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Maritime data technology landscape and value chain exploiting oceans of data for maritime applications

Authors: José Ferreira; Carlos Agostinho; Rui Lopes; Konstantinos Chatzikokolakis 0002; Dimitris Zissis; Maria-Esther Vidal; Spyros Mouzakitis;

Maritime data technology landscape and value chain exploiting oceans of data for maritime applications

Abstract

Maritime areas covers a large percentage of our world, being most of this area unexplored. Despite this, the sea has one of the most valuable and mostly exploited “economic platforms” of mankind, with applications in different sectors (as fishing industry, transportation cargo, etc.). Although this situation and the great evolution in technology can contribute to better know of the sea, this has not been happening. Given that a systematic collection of maritime data has already been carried out, yet is still dispersed and not used in its entirety. This is one of the objectives of the H2020 BigDataOcean project (http://www.bigdataocean.eu/site/), collecting the various data sources and thus being able to treat them together in order to obtain better results. This paper presents the analysis of the current landscape of big data, starting from the identification of existing ones, used tools and methodologies to be integrated in the project services, and platform with the aim of retrieving and analyzing the maritime data is presented. Then, the requirement engineering methodology is presented, being the methodology used during the project to identify the stakeholders, data sources, data value chain and the technologic gaps, resulting the in the identification of the first iteration of the requirements.

Keywords

Big Data; Maritime Data; IoT

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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