Training courses

Bayesian Network analysis and the social-cultural dimension

7 - 11 December 2020
Online course

Application deadline: 28 November 2020

​​Bayesian Networks (BNs) are a flexible modelling method that can be used in various ways to address different types of research questions. Their strength comprises the ability to combine different types of data and knowledge, as well as include, integrate and represent uncertainty. The graphical nature of BNs makes them easy to communicate across scientific disciplines, and to diverse groups of stakeholders.

The objective of this course is to learn how Bayesian Networks can be used in inter- and transdisciplinary analysis of socio-ecological systems.

After the course, the student can:

  • explain what Bayesian Networks (BN) are and how they work
  • explain what inter- and transdisciplinary research mean and what is their value
  • estimate and evaluate the need for inter/transdisciplinarity and participatory approach in socio-ecological research questions
  • create a BN model that reflects a socio-ecological research question
  • evaluate theoretical, scientific, and cognitive factors that need to be considered when designing an inter/transdisciplinary BN model
  • use a readily available software package to build a BN
  • find and evaluate information sources to populate the model

​Practicalities:

The course is organized as online teaching on 7-11 December 2020. The teaching includes short lectures, reading selected articles, peer group discussions, discussions and Q&A sessions with the teachers, guided exercises to learn the BN software, and framing, building, and presenting your own model (and giving and receiving feedback).

​Requirements for attending:

  • installation of the BN software (Hugin Lite, available free of charge for evaluation purposes for Windows, iOS and Linux)
  • possibility to attend online meetings during European office hours (including microphone and preferably camera use)
  • possibility to dedicate the whole week for the course – work is required also outside of the online meetings




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Instructors:​

Laura Uusitalo, Finnish​ Environment Institute​, Finland

Laura has been working with Bayesian networks for 20 years, and has degrees both in aquatic ecology and computer science. She works as a leading researcher in Finnish Environment Institute, and her current interests include decision support systems, interdisciplinary research, and machine learning.

Päivi Haapasaari, University of Helsinki​, Finland 

Päivi works as a professor in multidisciplinary risk analysis at the University of Helsinki. Her academic background is in environmental social sciences.  Her research covers social scientific and inter/transdisciplinary approaches to marine environmental problems and resource use, using e.g. Bayesian networks.

Tuition fees:​
750 EUR for participants from ICES member countries
1250 EUR for participants from non-ICES member countries

Following application submission, please await notification from the course coordinator prior to making travel arrangements.​
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Bayesian Network analysis and the social-cultural dimension

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