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  • × theme_ss:"Wissensrepräsentation"
  • × theme_ss:"Semantische Interoperabilität"
  1. Reasoning Web : Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures (2017) 0.03 
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    Abstract
    This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.
    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
    RSWK
    Ontologie <Wissensverarbeitung> / Semantic Web
    Series
    Lecture Notes in Computer Scienc;10370 )(Information Systems and Applications, incl. Internet/Web, and HCI
    Subject
    Ontologie <Wissensverarbeitung> / Semantic Web
    Theme
    Semantic Web
  2. Burstein, M.; McDermott, D.V.: Ontology translation for interoperability among Semantic Web services (2005) 0.02 
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    Abstract
    Research on semantic web services promises greater interoperability among software agents and web services by enabling content-based automated service discovery and interaction and by utilizing. Although this is to be based on use of shared ontologies published on the semantic web, services produced and described by different developers may well use different, perhaps partly overlapping, sets of ontologies. Interoperability will depend on ontology mappings and architectures supporting the associated translation processes. The question we ask is, does the traditional approach of introducing mediator agents to translate messages between requestors and services work in such an open environment? This article reviews some of the processing assumptions that were made in the development of the semantic web service modeling ontology OWL-S and argues that, as a practical matter, the translation function cannot always be isolated in mediators. Ontology mappings need to be published on the semantic web just as ontologies themselves are. The translation for service discovery, service process model interpretation, task negotiation, service invocation, and response interpretation may then be distributed to various places in the architecture so that translation can be done in the specific goal-oriented informational contexts of the agents performing these processes. We present arguments for assigning translation responsibility to particular agents in the cases of service invocation, response translation, and match- making.
  3. Koutsomitropoulos, D.A.; Solomou, G.D.; Alexopoulos, A.D.; Papatheodorou, T.S.: Semantic metadata interoperability and inference-based querying in digital repositories (2009) 0.02 
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    Abstract
    Metadata applications have evolved in time into highly structured "islands of information" about digital resources, often bearing a strong semantic interpretation. Scarcely however are these semantics being communicated in machine readable and understandable ways. At the same time, the process for transforming the implied metadata knowledge into explicit Semantic Web descriptions can be problematic and is not always evident. In this article we take upon the well-established Dublin Core metadata standard as well as other metadata schemata, which often appear in digital repositories set-ups, and suggest a proper Semantic Web OWL ontology. In this process the authors cope with discrepancies and incompatibilities, indicative of such attempts, in novel ways. Moreover, we show the potential and necessity of this approach by demonstrating inferences on the resulting ontology, instantiated with actual metadata records. The authors conclude by presenting a working prototype that provides for inference-based querying on top of digital repositories.
    Theme
    Semantic Web
  4. Wenige, L.; Ruhland, J.: Similarity-based knowledge graph queries for recommendation retrieval (2019) 0.01 
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    Abstract
    Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].
    Content
    Vgl.: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval. Vgl. auch: http://semantic-web-journal.net/content/similarity-based-knowledge-graph-queries-recommendation-retrieval-1.
    Source
    Semantic Web. 10(2019) 6, S.1007-1037
  5. Soergel, D.: Towards a relation ontology for the Semantic Web (2011) 0.01 
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    Abstract
    The Semantic Web consists of data structured for use by computer programs, such as data sets made available under the Linked Open Data initiative. Much of this data is structured following the entity-relationship model encoded in RDF for syntactic interoperability. For semantic interoperability, the semantics of the relationships used in any given dataset needs to be made explicit. Ultimately this requires an inventory of these relationships structured around a relation ontology. This talk will outline a blueprint for such an inventory, including a format for the description/definition of binary and n-ary relations, drawing on ideas put forth in the classification and thesaurus community over the last 60 years, upper level ontologies, systems like FrameNet, the Buffalo Relation Ontology, and an analysis of linked data sets.
