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The technique of \textit{in situ}, long-form recordings is gaining momentum in different fields of research, notably linguistics and pathology. This method, however, poses several technical challenges, some of which are amplified by the peculiarities of the data, including their sensitiveness and their volume. In the following paper, we begin by outlining the problems related to the management, storage, and sharing of the corpora produced using this technique. We then go on to propose a multi-component solution to these problems, in the specific case of daylong recordings of children. As part of this solution, we release \emph{ChildProject}, a python package to perform the operations typically required to work with such datasets and to evaluate the reliability of annotations using a number of measures commonly used in speech processing and linguistics. Our proposal, as we argue, could be generalized to broader populations.
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-\keywords{daylong recordings, speech data management, data distribution, annotation evaluation, inter-rater reliability}
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+\keywords{daylong recordings, speech data management, data distribution, annotation evaluation, inter-rater reliability, reproducible research}
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