Maritime Big Data


Big Data in the Maritime Industry – What is Possible and What is Useful?

The age of IoT, Industry 4.0, and even 5.0 is here and it has brought along data in amounts that transcend what most know how to navigate effectively.

It is somewhat presumptive for anyone to claim ability to present all that is possible and may be useful regarding Big Data in the maritime industry. It is presumptive as the possibilities are almost unlimited and what is considered ‘useful’ depends on each consumer of the information. However, what we can provide is a short overview and few examples of how big data can be used with the purpose of giving perspective and nuance to the big data conversation.

When we talk of big data, we are not talking specifically about the volume of data available or stored, but rather the use of analytics to transform large amounts of data to information. The distinction between data and information is crucial, as big data in itself is merely numbers, while information is what is actually usable to the industry. GateHouse Maritime is driven to deliver these analytics tools to transform data to information.

The foundation for our analytics is Automatic Identification System (AIS) data transmitted by commercial vessels worldwide. AIS messages contain the vessel’s geographic location, name, unique identity numbers, ship type, cargo, country, length, width, draught, rate of turn, speed, course navigational status and destination. This rich data source can provide very useful information to the consumer through analytics.

Potential applications of big data analytics include:

  • Vessel traffic pattern analysis based on draught and speed through a navigation channel
  • Comparison of vessel transits through a taxation zone year over year
  • Individual vessel speed analysis over a defined time to determine maintenance requirements
  • Individual vessel speed analysis to determine emissions
  • Detection of vessel navigation anomalies based on known transit and movement patterns
  • Forecasting of vessel arrivals worldwide
  • Estimated time of arrivals in support of supply chain logistics
  • Historical track analysis to determine recommended navigation tracks


The possibilities for extracting valuable information from data with time/location/asset information are immense. The above-mentioned possibilities of different analysis are merely a fraction of what is possible, which clearly bring forth the issue of information overflow. Even when big data is analysed, the sheer amount of information can be counterproductive.

The question each consumer should ask is therefore which information can drive my business model? What is useful and what is merely data? A data expert can help you discover the many technical possibilities, but you will have to define a clear purpose to truly unlock the potential of maritime big data.

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