  6. Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.01 
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    Abstract
    The lack of standardization in the production, organization and dissemination of information in documentation centers and institutions alike, as a result from the digitization of collections and their availability on the internet has called for integration efforts. The sheer availability of multimedia content has fostered the development of many distinct and, most of the time, independent metadata standards for its description. This study aims at presenting and comparing the existing standards of metadata, vocabularies and ontologies for multimedia annotation and also tries to offer a synthetic overview of its main strengths and weaknesses, aiding efforts for semantic integration and enhancing the findability of available multimedia resources on the web. We also aim at unveiling the characteristics that could, should and are perhaps not being highlighted in the characterization of multimedia resources.
  7. Sigel, A.: Wissensorganisation, Topic Maps und Ontology Engineering : Die Verbindung bewährter Begriffsstrukturen mit aktueller XML Technologie (2004) 0.01 
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    Abstract
    Wie können begriffliche Strukturen an Topic Maps angebunden werden? Allgemeiner. Wie kann die Wissensorganisation dazu beitragen, dass im Semantic Web eine begriffsbasierte Infrastruktur verfügbar ist? Dieser Frage hat sich die Wissensorganisation bislang noch nicht wirklich angenommen. Insgesamt ist die Berührung zwischen semantischen Wissenstechnologien und wissensorganisatorischen Fragestellungen noch sehr gering, obwohl Begriffsstrukturen, Ontologien und Topic Maps grundsätzlich gut zusammenpassen und ihre gemeinsame Betrachtung Erkenntnisse für zentrale wissensorganisatorische Fragestellungen wie z.B. semantische Interoperabilität und semantisches Retrieval erwarten lässt. Daher motiviert und skizziert dieser Beitrag die Grundidee, nach der es möglich sein müsste, eine Sprache zur Darstellung von Begriffsstrukturen in der Wissensorganisation geeignet mit Topic Maps zu verbinden. Eine genauere Untersuchung und Implementation stehen allerdings weiterhin aus. Speziell wird vermutet, dass sich der Concepto zugrunde liegende Formalismus CLF (Concept Language Formalism) mit Topic Maps vorteilhaft abbilden lässt 3 Damit können Begriffs- und Themennetze realisiert werden, die auf expliziten Begriffssystemen beruhen. Seitens der Wissensorganisation besteht die Notwendigkeit, sich mit aktuellen Entwicklungen auf dem Gebiet des Semantic Web und ontology engineering vertraut zu machen, aber auch die eigene Kompetenz stärker aktiv in diese Gebiete einzubringen. Damit dies geschehen kann, führt dieser Beitrag zum besseren Verständnis zunächst aus Sicht der Wissensorganisation knapp in Ontologien und Topic Maps ein und diskutiert wichtige Überschneidungsbereiche.
  8. Panzer, M.; Zeng, M.L.: Modeling classification systems in SKOS : Some challenges and best-practice (2009) 0.01 
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    Abstract
    Representing classification systems on the web for publication and exchange continues to be a challenge within the SKOS framework. This paper focuses on the differences between classification schemes and other families of KOS (knowledge organization systems) that make it difficult to express classifications without sacrificing a large amount of their semantic richness. Issues resulting from the specific set of relationships between classes and topics that defines the basic nature of any classification system are discussed. Where possible, different solutions within the frameworks of SKOS and OWL are proposed and examined.
  9. Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.01 
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    Source
    Proceedings of the Sixth Workshop on Scripting and Development for the Semantic Web, Crete, Greece, May 31, 2010, CEUR Workshop Proceedings, SFSW - http://ceur-ws.org/Vol-699/Paper2.pdf
  10. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.01 
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    Date
    3.12.2016 18:39:22
  11. Widhalm, R.; Mueck, T.A.: Merging topics in well-formed XML topic maps (2003) 0.01 
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    Source
    The Semantic Web - ISWC 2003. Eds. D. Fensel et al
  12. Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.01 
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    Source
    Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
  13. Ehrig, M.; Studer, R.: Wissensvernetzung durch Ontologien (2006) 0.01 
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    Source
    Semantic Web: Wege zur vernetzten Wissensgesellschaft. Hrsg.: T. Pellegrini, u. A. Blumauer
  14. Peponakis, M.; Mastora, A.; Kapidakis, S.; Doerr, M.: Expressiveness and machine processability of Knowledge Organization Systems (KOS) : an analysis of concepts and relations (2020) 0.01 
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    Abstract
    This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.

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