Digitising ocean technologies and data collection is providing new insights into the health of our seas. Known as Big Data, this form of information gathering and research is a vital tool for governments and policy makers.
A recent report, Big Data in Marine Science was published by the European Marine Board and aims to
‘raise awareness of big data, give some examples of its potential applications in marine science, and identifies actionable recommendations needed to fully bring marine science into the world of big data. “
The report covers several case studies where a big data approach had been applied including climate and marine biogeochemistry, habitat mapping for marine conservation and food provision from seas and the ocean.
Taking part in this collaborative publication was Dr Tara Marshall, School of Biological Sciences, at Aberdeen University.
Dr Marshall focussed on how the big data approach was being utilised in aquaculture to manage sea-lice outbreaks in Norway.
Dr Marshall explained:
“Sea-lice are external parasites that kill young salmon and reduce disease resistance in both juveniles and adults. Infection rates increased as global salmon farming expanded throughout the 1980s and 1990s, and while the use of biopesticides provided a short-term solution, their efficacy declined due to increasing resistance.
“Currently, sea-lice pose a significant challenge to the growth of the global salmon farming industry.
“Big data are becoming a part of industry-led solutions for combating sea-lice by taking advantage of the wealth of environmental and production-level data being collected and shared in real-time. These data can be used to predict when and where outbreaks will occur such that measures can be introduced to limit spread of sea-lice.”
The report recommends the following for the managing of sea lice outbreaks:
- Develop smart sensors e.g. camera-based sea-lice counters, automated fish welfare monitoring systems and improved automated environmental monitoring systems to increase the temporal resolution of the biological and environmental data thereby allowing improvement in forecasting algorithms
- Improve connectivity of sensors and data transfer for better monitoring data
- Use data standards and best practices based on FAIR principles across the whole ocean data value chain
- Involve digital firms (such as IBM) for cross-industry collaboration and cross-fertilization of technology and expertise
- Develop effective collaborations across government, industry, universities and the digital sector to deliver realtime operational data analytics for forecasting sea-lice outbreaks
- Develop a viable and sustainable business model to maintain and scale-up monitoring networks
The report was the result of a significant collaboration between institutions in 18 European countries.
There is a huge amount of data collected on marine science but there is no unifying framework bringing it all together. Some information is not publicly available and some gets lost over time – a change is required.
- F – Findable
- A – Accessible
- I – Interoperable
- R – Reusable
If the principles of FAIR were applied to Marine Science worldwide the real value of the data being collected would be realised leading to improved policy making to make our seas cleaner and the activities which take place in them more sustainable.
FAIR requires key changes in the practice and culture of research and the implementation and normalisation of certain technologies and practices.
You can read more about that here: Turning Fair Into Reality and the European Open Science Cloud.
Commenting on her involvement with the Marine Science data collaboration ,Dr Marshall said:
“I was delighted to be part of the team commissioned by the European Marine Board to investigate the use of big data in marine science. We often hear of big data in relation to other disciplines, however, it can – and I am sure will – play an important part in the future development of marine science including applications to seafood production.”
Dr Marshall’s participation in the report writing was funded by Marine Alliance for Science and Technology for Scotland (MASTS).
Reporter: Fiona Grahame