Research Data Management (RDM)

Research data management

Research data management (RDM) is about how you collect, care for, use, preserve and share the data that support your research.

Research data lifecycle

The research data lifecycle includes everything from planning how data will be collected, to publication, to long term data preservation, to possible reuses of data. Steps of the lifecycle include: Plan, Acquire, Process, Analyze, Preserve, Share Results, and Reuse, but terms may differ based on institution, field of research, or model author. 

Importance of RDM

There are several reasons RDM is important. Here are some:

• Funding agencies increasingly turn to data and reproducible results to approve research grants.
• Journal publishers require authors to provide a data availability statement (DAS).
• Data is a transient product and can be easily lost if not saved properly.
• Managing research data correctly saves time and money.
• Data that can be referenced, verified, and validated increases the accuracy and quality of the research. Sharing data can also often lead to developments and insights from its readers, even if they are outside the original research.

RDM Glossary

• University of Waterloo
• Cornell Data Services
• University of Nebraska-Lincoln
• USDA Data Management Glossary

CMU Library Research Data Services

1. The datasets collection
2. RDM
   1. data repository 
3. Data analysis tools
4. Data visualization
5. Teaching with data
6. collaboration 
7. education / training

Research Data Management (RDM) is a broad concept that includes processes undertaken to create organized, documented, accessible, and reusable quality research data. The role of the library data services is to support researchers through the research data lifecycle. 

We can assist with researchers' needs such as:

• Identify resources and information for creating data management plans to meet funding agencies, IRB proposals, and publishers' requirements; 
• Identify resources for literature review and existing data related to research topics, 
• Provide the library's dataset collection and assistance in searching relevant datasets for secondary analyses; 
• Provide information related to creating data documentation, metadata standards;
• Identify repositories suitable for depositing and preserving different types of research data;
• Assist researchers to track research impact of data citations;
• Provide library instruction on data and data management for classes, research consultations for individual researchers.
• Create library research guides, workshops, webinars, or tutorials needed for CMU research community.

Contact the librarians for assistance:

• Rui Wang, Social Science Librarian / ICPSR Official Representative wang1r@cmich.edu
• Rebecca Renirie, Life Science / Medical Librarian hill2ra@cmich.edu
• Or, other Subject Librarians