How to write your Data Management Plan
Welcome to this self-study course about research data management. In this course you will learn more about how you can manage your research data.
A lot of material of that version of the Learn to write your DMP course has been developed by RDM Support of University of Utrecht.
With all questions about this course you can contact: firstname.lastname@example.org.
By VIB Bioinformatics Core, ELIXIR Belgium and Helis Academy
- LiaScript: this course as e-learning resource
The course consists of 6 chapters, divided in three categories.
- Prepare Data collection
- Prepare Data documentation
- Handle Data storage
- Handle Data security
- Share Data selection and preservation
- Share Data availability for reuse
Each chapter starts with an introduction and ends with an assignment to write that part of your data management plan that corresponds with what you have just learned. You are currently in the introd uction chapter. In this chapter you will learn more about the course and the learning environment. The course ends with chapter 7, ‘Rounding up’.
Data Management Plans The assignment throughout the course is to fill your own data management plan. At the end of each chapter you will be asked to log into DMPonline. With the content in this course, you should be able to apply this to your research project.
Questions about the course If you have technical questions, please contact email@example.com. If you have content related questions, please contact RDM Support: firstname.lastname@example.org. All feedback is welcome, as this is still a beta version. Based on feedback from users, more content may be added or existing content may be changed to a different form.
Technical requirements Some activities use HTML5. Make sure your browser has installed the latest updates. If an activity doesn’t work, we recommend you use another browser.
Licenses and credits We wish you a lot of fun with the course and we hope it turns out to be a useful learning experience. The content of the course is adapted from an online course of University of Utrecht.
We are giving overviews on why it is important to manage your research data, user stories about data loss, funder requirements, and RDM Support.
Introduction to Data Management Plans
Preparatory steps for Data collection and Documentation
- Will you use existing data?
- What data will you collect or create?
- How will the data be collected or created?
- How will you manage rights issues?
- What are the costs involved in managing and storing your data?
Prepare: Data collection
Prepare: Data documentation
Storing your data properly can save you a lot of time (in finding and interpreting) and frustration (in not losing it). Moreover, when properly structured and annotated during research, you’ll have your data preserved and/or shared with minimal effort at the end of your research.
Handle: Data Security
Handle: Data storage
Research should be transparent and you should always be able to revert back to your data if necessary and be able to show others how you came to your results. Therefore, your research data with all information reasonably necessary for verification needs to be preserved. With well-managed and preserved research data, you can defend yourself against allegations of mistakes. You can also prevent wrong conclusions from further spreading into the scientific community if there really are mistakes.
Share: Data availability for reuse
Share: Data selection and preservation
OtherAssorted other tutorials
Overview of other training resources collected by UGent RDM team
This material is maintained by:Alexander Botzki
For any question related to this topic and the content, you can contact us at email@example.com
This material was contributed to by:Alexander Botzki
RDM training by the University of Edinburgh: MANTRA
RDM training by the University of Melbourne: Managing Data @ Melbourne
RDM website of University of Amsterdam: Essentials for Data Support
Delft University of Technology: Research Data Services
Wageningen University & Research: Essentials for Data Support
Digital Curation Centre: Essentials for Data Support
UK Data Archive: Essentials for Data Support
Australian Networked Data Services (ANDS): Essentials for Data Support
ORION e-learning course: Essentials for Data Support