Planning is the first and most important step of the data management process because it entails the development of a vision that will encompass all subsequent steps.
Before collecting data, it is imperative to define objectives, to analyze needs, to identify means, to anticipate risks and challenges, and to envision future data use. The final cost of data management – including human resources and equipment – always represents a significant portion of operating and/or research budgets. Therefore, defining a sound data management and conservation strategy is an essential step that will become a definite investment in the long run.
The components of data collection planning are described below. They will be developed by scientists/investigators according to their own context (laboratory, field, operational or research activities, etc.). This list can be used as a planning tool and check-list.
Assessment of the necessary resources for data management: efforts required beyond the data collection process have to be considered e.g. for the entire data life cycle. Assessing and including data management costs in the early stages of a project ensure that it will not become a burden along the way.