It makes you think ahead how to handle your data throughout the entire research process, and things you need to sort out or clarify at the outset. A well-thought-out DMP is like a guiding map, which helps to prevent problems from happening and ensures the data are managed properly for present and future use. Therefore, with or without a funder's requirement, creating a DMP is always beneficial for your research.
To get the benefits out of a DMP, researchers have to do some prior thinking and preparation for certain matters or issues that may need to be addressed.
|Matter / Issue||Resulting Benefits|
|File naming convention and structure||Have a well-organized filing system that facilitates file retrieval and version tracking.|
|Data storage and backup||Prevent data loss.|
|Data description and documentation||Resulting datasets are discoverable, understandable and reusable.|
|Sensitive and personal data handling||Prevent disputes caused by data leakage.|
|Intellectual property and copyright||Avoid allegations of rights infringement.|
|Data archiving and sharing||Archiving and sharing datasets in an open repository can increase their visibility and impact.|
|Long-term preservation||Data maintained regularly can be used repeatedly for future research.|
Depends on the nature of your research, you may or may not be concerned with some of the above items. Yet, there are more details you need to include in your DMP, which are mostly basic and factual information.
A DMP may be as simple as a one- to two-page document, and you can update it as often as needed. The following is a list of the commonly seen elements. Some funders may have their own requirements.
If you are unfamiliar with some of the topics listed above, there are online guides that can help, such as:
Apart from reading guides, studying other researchers' DMPs is a good way to gain practical knowledge.
There are many things a beginner can learn from other researchers' DMPs, such as their styles and practices. Some universities and organizations share examples of DMP on the web for public access like the ones below. While they may not be exemplary plans that suit all your purposes, you can find in them different data management approaches that can help to enrich your skills in crafting your own DMP.
Supply and Demand of Proteins During Neuronal Growth and Extension [UC San Diego Sample NSF Data Management Plans]
|Noncommutative surfaces and Calabi-Yau algebras [UC San Diego Sample NSF Data Management Plans]|
Two social science examples [By University of Leeds via the Digital Curation Centre (DCC)]
|Court Workforce Racial Diversity and Racial Justice in Criminal Case Outcomes in the United States [By University of Washington via DMPTool]|
|COVID-19 Oral Histories Project [University of Texas at San Antonio via DMPTool]|
Visit the sites inside the square brackets to view more DMPs for other subject fields.
If you are ready, go to the next box to try creating a DMP for your project.
You can try creating a DMP using the template developed by the Library on DMPTool@HKUST, which is a local version of the DMPTool at HKUST. The template includes questions in 6 areas. You can save your DMP in DMPTool@HKUST and come back anytime for future revisions. Exports options are also available. Guiding information and examples are provided for each question to help you finish the plan.