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Authors: Iván García ; Miguel A. Martínez-Prieto ; Anibal Bregón ; Pedro C. Álvarez and Fernando Díaz

Affiliation: Universidad de Valladolid, Spain

Keyword(s): Data Lake, ADS-B, Big Data, Flight Analytics, Hadoop.

Related Ontology Subjects/Areas/Topics: Big Data ; Data Engineering ; Data Management and Quality

Abstract: The dramatic growth in the air traffic levels witnessed during the last two decades has increased the interest for optimizing the Air Traffic Management (ATM) systems. The main objective is being able to cope with the sustained air traffic growth under safe, economic, efficient and environmental friendly working conditions. The ADS-B (Automatic Dependent Surveillance - Broadcast) system is part of the new air traffic control systems, since it allows to substitute the secondary radar with cheaper ground stations that, at the same time, provide more accurate real-time positioning information. However, this system generates a large volume of data that, when combined with other flight-related data, such as flight plans or weather reports, faces scalability issues. This paper introduces an (on-going) Data Lake based architecture which allows the full ADS-B data life-cycle to be supported in a scalable and cost-effective way using technologies from the Apache Hadoop ecosystem.

CC BY-NC-ND 4.0

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Paper citation in several formats:
García, I.; Martínez-Prieto, M.; Bregón, A.; Álvarez, P. and Díaz, F. (2017). Towards a Scalable Architecture for Flight Data Management. In Proceedings of the 6th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-255-4; ISSN 2184-285X, SciTePress, pages 263-268. DOI: 10.5220/0006473402630268

@conference{data17,
author={Iván García. and Miguel A. Martínez{-}Prieto. and Anibal Bregón. and Pedro C. Álvarez. and Fernando Díaz.},
title={Towards a Scalable Architecture for Flight Data Management},
booktitle={Proceedings of the 6th International Conference on Data Science, Technology and Applications - DATA},
year={2017},
pages={263-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006473402630268},
isbn={978-989-758-255-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Data Science, Technology and Applications - DATA
TI - Towards a Scalable Architecture for Flight Data Management
SN - 978-989-758-255-4
IS - 2184-285X
AU - García, I.
AU - Martínez-Prieto, M.
AU - Bregón, A.
AU - Álvarez, P.
AU - Díaz, F.
PY - 2017
SP - 263
EP - 268
DO - 10.5220/0006473402630268
PB - SciTePress