Data Management

Research and other types of scholarly or creative activity generate data.  Whether an architect created blueprints and computer-aided renderings, or a biologist collected specimens, both of their projects generated data.  

Data management is defined as the organization, storage, access, and preservation of data in its various forms (Henderson, 2016).  This also includes what will be done with the data once a project is completed and how it may be shared and stored.  

Data management and data management plans are important for many reasons.

• New federal guidelines mandate making data that was generated from federally funded projects openly available. 
• There is a critical issue with reproducibility in research. Good data management addresses this issue and makes the research stronger.
• Researchers may be required to submit a Data Management Project in their grant proposals. 
• Increasing numbers of journals are either encouraging or requiring researchers to share their research data for manuscripts selected for publication. 
• Data management helps with data sharing, archiving, and efficiency. It also creates stronger support of results and strengthens research impact.

For general tips and considerations on managing and sharing data, style guides often have good information. Look up data management in an authoritative style, writing or research guide within your subject area; see a list in the Citations Research Guide or search the FAU Library Catalog. Many of the style guides also have information on ethical and legal considerations concerning data management.

Source: Henderson, M. E. (2016). Data management: A practical guide for librarians. Rowman & Littlefield.

Data Management in Higher Education