Why Does Ocean Data Matter?

As the most significant carbon sink, our oceans are a crucial ally in the fight against climate change, absorbing approximately 30% of the carbon dioxide produced by human activities. They are also home to 80% of Earth's biodiversity, making them a critical component of life. However, these vital ecosystems face unprecedented threats, particularly in coastal areas, due to boating, fisheries, aquaculture, energy, and mining.

In addition to their role as carbon sinks and biodiversity hotspots, our oceans are also a significant energy source. From subsea oil and gas to the urgent need for sustainable energy solutions like offshore wind and wave energy, our oceans are a beacon of hope.

Whether measuring geotechnical conditions, community sentiment, subsea conditions, marine mammal populations, aquaculture, or windspeed, collecting, monitoring, and analysing data underpins developing and preserving the oceans for industry and governments.

Large amounts of data are crucial for governments to understand the impact and for industries to make the right investment decisions. They're the backbone of informed decision-making.

How our requirements for ocean data changed

Our commitment to accuracy and reliability is unwavering, as we base our decisions on evidence and facts. Data-driven decisions reduce the risk of errors and instil confidence in your choices and their outcomes. It shifts from gut feelings or intuition to hard facts and evidence.

However, as our decision-making shifts from gut feelings to data-driven decisions, so do our data requirements. While we might have been comfortable with having a small data sample over a shorter timeline, many of today's models that use machine learning and AI depend on months or, in some cases, years of uninterrupted data collection.

Today, most of our ocean data is collected.

Most ocean data is collected using research and specialist ships and, in some instances, (anchored) stationary buoys. However, these are expensive operations, and the data collection could be more scattered.

Research and specialist vessels are expensive, and since most vessels use carbon-based fuel, they contribute to pollution. In some cases, they collect data to reduce pollution. Since they are costly and need to make return trips to change crew and get provisions, they can also not get months of uninterrupted data.

Innovative and more cost-effective monitoring methods can be used.

In the past, the sensors were large and energy-consuming. Now, they are smaller and more energy efficient. With this development, sensors that were dependent on large specialist vessels can now be deployed using small autonomous crafts or drones.

Whether operating above and below the waterline?and often in tandem, an emerging and cooperative ecosystem of Uncrewed Surface Vehicles (USVs), autonomous underwater vehicles (AUVs), ROVs, crawlers, and other towed?bodies sets out a practical path towards achieving more?with less: more purpose-led, sustainable ocean exploration?and discovery; less operational cost, risk to personnel. Many of these are powered by natural forces, such as waves and wind, require little energy, and involve minimal emissions of CO2. Those vessels that only operate on the surface are often equipped with solar panels, which provide energy to operate the instruments on board.

These autonomous vessels can cover large areas at sea for months, giving us a better understanding of ecosystems and how they are affected. Although autonomous craft cannot wholly replace research ships, they contribute to increased space and time coverage and reduce the dependence on large and expensive specialist vessels.

The development of artificial intelligence also makes it easier to analyse the large amounts of data we collect. In the future, it is vital that we further develop our ability to handle big data.