Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/161879
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dc.contributor.authorMoura, Ricardo-
dc.contributor.authorSantos, Nuno Pessanha-
dc.contributor.authorRocha, André-
dc.contributor.authorLobo, Victor-
dc.contributor.authorNeto, Miguel de Castro-
dc.date.accessioned2024-01-03T22:54:18Z-
dc.date.available2024-01-03T22:54:18Z-
dc.date.issued2023-12-
dc.identifier.issn2052-4463-
dc.identifier.otherPURE: 78953982-
dc.identifier.otherPURE UUID: e13eff53-9064-444e-b0ba-f26bdb25f533-
dc.identifier.otherScopus: 85178942831-
dc.identifier.otherWOS: 001117999800002-
dc.identifier.otherPubMed: 38062072-
dc.identifier.otherPubMedCentral: PMC10703830-
dc.identifier.otherORCID: /0000-0002-3003-9235/work/151368300-
dc.identifier.otherORCID: /0000-0002-0149-3367/work/151411058-
dc.identifier.otherORCID: /0000-0002-7265-3890/work/151424443-
dc.identifier.urihttp://hdl.handle.net/10362/161879-
dc.descriptionThis work was supported by the national project MArIA - Plataforma Integrada de desenvolvimento de modelos de Inteligência artificial para o mar, with grant number POCI-05-5762-FSE-000400. Publisher Copyright: © 2023, The Author(s).-
dc.description.abstractPiracy has been a global concern and a threat to the safety of people performing maritime trade around the globe. Since ancient times maritime piracy has been a common practice that, unfortunately, has not ended in the current days. A georeferenced dataset providing the position, meteorologic conditions, and a description of the occurrence can provide essential information for analyzing this global phenomenon. The dataset focuses on the Gulf of Guinea (GoG) as an area dominated by corruption and weak supervision capacity by the local authorities. The time interval considered in this paper is between 2010 and 2021. Using this simple dataset, it is possible to analyze attributes such as when the piracy occurred or if the illegal activity involved deaths or kidnapping. The accuracy of the data was guaranteed by cross-referencing data sources, so we have 595 pirate attacks accurately described. This dataset can easily be used for data mining, allowing further analysis of the patterns and trends of pirate attacks in the GoG over time.en
dc.format.extent11-
dc.language.isoeng-
dc.relationFunding Information: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00297%2F2020/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00297%2F2020/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT-
dc.rightsopenAccess-
dc.subjectStatistics and Probability-
dc.subjectInformation Systems-
dc.subjectEducation-
dc.subjectComputer Science Applications-
dc.subjectStatistics, Probability and Uncertainty-
dc.subjectLibrary and Information Sciences-
dc.subjectSDG 17 - Partnerships for the Goals-
dc.titleGeoreferenced dataset of maritime piracy in the Gulf of Guinea from 2010 to 2021-
dc.typearticle-
degois.publication.issue1-
degois.publication.titleScientific Data-
degois.publication.volume10-
dc.peerreviewedyes-
dc.identifier.doihttps://doi.org/10.1038/s41597-023-02706-x-
dc.description.versionpublishersversion-
dc.description.versionpublished-
dc.contributor.institutionCMA - Centro de Matemática e Aplicações-
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School-
dc.contributor.institutionNOVA Information Management School (NOVA IMS)-
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)
Home collection (FCT)

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