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Big data of the past: Analysis of historical freight shipping corridor data in the period 1662-1855

机译:过去的大数据:1662-1855期间的历史货运流行者数据分析

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This paper examines the use of big data and data analytics in international transport networks from the perspective of historical big data, focusing on shipping logs from the British, Dutch, Spanish and French fleets in between 1662 and 1855. Based on a large-scale database containing mainly meteorological data collected in the CLIWOC project (2003), we computed travel distances and analyzed historical global maritime networks. This paper focuses on route choice, and consequently the time, distance, speed and reliability of the ships, covering different time periods, seasonal patterns and trade flows. The results reveal a clear picture of the main routes per nationality that is also indicative of the linguistical, cultural and economic colonial heritage that remains in the 'host' countries up to this day. The average daily distances covered vary over the countries involved, over the seasons and over different time periods. Also the trip characteristics vary notably over the different countries. Zooming in on the main trade flows, the corridor from the Netherlands to Indonesia stands out, but also considerable differences in average speed and stopover times were found along this route. Related to the complexity of using big data in studying international transport networks, our conclusion is that the degree of permutations and interactions with the dataset is not necessarily less for analyzing historical shipping records. It seems that big data of the past still can inspire future explorations of our historical transport networks on the world's oceans.
机译:本文从历史大数据的角度介绍了在国际运输网络中使用大数据和数据分析,从英国,荷兰语,西班牙语和法国舰队的运输日志介于1662和1855年之间。基于大规模数据库主要在CLIWOC项目(2003年)中收集了气象数据,我们计算了旅行距离并分析了历史的全球海事网络。本文侧重于路线选择,因此船舶的时间,距离,速度和可靠性,涵盖不同的时间段,季节性模式和贸易流量。结果揭示了每国籍的主要航线的清晰图片,也表明了在“宿主”国家仍然存在于今天的语言,文化和经济殖民遗产。涵盖的平均每日距离因涉及的各国和不同的时间段而异。旅行特征也明显不同于不同国家。从主要贸易流量放大,荷兰到印度尼西亚的走廊脱颖而出,但在这条路线上发现了平均速度和中间速度的相当大的差异。与使用大数据在研究国际运输网络中使用大数据的复杂性有关,我们的结论是,与数据集的禁育程度不一定不必分析历史送货记录。似乎过去的大数据仍然可以激发我们在世界海洋上的历史交通网络的未来探索。

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