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Commodity Flows
Commodity flows are datasets created by aggregating AIS, Fixtures, Vessel Lineups, Bill of Lading data, and a variety of other datasets to map cargo types and quantities to specific vessels.
Once this has been done, it’s possible to work out the flows from one location to another by combining the cargoes in and out, enabling both a highly granular and high-level overview of the supply of commodities.
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Commodity Flow Data maps the movement of cargoes across maritime routes by aggregating multiple datasets including AIS, fixture data, vessel lineups, and bills of lading to link specific cargo types and quantities to individual vessels.
Once cargos are assigned to ships, the dataset enables the reconstruction of flows between origins and destinations.
This data provides both granular shipment-level insights and macro-level trade flow trends.
Coverage
Coverage depends on the depth and quality of source datasets but is typically global across:
Major bulk commodities (Oil, LNG, Products, Iron Ore, etc)
Wide range vessel classes involved in seaborne trade
Key import/export corridors and strategic maritime chokepoints
Some platforms now include predictive cargo flow estimates for routes or voyages lacking full data coverage. This is achieved through modelling based on historic movement patterns and vessel behaviour.
Sources
Commodity flow datasets are built and enhanced using multiple different data sources. These can include, but are not limited to:
AIS data
Fixture data
Vessel lineup data
Bills of lading and customs filings
Predictive modelling outputs
Methodology
The workflow typically includes:
Vessel identification and voyage tracking
Matching cargo declarations or inferred data
Cargo attribution to origin and destination points
Aggregation and visualisation of flows at regional, national, or global levels
Predictive gap-filling in the absence of full source coverage, using vessel history and commodity patterns
Why This Data?
Commodity flow datasets are essential for understanding global supply and demand dynamics across energy, agriculture, and industrial sectors:
Used by traders, analysts, ports, and governments to monitor volumes, forecast pricing impacts, and assess trade dependencies
Supports freight modelling, capacity planning, and geopolitical risk analysis
Valuable for market entry, competitor benchmarking, and macroeconomic research
Benefits:
Provides high-resolution insight into specific commodity movements
Offers geographic and temporal flexibility, with queries from voyage-level to global aggregates
Builds from vessel-level behaviour, allowing for dynamic expansion to new commodities or routes