From a prototype to a data ecosystem for experimental data and predictive models

Data ecosystems have been a game-changer in many industrial applications and research fields, speeding up their development. The possibility of collecting large amounts of data within the same environment has also raised some common questions to all application domains, including the quality of the data collected and their reliability and trustworthiness. From experience gained collaborating with the chemical engineering field, this paper raises some discussion points related to the management of experimental data and predictive models within a data ecosystem. In fact, this type of data poses new requirements that require specific treatment before being implemented in a traditional data ecosystem.