Our data Supports


We’re engaged in a variety of confidential fishing industry projects including operational performance and compliance analytics. If you are interested in discussing fishing industry data analytics, please drop us a line. High resolution ocean data enables precision fishing, increasing targeted catch species while avoiding bycatch and choke species. Make more money while decreasing your ecosystem impact. In the long run, this data can be used to understand the true causes of abundance and distribution shifts, enabling you to better plan for the future.

“Temperature data is absolutely critical to target specific species, especially with permit restrictions on by catch… It is not one degree, but a small fraction of a degree change in bottom temperature that completely changes a lobster’s behaviour.”

-Captain Lawrence Moffet, F/V Matt & Patt


We make it easy by translating between the diversity of fishing practices and resulting data to standardized and well-documented data that can be directly used in models or analyses. Using Argo and QARTOD based QC, we serve data in near real-time in standardized formats with machine-to-machine connectivity via ERDDAP. Let us know how you want data; we can even feed directly into operational pipelines like CMEMS instac or the GTS.

Fishing activities are already taking place not only where data is lacking but also where it is needed most by ocean model and forecast users: in the dynamic shelf seas and coastal regions. Collaborative data collection with the fishing industry presents an opportunity to complement the ocean observation systems and technologies of today. Subsurface fishing vessel data streams are assimilated operationally into a growing assortment of ocean models: Doppio (ROMS USA), the Moana project in New Zealand, RIAM Real-Time Ocean Forecasting system in Japan, and several European models. Data collection opportunities are not limited to sub-surface physical parameters, but can also be extended to co-locate a range of Essential Ocean Variables.


The importance of monitoring our oceans cannot be overstated. The world’s oceans provide food, resources, and employment for billions. The ocean is also an essential climate regulator and our largest buffer against increasing global temperatures from carbon emissions. Roughly 93% of the excess heat and 30% of the carbon produced by climate change is absorbed into the ocean. However, this crucial buffering capacity could change due to shifts in ocean currents or ocean acidification. Recent studies have shown large errors in prior ocean models (Cheng, et al. 2019, Lozier, et al. 2019). These models are built and run with inadequate data, directly decreasing the accuracy of the Intergovernmental Panel on Climate Change (IPCC) reports (Lozier, et al. 2019).

The current state of the art in autonomous and cost effective ocean data collection technologies cannot operate around sea ice, where it is of the utmost importance to monitor climate change processes. Fortunately, fishing vessels often prefer to fish the ice line, providing an opportunity to get data where it is needed most.


Hydrographic data coupled directly with fine scale catch data is a key step forward in the implementation of more dynamic and Ecosystem Based Fisheries Management. Oceanographic data measured with the sensors can be directly correlated to commercial catches, enabling greater insight into when and where which fish species are. This means quotas can be improved and by-catch avoided more effectively, leading to an overall improvement of ocean health.
Bottom temperatures from the eMOLT project are used in the lobster stock assessment to correct for temperature dependent changes in catchability between different survey methods. Fishers collecting data on their own terms flips the current paradigm of top-down fisheries data collection. Involving fishers in the scientific process leads to increased stakeholder involvement, improved dialogue between fishers and scientists, and better compliance with regulations