DATABOOK : a standardised framework for dynamic documentation of algorithm design during Data Science projects
Keywords:Data Science, Artificial Intelligence, Documentation, Reproducibility, Algorithm Transparency, Project Process, FAIR, Human Data Mediation
This paper proposes a standard documentation framework for Data Science projects, called Databook. It is a result of five years of action-research on multiple projects in several sectors of activity in France, and of a confrontation of standard theoretical Data Science processes, such as CRISP_DM, with the reality of the field. As a vector for knowledge sharing and capitalisation, the Databook has been identified as one of the main facilitators of Human Data Mediation. Transformed into an operational prototype of simple and minimalist documentation, it has since been tested then on about a hundred Data Science projects, has proven its benefits for the internal and external efficiency of Data Science projects, and can be turned into a more ambitious standard framework for data patrimony valorisation and data quality governance.
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Copyright (c) 2021 Anna Nesvijevskaia
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