the Semantic Web (2012) 0.06
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    e
    Source
    Semantic search over the Web. Eds.: R. De Virgilio, et al
  19. Bergamaschi, S.; Domnori, E.; Guerra, F.; Rota, S.; Lado, R.T.; Velegrakis, Y.: Understanding the semantics of keyword queries on relational data without accessing the instance (2012) 0.06
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    Language
    e
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    Semantic search over the Web. Eds.: R. De Virgilio, et al
  20. Ioannou, E.; Nejdl, W.; Niederée, C.; Velegrakis, Y.: Embracing uncertainty in entity linking (2012) 0.06
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    Language
    e
    Source
    Semantic search over the Web. Eds.: R. De Virgilio, et al

Years

Languages

  • e 255
  • d 12
  • f 1
  • More… Less…

Types

  • a 158
  • el 79
  • m 51
  • s 21
  • n 10
  • x 5
  • r 2
  • More… Less…

Subjects

Classifications