Content | Navigation |

Overview

Most federal funding agencies now require a Data Management or Data Sharing Plan as part of a proposal submission.  This is a formal document that outlines the type of data you are collecting, standards used to describe the data (metadata), who owns the data and how it can be accessed, considerations needed to protect sensitive information, including study participant confidentiality and intellectual property protection, and how you will ensure the archiving and preservation of the data. Carefully read proposal solicitations and agency guidelines for specific data plan instructions.  Requirements may vary by agency and program. 

For specific information on federal agency requirements, see Federal Agency Information and Open Access.

Data Life Cycle

Take into account  the life cycle of data when developing data management plans.  There are various stages to consider, including:

Proposal Planning and Project Start-up

  • Collection
  • Analysis
  • Sharing
  • Archiving
  • Re-Using

Data management throughout the life-cycle of your research can be beneficial in numerous ways:

  • Save time
  • Increase research impact
  • Ensure long-term ability to preserve fragile data sets
  • Organize and categorize data for efficient access, analysis, queries, etc.
  • Support sharing and open-access
  • Focus on data sharing as an objective of investigation
  • Support data-intensive discovery across disciplines
  • Promote verification and replication of research analysis and findings

Best Practices for Researchers:

http://www.data-archive.ac.uk/media/2894/managingsharing.pdf 

DataONE:         https://www.dataone.org/data-life-cycle

 


Student Focused. Land Grant. Research University.

Follow NDSU
  • Facebook
  • Twitter
  • RSS
  • Google Maps
Last Updated: Thursday, September 22, 2016 4:27:13 PM
Privacy Statement