Abstract
Link discovery in the maritime domain is the process of identifying relations—usually of spatial or spatio-temporal nature—between entities that originate from different data sources. Essentially, link discovery is a step towards data integration, which enables interlinking data from disparate sources. As a typical example, vessel trajectories need to be enriched with various types of information: weather conditions, events, contextual data. In turn, this provides enriched data descriptions to data analysis operations, which may lead to the identification of hidden or complex patterns, which would otherwise not be discovered, as they rely on data originating from disparate data sources. This chapter presents the fundamental concepts of link discovery relevant to the maritime domain, focusing on spatial and spatio-temporal data. Due to the processing-intensive nature of the link discovery task over voluminous data, several techniques for efficient processing are presented together with examples on real-world data from the maritime domain.
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Notes
- 1.
In this chapter, entities correspond to spatial objects, so these terms are used interchangeably.
- 2.
Other Coordination Reference Systems (CRS) can be also used for the construction of the grid.
- 3.
Available online https://zenodo.org/record/1167595 and https://zenodo.org/record/2576584.
- 4.
Available online at https://zenodo.org/record/1167595.
- 5.
The generated RDF triples from contextual data sets are available online at https://zenodo.org/deposit/2576584 and the surveillance data set at https://zenodo.org/deposit/2576152.
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Acknowledgements
The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: HFRI-FM17-81).
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Santipantakis, G.M., Doulkeridis, C., Vouros, G.A. (2021). Link Discovery for Maritime Monitoring. In: Artikis, A., Zissis, D. (eds) Guide to Maritime Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-61852-0_7
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