Research Data Management Planning
Preparing a data management plan for your research project will save you time and effort during your project. It will enable you to make informed decisions early in the project that will impact the effort required to achieve the best outcomes. For example, consideration of how you will de-identify data for possible future sharing will inform the structure of data collection tools, data records and the content of consent forms.
Research data management includes all the activities associated with data other than using the data. Examples include:
- data storage and backup
- organising data into directories/folders and using meaningful file names
- archiving final state data for long-term preservation
- describing datasets for future reuse and discovery
- data sharing or publishing
- collaboratively creating and using data with other researchers
- ensuring security of confidential data
- synchronising data between desktop, laptop, USB key, cloud storage, etc.
While data management does not directly produce results, it is an unavoidable consequence of working with data. Good data management choices can save you time and effort in the long term and help increase the value of your data in the future.
A research data management plan is a document that describes
- what data will be created
- what policies (funding, institutional, ethical, and legal) will apply to the data
- ownership, access and protection of intellectual property
- how the data will be described and possibly shared and/or reused
- what data management practices (backups, access control, preservation and archiving) will be used
- what facilities and equipment (hard-disk space, backup server, repository) will be required and
- who will be responsible for each of these activities.
The best time to develop your data management plan is at the beginning of your research. Any time spent on creating a robust and easy to use data management framework will be rewarded many times over during your research.
Preparing a research data management plan will help you make good data management choices, which can save you time and effort in the long term and help increase the value of your data in the future.
Many international funding bodies require a formal research data management plan as part of the funding application including agencies such as the US National Science Foundation (NSF) Data Management Plan Requirements and the UK Medical Research Council (MRC) which states that researchers "ensure that data are properly preserved for sharing and informed use beyond the originating research teams... [through] planning & implementation of effective data management in research".
While Australian funding agencies do not currently require this, it is anticipated that the Australian Research Council (ARC) and the National Health and Medical Research Council (NHMRC) may soon require data management planning within the funding application process.
The Australian Code for the Responsible Conduct of Research released by ARC and NHMRC, requires aspects of data management such as ownership, ethics, data sharing, storage, retention and disposal to be well-documented by researchers. In order to receive NHMRC funding, researchers must comply with the code.
"Failure to comply with requirements from funding bodies like the ARC or NHMRC may jeopardise future research funding." Source: ANDS and Data Storage Guide, ANDS 2011
The Deakin Library has produced a Data Management Toolkit for researchers, designed as a guide based on the Model Data Management Toolkit for Researchers (2008), Legal Framework for e-Research Project and Open Access to Knowledge (OAK) Law Project - QUT.
It is designed as a checklist, prompting you to answer a series of questions regarding ownership and rights relating to research data. This data management toolkit has been designed with researchers in mind. It provides guidelines on implementing a research data management plan, and can assist you in ascertaining responsibilities in relation to managing your research data.
Mantra is a free online data management training course that has been developed by the University of Edinburgh's data centre, EDINA. The course provides guidelines for good practice in research data management for researchers who work with digital data and would like to learn more about managing their research data.
Research Data MANTRA online course by Data Library and EDINA, University of Edinburgh is licensed under a Creative Commons Attribution 2.5 UK: Scotland License.
Data Management Planning (ANDS) Includes links to other Australian National Data Services information
Data Management Checklist (UK Data Archive) Questions to ensure good data practices
Data Management Manual (ANU) Highlights key aspects of data management and writing a plan
Data Management Planning (QUT) Guidelines for management of research data
Data Management Planning (Monash University) Includes a draft checklist for HDR students
Data Management Plans (Digital Curation Centre - DCC) Links to various resources, including an online tool
Data Planning Checklist (MIT Libraries) Brief checklist with links to further information
Research Data Management (University of Melbourne) Includes guidelines, checklist and a template
Data Plan (Curtin University) Check list with links to further instructions