Mashup Tools for Big Data Analysis in Maritime Surveillance - Melillos, George; Themistocleous, Kyriacos; Danezis, Chris; Michaelides, Silas; Hadjimitsis, Diofantos G.; Jacobsen, Sven; Tings, Björn (My University, 2020)
The growth of big data and its popularity in maritime surveillance has increased at an exponential rate. The amount of maritime information being collected every minute around the world exceeds the capacity of traditional databases. The development of real-time, Geospatial Web Applications e.g., MarineTraffic and VesselFinder AIS vessel tracking web sites, provide us with huge sets of structured and unstructured data that are too complex for traditional data-processing software. The aim of this paper is to exploit the benefits of query and mashup amounts of maritime data using mashup tools as a result to create a single, unique visualization. The results show that using mashup techniques in maritime surveillance could be used to monitor, compare, combine, manipulate and analyse Big Maritime data. Therefore, research on Maritime Data offers a huge potential and an opportunity to benefit from the advantages.
Keywords: Maritime Surveillance; Big Data; Mashup Tools; Python; Web Scraping; AIS