Ideas from the speakers
The discussion on data intelligence highlighted a critical issue: organising the existing free data and making it understandable and usable for various sectors such as government, industry, science, and AI platforms. As solutions to this issue, speakers presented different projects that enable the structuring, collection, and distribution of data.
The first idea was a platform that organises collected data from oceans in high quality. This data can be used by various involved groups or for high-quality AI training. A second project from the same speaker is a research-tourism vessel. It is a luxurious cruise liner with a submarine level that gives people the chance to observe ocean life. This mesmerises people and evokes a willingness to act. Another example are “Christmas Tree” valves in Brazil that help operate oil and gas transportation. They can also collect data, which often gets lost if not used. This means that to fill the data gaps, we not only need to organise data to make it more accessible, but also to concentrate on the so-called three pillars. “Accelerating 30 by 30” by helping countries like Brazil even for free, “Transforming ocean industries” such as the use of Christmas Tree valves in Brazil, and lastly investing in “higher education” with high-quality organised data. Additionally, we have to embrace AI.
Another project was created to help collect data and obtain small investments for further research. It is a platform that can be used by people who take pictures of marine habitats and upload them for a small amount of money, which is based on their willingness to pay. About half of global travel is related to seas and oceans and consists of people who want to see animals. If tourism is involved in data collection, large amounts of new data can be collected.
The last project can be used for both collecting data and engaging more people, especially children. At resorts, underwater cameras are placed that stream live footage. These videos showing what is underwater and what impact humans have are then shown to children in schools. This builds a connection to nature during their formative years. At the same time, these videos can be used to identify visual surfaces and analyse audio data.
Insights from the audience
As one member of the audience has contributed, many projects allocate too little funding for proper data management. As an example, it was mentioned that even some of the best resources of aggregated coral data in the world have not updated their maps for the last two years. This means that the allocation of the finances should become more effective. Moreover, the availability of data for the whole population, including scientists, policymakers, governments, investors, and the public, increases the value of this data. Researchers often focus only on their own datasets and use the data for specific projects. However, when the project is over, the data gets lost. To eliminate the loss of data, it should become a collective utility instead of remaining under individual ownership. Similar successful models, such as the Allen Coral Atlas, already exist, and the key characteristics lie in continuous updates, the aggregation of multiple data sources, and open accessibility. Another question arose regarding the storage of data and its connection with politics. Since scientific data is not neutral in terms of power and can be deleted, manipulated, or restricted, it should be stored in independent, resilient institutions where backups and international collaboration are possible. To manage massive datasets collected from video footage, sensor data, and satellite imagery, the data should be processed, filtered, and compressed, as one of the speaker’s projects allows. A different recommendation from the audience was the active use of AI. Carefully collected and organised data is very useful for training Artificial Intelligence, which can then be used to analyse large datasets, identify patterns, and support decision-making. As a contribution to the marine data collecting project through a platform that collaborates with people, another opinion was expressed. Not only AI, but also citizens should be involved in the collection of data. Although data may sometimes be inaccurate, large datasets combined with AI filtering can still result in reliable results.
