Research Data Management at McMaster

Research Data Management at McMaster

In the spirit of good data stewardship and funding agency requirements the adoption of Research Data Management (RDM) practices are increasing worldwide. In Canada a handful of funding agencies require researchers to apply RDM practices to their data to ensure it is comprehensive and accessible long-term. The purpose of this website is to both provide information and link relevant resources to different phases of RDM to reduce obstacles associated with the process. The buttons beneath can be used to navigate to sections of the RDM process, in addition to the menu on the left.

RDM is the active organization and maintenance of data throughout its lifecycle, from its collection, interpretation, dissemination, and the archiving of valuable results. RDM enables reliable verification of research results, and permits innovative, interdisciplinary research built on existing information. The application of RDM improves cumulative research efficiency, and reduces the overall cost of research

RDM integrates data management considerations such as data documentation and metadata, security, archiving, and sharing with the traditional data life cycle of planning, collecting, and preserving. The incorporation of RDM practices throughout a project optimizes the quality and re-use of the research data, and can become quite efficient on time. This approach enables the data's comprehensiveness and accessibility to be preserved both short and long-term.