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Research Data Management

Why bother?

A Data Management Plan (DMP) is a formal document that details how you intend to generate, describe, store, protect, archive, share, re-use and/or de-accession your research data.  See below for key reasons to develop a DMP for your research project

 

Improves your publishing plan


The simplest benefit is that it is a very useful planning exercise.  Writing your DMP will help you anticipate the full range of privacy, ethical, storage, archiving and budgetary needs you'll have to meet with respect to your research data.  
 

  • Note that a DMP is intended to be a living document.  You may need to go back to your DMP more than once to update/revise it to reflect any unanticipated circumstances that crop up along the way.

 

Saves time

 

The act of writing a DMP will save you valuable time and effort over the long run as you'll be making your crucial data management decisions early on - allowing you to set up systems and standards that you can follow consistently throughout the project.
 

  • As a result, your data is liable be ready for deposit at the same time your research is due to publish / be presented. 
     
  • If you don't establish your plan early on you could find yourself spending unanticipated weeks at the end of your project trying to revise, organize and document your data to the standard that your publisher, funder and/or data repository requires.

 

Establishes roles & responsibilities
 

You and your research partners will know from the outset who is going to be responsible for which parts of your data plan - ensuring nothing is forgotten or unnecessarily duplicated.

 

Fulfills funding/professional mandates
 

  • NOTE: If you receive funding from the Tri-Agencies you may find that a data management plan is mandatory and must accompany your application. 
     
  • Many disciplines and institutions embrace the FAIR principles.  Completing a DMP will help you anticipate potential responsibilities, challenges and opportunities associated with making your data as FAIR as possible.   See the FAIR Principles box below for more information.