Research Data Management

Get expert help with research data planning, discovery, and sharing. You can book a consultation for:

•   Data Management & Sharing Plans – including DMPTool support and NIH/NSF requirements
•   Search & Share – help locating datasets, selecting repositories, and making your data citable and reusable
•   Quick Questions – for smaller data-related topics or brief follow-ups

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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)

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) 

•    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) 

(JISC Research Data Lifecycle, CC BY-ND)