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3. Data Life Cycle

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3.2 Planning

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.


... should include resources to be dedicated to data management (from data collection to sharing).

Needs [ why? for whom? ]

  • Data collection requirements
  • Business/research objectives
  • Users/clients
  • Target audience
  • Anticipated benefits/results

Data [ what? ]

  • Identification of existing data
  • Selection of variables
  • Type of data: digital, images, video, audio, animations, simulations, models
  • Standard formats

Methodology [ how? ]

  • Sampling plan
  • Experimental/laboratory protocol
  • Data collection process
  • Data access mechanisms

Required resources [ how? who? how much? ]

  • Financial means: existing / to be obtained
  • Human resources: expertises & skills required, staff availability, training needs, roles & responsibilities
  • Equipement: existing / to be acquired

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.


Data management costs can be assessed by looking at efforts that will be required to collect, validate and structure data and to develop data access mechanisms. Litterature often refers to amounts equivalent to 6 to 10% of research project budgets.

Scope of project [ when? where? how much? ]

  • Period: dates/duration, frequency
  • Area of interest: geographical situation, definition et delineation of area of interest
  • Deliverables: Specific, Measurable, Achievable, Realistic, Timely – SMART

Issues [ what? how? ]

  • Risk analysis
  • Identification of opportunities