Articles | Volume 19, issue 8
Biogeosciences, 19, 2095–2099, 2022
https://doi.org/10.5194/bg-19-2095-2022
Biogeosciences, 19, 2095–2099, 2022
https://doi.org/10.5194/bg-19-2095-2022
Technical note
19 Apr 2022
Technical note | 19 Apr 2022

Technical note: Incorporating expert domain knowledge into causal structure discovery workflows

Jarmo Mäkelä et al.

Data sets

Interactive Causal Structure Discovery with Hyytiälä measurements L. Melkas, J. Mäkelä, S. Chandramouli, I. Mammarella, T. Nieminen, K. Puolamäki, and R. Savvides https://doi.org/10.5281/zenodo.6451931

Model code and software

Interactive Causal Structure Discovery with Hyytiälä measurements L. Melkas, J. Mäkelä, S. Chandramouli, I. Mammarella, T. Nieminen, K. Puolamäki, and R. Savvides https://doi.org/10.5281/zenodo.6451931

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Short summary
Causal structure discovery algorithms have been making headway into Earth system sciences, and they can be used to increase our understanding on biosphere–atmosphere interactions. In this paper we present a procedure on how to utilize prior knowledge of the domain experts together with these algorithms in order to find more robust causal structure models. We also demonstrate how to avoid pitfalls such as over-fitting and concept drift during this process.
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