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xWCPS: Bridging the Gap Between Array and Semi-structured Data

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Knowledge Engineering and Knowledge Management (EKAW 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8982))

Abstract

The ever growing amount of information collected by scientific instruments and the presence of descriptive metadata accompanying them calls for a unified way of querying over array and semi-structured data. We present xWCPS, a novel query language that bridges the path between these two different worlds, enhancing the expressiveness and user-friendliness of previous approaches.

This research has been partially supported by EC FP7 Work programme (2007-2013) under grant agreements n. 283610 “European Scalable Earth Science Service Environment (EarthServer)” and n. 262693 “International Network for Terrestrial Research and Monitoring in the Arctic (INTERACT)”.

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Author information

Authors and Affiliations

  1. Athena Research and Innovation Center, Artemidos 6 and Epidavrou, 15125, Maroussi, Greece

    Panagiotis Liakos, Panagiota Koltsida & George Kakaletris

  2. Jacobs University Bremen, Campus Ring 1, 28759, Bremen, Germany

    Peter Baumann

Authors
  1. Panagiotis Liakos
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  2. Panagiota Koltsida
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  3. George Kakaletris
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  4. Peter Baumann
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Corresponding author

Correspondence to Panagiotis Liakos .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Patrick Lambrix

  2. Aalto University, Espoo, Finland

    Eero Hyvönen

  3. Linköping University, Linköping, Sweden

    Eva Blomqvist

  4. STLab ISTC-CNR, Rome, Italy

    Valentina Presutti

  5. Southeast University, Nanjing, Jiangsu, China

    Guilin Qi

  6. University of Manchester, Manchester, United Kingdom

    Uli Sattler

  7. Indiana University Bloomington, Bloomington, Indiana, USA

    Ying Ding

  8. Fondazione Bruno Kessler, Trento, Italy

    Chiara Ghidini

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Liakos, P., Koltsida, P., Kakaletris, G., Baumann, P. (2015). xWCPS: Bridging the Gap Between Array and Semi-structured Data. In: Lambrix, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2014. Lecture Notes in Computer Science(), vol 8982. Springer, Cham. https://doi.org/10.1007/978-3-319-17966-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-17966-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17965-0

  • Online ISBN: 978-3-319-17966-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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