Data science is an interdisciplinary field that extracts value from data. One of the relevant areas is its application in research in order to define requirements of the data life cycle. Thus, data should be managed before, during, and after a research project completion. A robust data management plan (DMP) is a relevant and useful instrument to establish data-related requirements. In this context, this paper aims at highlighting some characteristics associated to research data management. To conduct this study peer-reviewed literature and secondary data are methodologically employed to fulfil the paper objective. The results discuss the development of DMP, provide some examples of documents and a check list related to data management, and present some recommendations for developing a suitable data management plan from the literature. The data management plan is one of the important instruments that should be considered with care when designing and applying it. Future work may consider providing a structure and guidance for research students in the field of industrial engineering as a valuable avenue to explore.
Authors: Paulo A. Cauchick Miguel (Universidade Federal de Santa Catarina - UFSC), Suzana Moro (Universidade Federal de Santa Catarina - UFSC), Roberto Rivera (Universidade de Aveiro), Marlene Amorim (Universidade de Aveiro),
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