Koster Seafloor Observatory
Koster Seafloor Observatory (KSO) is a system that combines citizen science and machine learning for automated analysis of subsea movies. The system offers volunteers to assist scientists by watching snapshots of deep-water recordings and identify species in short movies recorded by remotely operated vehicles (ROVs). These annotations are then used to train machine learning algorithms to recognise biological objects in real time - for example species or habitats that are rare or indicative for a certain ecological condition.
Originally, KSO was designed for presenting the biological diversity on the seabed of Kosterhavets National Park on the Swedish West coast - an environment that is otherwise invisible to the public. Here you can find dead whales, flying feather stars, swimming scallops, large colorful sponges and starfish. Currently, the KSO system is upgraded and will soon also feature Baltic envrioments, while the analytical functions likewise expanding.
One aim is to make marine biodiversity (habitats and species), which can not be visited otherwise accessible to the public for teaching and exploration. Another goal is to train machine learning algorithms with the help of citizens.
How to participate
Want to engange? There are many levels at which you can participate. You can identify marine species and habitats. If you are a teacher, you can utilize the existing identifications made by others for your own classes and school projects and thereby promote knwoledge about the wonderful lifeforms on the bottom of the ocean.
You need a computer with internet connection.
Funding bodies: Nordic e-Infrastructure Collaboration (NeIC)Vinnova funded program Ocean Data Factory (ODF) Swedish Biodiversity Data Infrastructure (SBDI)
Profile image design by: Mattias Sköld
Other Organisations involved
North East Atlantic, including the Baltic Sea