Developing research in different fields is defendable as well as necessary for the development of disciplines and knowledge construction in general. The progress of qualitative and quantitative approaches is based on hard competitiveness and high level of innovation. This increases the need of a rigorous management of research process which should be more and more accurate and traceable to ensure a good data management approach. Considering this context, European Council stipulates a directive to require a good research data management in order to reinforce the ability of researchers to conduct properly their research activities (European Commission, 2016). For example the H2020 projects requires a Data Management Plan (DMP) since January 2017. In Switzerland, this tendency was clearly confirmed. Swiss researchers have been submitting their proposals to funding agencies without any requirement for research data management so far. However, the Swiss National Science Foundation will require a DMP since October 2017. Researchers are not prepared. They don’t know how it impacts their work and are looking for solutions to comply with these new requirements. This paper draws a general portrait of a recent Swiss project on this subject: data life cycle management applied on research data: DLCM. It presents, first, an over view of the main objectives and major dimensions of DLCM project and second, it will focus on one those latest which is dealing with training, consulting and teaching in the field of research data management.