Research and Data Analysis

Research Data Management Plans (DMPs) Best Practices Training Course

Introduction

In today’s data-driven research environment, effective Research Data Management Plans (DMPs) are essential for ensuring data integrity, reproducibility, long-term storage, and ethical compliance. Research Data Management Plans (DMPs) Best Practices Training Course is designed to equip researchers, data stewards, project managers, and institutional leaders with the knowledge and tools to create and implement robust, FAIR-compliant (Findable, Accessible, Interoperable, Reusable) data management plans. Whether dealing with sensitive data, big data, or collaborative multi-institutional projects, this course emphasizes best practices, policies, and tools that enhance the lifecycle of research data from creation to archiving.

As funding agencies and institutions increasingly mandate DMPs, mastering their creation has become a critical research skill. This course covers the practical, technical, ethical, and legal dimensions of managing research data responsibly. With hands-on activities, case studies from various disciplines, and expert guidance, participants will learn how to design DMPs that align with funding body requirements, institutional policies, and global data-sharing standards.

Programme Curriculum

Research Data Management Plans (DMPs) Best Practices Training Course

Introduction

Course Objectives

By the end of the course, participants will be able to:

Understand the principles and importance of research data management.
Develop a complete data management plan (DMP) aligned with best practices.
Apply FAIR data principles in creating DMPs.
Identify and categorize types of research data and metadata standards.
Use DMP tools and templates such as DMPTool and DMPonline.
Address data privacy, ethics, and legal compliance in data sharing.
Plan for secure storage, backup, and data preservation strategies.
Evaluate and select repositories for long-term data archiving.
Integrate DMPs into grant proposals and institutional protocols.
Collaborate on multi-institutional DMPs and manage stakeholder roles.
Conduct risk assessments for data loss, misuse, or legal exposure.
Monitor and review DMPs throughout the research lifecycle.
Communicate data sharing strategies to funders and collaborators.

Target Audiences

Academic researchers and principal investigators
Research data stewards and managers
University research administrators
Postgraduate and PhD students
Institutional compliance officers
IT specialists managing research infrastructure
Policy makers in research funding bodies
Librarians and digital archivists

Course Duration: 5 days

Course Modules

Module 1: Introduction to Research Data Management (RDM)

Definition and scope of RDM
Importance of RDM in scholarly communication
Lifecycle of research data
Overview of institutional and funder mandates
Common challenges in RDM
Case Study: Failed publication due to poor data management

Module 2: Components of an Effective DMP

Structure and sections of a DMP
Common funder requirements (NSF, NIH, Horizon Europe)
Key considerations: documentation, formats, access
Aligning DMPs with project goals
Real-life DMP samples
Case Study: NIH-funded project with exemplary DMP integration

Module 3: Applying FAIR Data Principles

What are FAIR data principles?
Making data findable with metadata and DOIs
Ensuring data accessibility and licensing
Interoperability and machine-readability
Enhancing data reuse with proper documentation
Case Study: Cross-institutional collaboration using FAIR data

Module 4: Legal, Ethical, and Privacy Considerations

Data protection laws (e.g., GDPR, HIPAA)
Managing sensitive and personal data
Informed consent and data anonymization
Intellectual property and data ownership
Ethics approval process and documentation
Case Study: Human-subject data in a multi-country study

Module 5: Tools and Technologies for DMPs

Overview of DMPTool, DMPonline, ARGOS
Institutional platforms and integration with grant systems
Automating DMP updates and tracking
Metadata standards (Dublin Core, DataCite, etc.)
Interfacing with data repositories and catalogs
Case Study: Using DMPTool for NSF grant success

Module 6: Data Storage, Backup, and Preservation

Short-term vs long-term storage solutions
Cloud storage vs institutional repositories
Version control and data integrity
Backup scheduling and redundancy protocols
Data preservation formats and timelines
Case Study: Data recovery in environmental science research

Module 7: Sharing, Reusing, and Archiving Data

Data licensing (CC0, CC-BY, etc.)
Choosing appropriate data repositories (Zenodo, Dryad, etc.)
Embargo periods and controlled access
Citing data and assigning DOIs
Encouraging data reuse and impact tracking
Case Study: Open-access dataset with high citation impact

Module 8: Monitoring, Reviewing, and Updating DMPs

Importance of DMP reviews
Integrating DMP monitoring into project management
Feedback loops between teams and institutions
Adapting DMPs to evolving research or funding conditions
Reporting and audit trails
Case Study: Adaptive DMP in longitudinal medical study

Training Methodology

Interactive lectures with practical examples
Hands-on exercises using real DMP templates and tools
Group work and peer review of DMP drafts
Case-based learning across disciplines
Facilitated Q&A with research data management experts
Guided walk-through of DMP submission to funding platforms

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

DMP creation compliance data lifecycle management

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000