Writing Data Management Plan During Grant Application

In addition to other essential grant application requirements, funders increasingly require applicants to submit a data management plan (DMP).

The grant proposal can be viewed as a preliminary draft of a comprehensive data management plan. According to the European Commission’s Horizon 2020, project data must be freely accessible to promote data sharing and ethical data management by researchers.

What is a data management plan?

Data Management Plan is a detailed supplementary document that explains the rationale for choosing specific formats, approaches, standards, and methods for your project.

Although this is a detailed document, it should not exceed two pages.

The main objective of the data management plan is to describe the types of data generated, their management, and their availability and accessibility to other researchers.

1. Ideally, the data management plan should answer the following questions:
2. What type of data does your research generate?
3. How will data be collected or generated?
4. Who is responsible for data ownership?
5. What standards and formats will be used for data and metadata?
6. What policies and restrictions are there on data access and sharing?
7. How do you plan to store and preserve data, samples, and other research products?

Why is it important to create a data management plan?

For starters, creating a data management plan is so important that some funding agencies do not accept proposals that do not include one.

Additionally, the proposal must include a DMP even if no data is generated.

Additionally, a data management plan is important for the following reasons:

1. It increases the impact and discoverability of your research through the citations of the data it yields.
2. DMP provides evidence of your research in relation to previously published results.
3. It ensures copyright and ethical respect.
4. It also helps in long-term data storage and preservation.
5. Most importantly, it allows you to share your data with other researchers and benefit from interdisciplinary research.

What are the elements of a data management plan?

Required to create a data management plan that supports data reuse beyond the project lifecycle.

Although there is no official template for creating a DMP, a grant applicant must address the key elements mentioned below:

1.Data Description

This is a brief description of the information provided collect. In this section should include the amount of data to be generated, their nature, and the type of data that needs to be generated and collected during the project.

The types of data that need to be included in this section are text, educational materials, spreadsheets, images, 3D models, software, audio files, video files, field observation reports, surveys, review files, etc. Last but not least, you must cite and give due credit while incorporating data that has been published by others.

2. Metadata and formatting

This section includes a description of the format of your data and how it will be created, collected, stored, and distributed.

Additionally, it includes the rationale for any procedural and storage implications of the formats.

The purpose of this section is to provide results that other researchers can understand.

Additionally, you must include measures taken to comply with the project’s testing procedures.

3. Storage and preservation

The storage and preservation section addresses the long-term strategy for maintaining, preserving, and archiving data. It must include storage methods, backup procedures, and resources for retrieving research data.

You must indicate where your data will be kept (name the repository, archive, or database).

Also, mention the procedures your planned long-term storage location must maintain. It is necessary to specify the retention period for data that will be accessible beyond the lifetime of the project.

4. Security, access and sharing

This section describes technical and procedural safeguards for information containing sensitive information and how permissions, restrictions, etc. are applied. Additionally, you need to specify when and how the data can be accessed. This section should address the following issues:

1. Resources required to make the data available. Instructions for accessing the data.
2. Whether the data is paid or not.
3. How long the principal investigator retains the rights to use the data before it becomes mass distributed.
4. Details of any obstacles for commercial, patent or political reasons.
5. List of federal and funding requirements for data sharing and management.

5. Ethics and data protection

The ethics and privacy section of the data management plan describes how the applicant plans to handle informed consent and how the privacy of that data will be protected. All precautions should be included, such as: B. Protect participant confidentiality or other ethical issues that may arise.

6. Intellectual property rights

This section must include information from the natural or legal person who owns the intellectual property rights in the data. Similarly, the measures taken to protect these intellectual property rights and copyright restrictions should also be clearly stated.

7. Roles and responsibilities

In your data management plan, it is important to identify who will be responsible for data management. These people play a critical role, are responsible for data management during the project, and should have information about version control, naming conventions, etc.

8. Budget

Do not confuse the budget portion of your data management plan with the budget portion of your funding request. This includes the cost of preparing data and documents for archiving.

How to Write a Data Management Plan?

• Use standard or widely adopted formats for easy sharing and storage.

• Check preferred formats while depositing your data in discipline or institutional archives.

• Do not forget to state the expected data outputs.

• Mention the volume, type, content, quality, and format of the final dataset.

• Outline the metadata and documentation to make the data easily comprehendible.

• State the standards and methodologies used to collate and manage data.

• Give credit to persisting data while pointing out its relation to your data.

• All collaborative proposals or sub-awards are treated as a unified project. Hence, they must be combined in a single data management plan.

Although a supplementary document, we know that data management plan can have a strong impact on the acceptance of your grant proposal. Did this help you in understanding the nuances of writing a data management plan? How have you been structuring your DMPs?

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