The maritime domain encompasses a diverse set of heterogeneous large-scale data about ships, routes and trajectories, port operations, fishing and maritime biodiversity, oceans, and environmental conditions. Performing timely and cost-effective analytical processing of this data is a key priority for maritime stakeholders in order to extract deep insights and automate various decision-making processes that will lead to optimising marine transport, improving fuel efficiency, and optimising port operational efficiency among others. The maritime data value chain defines the series of activities needed to appropriately manage data during the entire life-cycle of data as well as to extract value and useful insights from maritime data. The four key activities identified are: (1) data acquisition for collecting the data across different and geographically-dispersed data sources; (2) data pre-processing for transforming, integrating, and assessing the quality of the data; (3) data storage for storing data in a persistent and scalable way; and (4) data usage for processing the data and extracting value. This chapter provides an extensive overview of the maritime data value chain and discusses state-of-the-art technological solutions for managing and processing maritime data in efficient and effective ways.


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    Titel :

    Big Maritime Data Management


    Weitere Titelangaben:

    Progress in IS


    Beteiligte:
    Lind, Mikael (Herausgeber:in) / Michaelides, Michalis (Herausgeber:in) / Ward, Robert (Herausgeber:in) / T. Watson, Richard (Herausgeber:in) / Herodotou, Herodotos (Autor:in) / Aslam, Sheraz (Autor:in) / Holm, Henrik (Autor:in) / Theodossiou, Socrates (Autor:in)

    Erschienen in:

    Maritime Informatics ; Kapitel : 19 ; 313-334


    Erscheinungsdatum :

    15.11.2020


    Format / Umfang :

    22 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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