Citation

Meyers SD, Azevedo L, Luther ME. Transp. Res. Interdiscip. Persp. 2021; 10: 100387.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trip.2021.100387

PMID

unavailable

Abstract

Vessel traffic records from the Automatic Identification System (AIS) are a useful source of information for maritime data analytics, and of training data for maritime artificial intelligence systems. Researchers utilizing these data are developing the foundations for operational maritime tools essential to economic expansion and security. The global growth and distribution of this research effort from 1997 to 2019 was examined through a bibliometric study of 817 Scopus-listed publications. Indications of both collaboration and accelerating competition were found by examining the number of publications and authors, national and institutional affiliations of the authors, and number of citations received. Prior to 2003 about 1-5 publications per year appeared in the literature. The annual number of publications has doubled roughly every 5 years since the mid-2000s, reaching 140 in 2019. About 82% of publications were by authors based in a single country. Overall, authors affiliated with China contributed to 27% of all publications, followed by the US (9%) and Italy (8%). Authors from EU countries, taken collectively, were most common (37%). From 2016 to 2019 the number of authors from China quadrupled, and the number of publications with at least one China-affiliated author quintupled, producing about 39% of all publications in that time period. Some policy questions arising from this study are presented, and the need for continuing international collaboration and cooperative development are discussed.

Language: en

Keywords

Artificial intelligence; Automatic Identification System; Maritime data; Maritime policy; Research trends; Scientific collaboration