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Research Data Management (RDM): Data Management Plans

Data management essentials for Melbourne Polytechnic researchers

The Data Management Plan (DMP): Unpacked

A Data Management Plan (DMP) is a document which describes and clarifies how the data will be managed across the life of the research project, beginning with the Plan & Design stage (as indicated on the diagram below), and progressing through the other stages of the research cycle. 

Image creator:  Gaelen Pinnock
Image licensed under the Creative Commons Attribution-Share Alike 4.0 International  
Image source: https://commons.wikimedia.org/wiki/File:UCT_RDM_lifecycle_(all_icons).svg

Components of a Data Management Plan

It's the researcher's responsibility to construct the DMP.  However, organisations overseeing or sponsoring the research (such as universities or funding bodies) may have policy mandates which govern the specific information to be included in your DMP.  Also, some organisations provide ready-made DMP templates, which researchers are expected to complete and submit.  The following sections are commonly included in DMPs:

Data sources  (the data's origins, and the researcher's supply of information about it)
Data types (the types of information to be collected)
Data input methods  (methods used for data analysis; singular analyst or group; computer programs used; data input information)      
Ethical and legal restrictions  (data security; data disposal; data storage)
Responsibility for data  (responsible parties; succession planning)
Backup strategy  (data protection issues and practices)
Data organisation  (data organisation planning; file naming conventions)  
Plans for data sharing  (data reuse issues; long term storage; file management; licensing) 
Note:  this last section is known to be the most difficult in the RDM Plan

Source:  Sewell, Clare  2020,The No-Nonsense Guide to Research Support and Scholarly Information, Facet Publishing, London

DMPs: The Benefits

Data Management Plans help researchers to:

  • plan ahead, and prepare to handle various requirements, processes, or issues before they arise
  • clarify how data will be collected, stored, organised and arranged
  • identify potential risks (such as data loss) and develop strategies for limiting risk 
  • account for funder's expectations and requirements
  • identify issues associated with copyright, privacy, intellectual property, and ownership of data
  • organise and manage files:  selecting appropriate file formats; deciding file naming rules; and version control 
  • take account of budget considerations

Source: Imed Bouchrike 2020,  Guide2Research "What is RDM?"  

Recommended: Public DMP

Public DMPs @ DMP Online
... a long list of publicly-shared DMPs, for viewing   ...

The Public DMPs will give you ideas about:
Planning
Documenting
Formatting
Sorting
Confidentiality, Ethics & Consent
Copyright
Sharing

Recommended Resource

A guide from the Australian National Data Service
Source:  ANDS Guides and Resources : Data Management Plans  
                              
                          

Recommended: Free DMP Tool / Template

DMP Tool  
-  helps researchers to create DMPs  
-  free for anyone to use
-  open-source, online application
-  a shared resource for researchers
-  registration required

DMP Tool:  Quick-Start Tutorial
DMP Tool:  Data Management Guidance