  Reducing water losses is one of the most pressing issues for modern water
utilities. To that end, improving the efficiency of the pipe leakage and repair
process and aiding the selection of the pipes that are to be renewed or
rehabilitated are essential. To help addressing these tasks, in this work, we
develop a model predicting the probability of a pipe to be leaking. This work
is set the context of a multidisciplinary project with Soci{\'e}t{\'e} Wallone
des Eaux and it is aligned with their goal to improve their Infrastructure
Asset Management in the short and the long terms. Developing and feeding this
leakage probability model relies on an intense data processing phase,
mobilizing data and water engineering sciences, since the raw data from SWDE is
not ready to be used in the model. Complementarily, we thus employ techniques
from sociology (e.g., interviews, analyses of the human/non-human actors and of
the tools, sociotechnical translations) in order to complete the data, to
improve our understanding of its production, and to increase its value and its
availability for the prediction of the pipe leakage probability. This model
will be implemented in SWDE's information system and used for strategies to
reduce water losses.
