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Research Data Management

What is Data?

From the perspective of research data management, it is perhaps most useful to think of data as everything that would be needed to reproduce a given scientific output. It is important to recognize that data goes beyond spreadsheets of numbers. Data can take many forms: biospecimens, video recordings, images, software programs, algorithms, paper lab notebooks. (Surkis & Read, 2015)

What is Research Data Management (RDM)?

Research Data Management refers to the practices of organizing, documenting, storing, sharing, and preserving data gathered during a research project.

Effective management of data includes:
•    File organization 
•    Documentation and version control 
•    Storage and access for security and collaboration
•    Archiving and preservation for future accessibility
•    Policies for sharing and reuse

(Adapted from Texas A&M University Libraries

Why Manage Research Data?

•    Meet funder and publisher requirements
•    Organized data saves time
•    Increases the impact of your research through data citation
•    Clearly documents and provides evidence for your research in conjunction with published results
•    Meets copyright and ethical compliance (ie. HIPAA)
•    Preserves data for long-term access and prevents loss of data
•    Describes and shares data with others to further new discoveries and research
•    Ensures project continuity through researcher or staff changes
•    Reduces risk of lost, stolen, or misused data

(Adapted from Texas A&M University Libraries, Princeton University Library, Northwestern Libraries

Research Data Lifecycle and Checklist