在港口国控制中利用大数据:港口国控制数据及其在航运业治理和透明度方面的潜力分析

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
D. Ampatzidis
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引用次数: 0

摘要

摘要国际海事组织和几个欧洲国家(巴黎谅解备忘录)于1982年对国家港口的船只进行了港口国管制(PSC)检查,以评估其遵守安全和安保法规的情况。本研究讨论了PSC数据如何与大数据基础理论共享共同特征,并通过将其解释为大数据,我们可以将其治理和透明度视为大数据的挑战,从其使用中获得价值。因此,从大数据的范围来看,PSC应表现出体积、速度、多样性、价值和复杂性,以尽可能好的方式支持岸上和船上的官员,使船只保持在最佳航行条件下。出于上述目的,本文采用了学术和商业环境中广泛使用的大数据理论,研究数据集的特征以及如何从大数据和分析中获取价值。研究得出结论,PSC数据为航运业提供了有效的信息。然而,由于缺乏PSC数据能力来呈现PSC制度和港口的全貌,海事界对建立更安全、更可持续的行业的努力提出了挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging Big Data in port state control: An analysis of port state control data and its potential for governance and transparency in the shipping industry
Abstract The International Maritime Organization along with couple European countries (Paris MoU) has introduced in 1982 the port state control (PSC) inspections of vessels in national ports to evaluate their compliance with safety and security regulations. This study discusses how the PSC data share common characteristics with Big Data fundamental theories, and by interpreting them as Big Data, we could enjoy their governance and transparency as a Big Data challenge to gain value from their use. Thus, from the scope of Big Data, PSC should exhibit volume, velocity, variety, value, and complexity to support in the best possible way both officers ashore and on board to maintain the vessel in the best possible conditions for sailing. For the above purpose, this paper employs Big Data theories broadly used within the academic and business environment on datasets characteristics and how to access the value from Big Data and Analytics. The research concludes that PSC data provide valid information to the shipping industry. However, the lack of PSC data ability to present the complete picture of PSC regimes and ports challenges the maritime community’s attempts for a safer and more sustainable industry.
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
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