Bodies of water contain valuable data on the condition of the sea, its species, related changes and biodiversity, as well as the impact of human activity on the sea. Such data could be better utilised in tackling wicked problems.
This is why the University of Helsinki is organising an open online course entitled Data Science for Monitoring Aquatic Ecosystems, headed by Professor of Computer Science Petteri Nurmi. The Finnish civil engineering association Maa- ja vesitekniikan tuki supports the course that utilises data processing methods to address challenges related to waterbodies. The language of the course is English and teaching will begin in 2026.
“In my previous research and teaching, I have noticed that the analysis of sensor data entails special features that are not usually discussed in basic data science courses. That’s why we wanted to design a course that supports students of different disciplines from this perspective,” Nurmi says.
Nurmi has previously contributed to a course on sensor data analysis and the Internet of Things, which provided the initial inspiration and background for combining aquatic ecosystems with data science.
While the upcoming course Data Science for Monitoring Aquatic Ecosystems is targeted at students close to completing their bachelor’s degrees or in the early stages of their master’s studies, Nurmi believes that the introductory course provides useful background information and methodology for doctoral researchers as well. The course includes assignments of varying levels of difficulty, which can be completed according to individual skills.
Comprehensive understanding of the process of data collection and processing
Solutions based on sensor technology and the Internet of Things in waterbodies, the identification of plastic litter and biodiversity in aquatic ecosystems, among other topics, have been previously investigated in computer science. Nurmi points out that, while being important application targets for the discipline, no actual introduction to them has been available at the University.
“Many researchers are already utilising engineering methods in the study of water environments, but we lack systematic education in this area. This course fills precisely that gap.”
The course explores the entire process of data collection and processing from start to finish; what data collection is, how often and accurately data are collected, what errors data may contain, and how data are eventually ‘cleaned up’ and utilised, for example, in the development of machine-learning algorithms.
The course assignments relate to diverse water data, such as pH-values, temperature and other aquatic parameters, as well as to imaging and biodiversity data. The idea is to use data collected by underwater sensors, such as hydrophones, or underwater microphones. It may also be possible to utilise long-term data on the Baltic Sea collected in the University of Helsinki’s MONICOAST research project.
“The aim is to highlight a wide range of content suited to both students of data science and natural scientists. As a multidisciplinary introductory course combining aquatic ecosystems with data science, this is the only one of its kind in Finland,” says Nurmi.
The course will be organised as a massive open online course (MOOC). Following its release, the course can be accessed from anywhere in the world.