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Mapping Data Driven and Upper Level Ontology

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6304))

Abstract

The Linking Open data (LOD) [1]initiative aims to facilitate the emergence of a web of linked data by publishing and interlinking open data on the web in RDF. The access to these data becomes increasingly a challenge. This paper presents an innovative method for retrieving facts from vast amounts of data by using an upper level ontology (PROTON) [2] as an access interface. FactForge, the largest and most heterogeneous body of general factual knowledge that was ever used for logical inference served to develop and test the method of mapping ontologies.

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References

  1. World Wide Web Consortium (W3C): Linking Open Data. W3C SWEO project home page as of January 2010 (2010), http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData

  2. Terziev, I., Kiryakov, A., Manov, D.: D.1.8.1 Base upper-level ontology (BULO) Guidance, Deliverable of EU-IST Project IST – 2003 – 506826 SEKT (2005)

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  4. Welty, C., Guarino, N.: Supporting Ontological Analysis of Taxonomic Relationships. Data and Knowledge Engineering (2001)

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Author information

Authors and Affiliations

  1. Ontotext AD, Tsarigradsko Chosse 135, Sofia, 1784, Bulgaria

    Mariana Damova, Svetoslav Petrov & Kiril Simov

Authors
  1. Mariana Damova
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  2. Svetoslav Petrov
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  3. Kiril Simov
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Editor information

Editors and Affiliations

  1. Winston-Salem State University, 601 S. Martin Luther King Drive, NC 27110, Winston Salem, USA

    Darina Dicheva

  2. Institute of Information Technologies, Bulgarian Academy of Sciences, 29A Acad. Bonchev Str., 1113, Sofia, Bulgaria

    Danail Dochev

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© 2010 Springer-Verlag Berlin Heidelberg

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Damova, M., Petrov, S., Simov, K. (2010). Mapping Data Driven and Upper Level Ontology. In: Dicheva, D., Dochev, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2010. Lecture Notes in Computer Science(), vol 6304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15431-7_31

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  • DOI: https://doi.org/10.1007/978-3-642-15431-7_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15430-0

  • Online ISBN: 978-3-642-15431-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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