Sharing industrial ocean data: use cases
We at HUB Ocean always say privately-owned industrial ocean data must be unlocked for the benefit of science, but why has this not already happened? What are the barriers? Do industries — for example, shipping, fisheries, or energy companies — know what data scientists really need? Do scientists know what data exists?
In March, HUB Ocean, in collaboration with the Intergovernmental Oceanographic Commission (IOC) of UNESCO, will host a workshop on sharing ocean physics data aimed at answering these questions and finding solutions. We will bring representatives of science, industry and governments together in one room and build specific use cases.
As a preparation step, we held an online workshop with more than 20 ocean scientists from Europe, the US, and the Middle East working with ocean models. We asked them how they use industrial ocean data, what impact and value it adds to their research, and what data gaps need addressing.
What is ocean physics data and why do we need it?
The Global Ocean Observing System (GOOS) lists essential physical ocean variables that measure sea state, temperature, and salinity on and under the surface. The list defines more than 35 variables, from the length of waves to ocean and atmosphere heat exchange, to sea ice thickness and sea surface height.
Sea ice thickness is one of ocean variables
Scientists feed this data to large-scale ocean models to increase understanding of the ocean through improved analytics, modelling and predictions. For instance, knowing the length of waves is important to ensure seafaring transport safety or to optimise rescue operations at sea, while sea surface height is an indicator of climate change.
Fueling ocean models with relevant, accurate and detailed ocean physics data can enhance the prediction of hurricanes, storms, floods, droughts and heat waves, to name a few. We can get a better understanding of economically valuable fish migration or even predict ecosystem shifts.
Why share privately-owned ocean data?
In the preparatory workshop, we asked participants to outline specific use cases where industrial data sharing would be mutually beneficial to science and industry. Here are some examples:
Better forecasts of storms can help reduce damage to infrastructure
Improved modelling and forecasts of extreme weather will help reduce infrastructure damage, repair costs and time. In general, companies will better estimate infrastructure durability or develop new designs based on these enhanced models. It will also help transport companies build new, optimised shipping routes.
Improved mapping of turbidity and currents across the seafloor will reduce downtime risks for submarine cables and other critical offshore installations.
Improved modelling of sea level rise and coastal erosion will help mitigate risks for coastal infrastructure, such as seawalls, roads, ports, and harbours.
What data gaps do we need to address first?
According to the findings, scientists often need more detailed and accurate data for variables they already use, as well as data at a higher temporal and spatial frequency. There are also gaps in data types, such as:
Data from the subsurface and deep ocean
Data of ocean currents: surface, subsurface, and especially the bottom
Data from underneath the sea ice
Wintertime data from polar regions
Behavioural data of various ocean species
Data on long-term changes in coastal regions
Other data types where researchers see gaps include current and potential fishing zones, shipping routes, and maps of global ocean data initiatives.
Another thing we learnt was that, when it comes to the private sector, there can be a lack of detail on where data is and who in fact owns it. Many ocean companies do not necessarily acquire the data themselves but contract others to do it. It is eventually hard to find the original version of the ready-for-analysis data so that it can be reused by scientists. This issue also adds to the uncertainty over the quality, reliability, and provenance of data.
What are the next steps?
Sharing closed industrial data with the scientific community and the public contributes to better science, prediction, science-based decisions and more sustainable ocean management – and ultimately, a better world.
At the in-person workshop in March, that we are hosting in collaboration with the IOC of UNESCO, we plan to define clear use cases, highlight priority datasets needed and lift the barriers to data sharing.