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An Infrastructure and Approach for Inferring Knowledge Over Big Data in the Vehicle Insurance Industry

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Advances in Big Data (INNS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 529))

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Abstract

In recent years, insurance organizations have turned their attention to tapping into massive amounts of data that are continuously produced across their IT ecosystem. Even though the concept of Big Data provides the needed infrastructure for efficient data management, especially in terms of storage and processing, the aspects of Value and Variety still remain a topic for further investigation. To this end, we propose an infrastructure that can be deployed on top of the legacy databases of insurance companies. The ultimate aim of this attempt is to provide an efficient manner to access data on-the-fly and derive new value. In our work, we propose a Property and Casualty ontology and then exploit an OBDA system in order to leverage its power.

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Notes

  1. 1.

    http://franz.com/about/press_room/ag-6.0_2-8-2016.lhtml.

  2. 2.

    http://ontop.inf.unibz.it/.

  3. 3.

    http://www.dis.uniroma1.it/~mastro/?q=node/2?.

  4. 4.

    http://stardog.com/.

  5. 5.

    http://teiid.jboss.org/.

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Author information

Authors and Affiliations

  1. High Performance Information Systems Laboratory (HPCLab), Computer Engineering and Informatics Department, School of Engineering, University of Patras, Building B, 26500, Patras-Rio, Greece

    Aikaterini K. Kalou & Dimitrios A. Koutsomitropoulos

Authors
  1. Aikaterini K. Kalou
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  2. Dimitrios A. Koutsomitropoulos
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Corresponding author

Correspondence to Aikaterini K. Kalou .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, Lancaster University , Lancaster, United Kingdom

    Plamen Angelov

  2. Data Engineering Lab, Dept. of Informatics, Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

  3. Lab of Forest Informatics (FiLAB), Democritus University of Thrace , Orestiada, Greece

    Lazaros Iliadis

  4. WPC Information Systems Faculty, Arizona State University , Tempe, Arizona, USA

    Asim Roy

  5. Electrical Engineering Dept, (ICA), Pontifical Catholic Univ of Rio de Janei , Rio de Janeiro, Rio de Janeiro, Brazil

    Marley Vellasco

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Kalou, A.K., Koutsomitropoulos, D.A. (2017). An Infrastructure and Approach for Inferring Knowledge Over Big Data in the Vehicle Insurance Industry. In: Angelov, P., Manolopoulos, Y., Iliadis, L., Roy, A., Vellasco, M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-319-47898-2_30

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  • DOI: https://doi.org/10.1007/978-3-319-47898-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47897-5

  • Online ISBN: 978-3-319-47898-2

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