Journal on Data Semantics XII
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal defi
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Stefano Spaccapietra (Ed.)
Journal on Data Semantics XII
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Volume Editor Stefano Spaccapietra École Polytechnique Fédérale de Lausanne EPFL-IC, Database Laboratory 1015 Lausanne, Switzerland E-mail: [email protected]
Library of Congress Control Number: Applied for CR Subject Classification (1998): H.2, H.4, C.2, H.3, I.2 LNCS Sublibrary: SL 3 – Information Systems and Application, incl. Internet/Web and HCI ISSN ISSN ISBN-10 ISBN-13
0302-9743 (Lecture Notes in Computer Science) 1861-2032 (Journal on Data Semantics) 3-642-00684-1 Springer Berlin Heidelberg New York 978-3-642-00684-5 Springer Berlin Heidelberg New York
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The LNCS Journal on Data Semantics
Computerized information handling has changed its focus from centralized data management systems to decentralized data-exchange facilities. Modern distribution channels, such as high-speed Internet networks and wireless communication infrastructure, provide reliable technical support for data distribution and data access, materializing the new, popular idea that data may be available to anybody, anywhere, anytime. However, providing huge amounts of data on request often turns into a counterproductive service, making the data useless because of poor relevance or inappropriate level of detail. Semantic knowledge is the essential missing piece that allows the delivery of information that matches user requirement
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