Authors: Siyu Xu; Hao Hu
Addresses: Department of Transportation, Shipping and Logistics and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China ' Department of Transportation, Shipping and Logistics and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
Abstract: Many types of maritime incident databases have been established that allow people to learn from past incidents and develop corresponding mitigation measures. However, our investigation of multiple international and national databases shows that most existing databases only record basic information regarding incidents in a single table. Lots of useful information is not included in the database (i.e., limited extension of the database). Meanwhile, some basic information is recorded tautologically (i.e., data redundancy). In this paper, two widely used databases are taken as examples, the Global Integrated Shipping Information System and the Lloyd's List Intelligence, to explain these common problems of existing databases. To overcome these limitations and improve the efficiency of data maintenance, this paper develops a relational maritime safety management database. The entity-relationship model is first used to depict the inter-related semantic information surrounding maritime incidents, and a relational database model is subsequently formed. Microsoft Access is employed to implement the proposed database, and a database application is also designed to demonstrate the utility of the database. Our preliminary study shows that the proposed database is implementable and has potential usage for both industry and academic research.
Keywords: maritime incident; data maintenance; Global Integrated Shipping Information System; GISIS; Lloyd's List Intelligence; LLI; relational database; entity-relationship model; Microsoft Access.
International Journal of Shipping and Transport Logistics, 2019 Vol.11 No.4, pp.334 - 353
Available online: 02 May 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article