Recent years have seen intense research activity in the modelling and analysis of complex networks, mainly driven by the availability of new large-scale databases for social, biological, and technological networks (see for example Newman, 2010 for a review). Maritime transport networks are one area where these new ideas and techniques have found fertile ground (Deng et al., 2009; Hu and Zhu, 2009; Kaluza et al., 2010; Ducruet, 2013). In this study, we analyse a database generated from Lloyd’s Shipping Index, a weekly publication of cargo ship movements by Lloyd’s List, over the period 1890 to 2008. For 20 selected years, an entire volume of the Index, each containing data for one week, was extracted and the data transformed into a network where the nodes are ports and links are nonstop ship voyages. Because cargo shipping is the dominant transport mode for world trade (UNCTAD, 2013), it is of great economic relevance for understanding the importance of the nodes. Here we measure importance in two ways:
• the number of vessel calls; and • the degree, defined as the number of ports that the node is connected to by at
least one arriving or departing ship.