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Reducing water losses is one of the most pressing issues for modern waterutilities. To that end, improving the efficiency of the pipe leakage and repairprocess and aiding the selection of the pipes that are to be renewed orrehabilitated are essential. To help addressing these tasks, in this work, wedevelop a model predicting the probability of a pipe to be leaking. This workis set the context of a multidisciplinary project with Soci{\'e}t{\'e} Wallonedes Eaux and it is aligned with their goal to improve their InfrastructureAsset Management in the short and the long terms. Developing and feeding thisleakage probability model relies on an intense data processing phase,mobilizing data and water engineering sciences, since the raw data from SWDE isnot ready to be used in the model. Complementarily, we thus employ techniquesfrom sociology (e.g., interviews, analyses of the human/non-human actors and ofthe tools, sociotechnical translations) in order to complete the data, toimprove our understanding of its production, and to increase its value and itsavailability for the prediction of the pipe leakage probability. This modelwill be implemented in SWDE's information system and used for strategies toreduce water losses.

Understanding the leakage process for multi-scale water infrastructure  asset management: necessity for a dialogue between sociological and data  sciences