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The Identification and Creation of Ontologies for the Use in Law Enforcement AI Solutions – MAGNETO Platform Use Case

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Computational Collective Intelligence (ICCCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11684))

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Abstract

Every single day more and more organizations face the challenge of finding a way to support their conduct with data. The flooding amounts of data currently available vastly outweigh human capabilities, thus Big Data processing becomes a pressing issue. This problem is especially prevailing for Law Enforcement Agencies (LEAs), where massive amounts of critical data are collected from heterogenous sources, often by various entities in different countries. Ontologies have been developed into a predominant technique for establishing semantic interoperability among heterogeneous systems which transact information. In this paper we propose the Magneto ontology – a solution built as a crucial part of the Magneto project. It has been developed on top of well-established ontologies dealing with people, events and security incidents, bearing in mind the heterogenous nature of the myriad of data sources as the starting point. Examples of the building blocks, a classification of the sources of data, an overview of the application in a specific use scenario and a discussion on the future use of the ontology will be given.

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Acknowledgement

This work has been performed under the H2020 786629 project MAGNETO, which has received funding from the European Union’s Horizon 2020 Programme. This paper reflects only the authors’ view, and the European Commission is not liable to any use that may be made of the information contained therein.

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Authors and Affiliations

  1. ITTI Sp. z o.o., Poznan, Poland

    Rafal Kozik, Michal Choras & Marek Pawlicki

  2. Fraunhofer IOSB, Karlsruhe, Germany

    Dirk Pallmer, Wilmuth Mueller & Ernst-Josef Behmer

  3. Institute of Communication and Computer Systems (ICCS), Athens, Greece

    Ioannis Loumiotis & Konstantinos Demestichas

  4. University of Science and Technology, UTP, Bydgoszcz, Poland

    Rafal Kozik, Michal Choras, Marek Pawlicki & Witold Hołubowicz

  5. Thales Research & Technology, Palaiseau, France

    Roxana Horincar, Claire Laudy & David Faure

Authors
  1. Rafal Kozik
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  2. Michal Choras
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  3. Marek Pawlicki
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  4. Witold Hołubowicz
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  5. Dirk Pallmer
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  6. Wilmuth Mueller
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  7. Ernst-Josef Behmer
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  8. Ioannis Loumiotis
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  9. Konstantinos Demestichas
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  10. Roxana Horincar
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  11. Claire Laudy
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  12. David Faure
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Corresponding author

Correspondence to Marek Pawlicki .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. University of Pau and Pays de l'Adour, Pau, France

    Richard Chbeir

  3. University of Pau and Pays de l'Adour, Pau, France

    Ernesto Exposito

  4. University of Pau and Pays de l'Adour, Pau, France

    Philippe Aniorté

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Kozik, R. et al. (2019). The Identification and Creation of Ontologies for the Use in Law Enforcement AI Solutions – MAGNETO Platform Use Case. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_29

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  • DOI: https://doi.org/10.1007/978-3-030-28374-2_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28373-5

  • Online ISBN: 978-3-030-28374-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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