Data management is a set of practices that occur over the lifetime of a research project. These practices include the organization, documentation, and storage of research data. Ideally, they are planned for at the outset of a project and occur continuously and iteratively throughout the course of a project. When care is taken to manage research data thoughtfully, it makes the research process more efficient, facilitates collaboration, and can help prevent data loss.
Effective data management practices facilitate the accessibility of data when a project is completed. Data that is organized and documented is more easily reused by others and helps establish the transparency and reproducibility of research.
Data sharing is the practice of making research data available to others. Data can be made available for sharing by depositing it in a data repository, describing it in a data paper published in a data journal, or sharing it with individual researchers upon request. Before data is shared, it should be preserved.
Good data management practices and sharing research data have many systemic benefits. In his Statement on the Final NIH Policy for Data Management and Sharing, former NIH director Francis S. Collins, M.D., Ph.D., says, By committing ourselves to responsible data management and sharing, we are catalyzing the scientific process to accelerate revolutionary discoveries and medical breakthroughs.
Good DMS practices facilitate:
In addition to the systemic benefits, good data management and sharing practices can make daily life easier for individual researchers.
Good DMS practices enable:
To learn more about Data Management and Sharing, see the following subsections of this guide:
If you'd like to know more about how to implement data management and sharing best practices, see these sections of this guide:
