Managing the Data Lifecycle: The Importance of Planning and Metadata

Planning for how data is managed through the research lifecycle is an important and critical aspect of science, and is increasingly becoming more important in the research grant process and in science organizations.  A data management plan is different from a project plan and requires attention to how the data will be acquired, documented, stored, preserved, and made accessible at various stages in the research process.

Equally important in the science data lifecycle is the documentation of science datasets. A dataset is not considered complete unless accompanied by detailed and standardized metadata describing both fundamental and complex aspects of the data. Metadata facilitates not only discovery of data, but also, more critically, an ability to understand the data making it a re-usable asset to advancing science research.

This session will address these two critical aspects of the science data lifecycle planning for data management and creation of metadata - why they are important, and best practices in how to approach them.