Research Data Curation Training Course
Research Data Curation Training Course equips participants with practical knowledge of research data management, FAIR Data Principles, metadata standards, digital preservation, data governance, research integrity, cloud repositories, artificial intelligence applications, and international best practices for sustainable research data curation.
Course Overview
Research Data Curation Training Course
Introduction
Research Data Curation is a strategic discipline that ensures research data is properly collected, organized, documented, preserved, shared, and reused throughout its lifecycle. As research institutions, universities, government agencies, healthcare organizations, and private enterprises increasingly adopt digital transformation, effective data stewardship has become essential for improving research quality, transparency, reproducibility, compliance, and innovation. Research Data Curation Training Course equips participants with practical knowledge of research data management, FAIR Data Principles, metadata standards, digital preservation, data governance, research integrity, cloud repositories, artificial intelligence applications, and international best practices for sustainable research data curation.
Participants will gain practical skills in designing data management plans, implementing metadata frameworks, ensuring regulatory compliance, protecting sensitive research information, improving data discoverability, and supporting open science initiatives. Through practical exercises and global case studies, the course demonstrates how modern data curation enhances research collaboration, institutional reputation, funding opportunities, policy compliance, and long-term accessibility of valuable research assets.
Course Objectives
After completing this course, participants will be able to:
- Understand modern Research Data Curation principles.
- Develop effective Data Management Plans (DMPs).
- Apply FAIR Data Principles for research excellence.
- Implement international metadata standards.
- Improve research data quality and integrity.
- Establish digital preservation strategies.
- Strengthen research data governance frameworks.
- Enhance data security and privacy compliance.
- Support Open Science and research collaboration.
- Utilize cloud-based research repositories.
- Integrate AI-powered data curation technologies.
- Monitor research data lifecycle management.
- Improve institutional research visibility and impact.
Organizational Benefits
- Improved research quality and reproducibility.
- Enhanced regulatory compliance.
- Increased research funding competitiveness.
- Better institutional knowledge preservation.
- Stronger research collaboration.
- Improved data security and confidentiality.
- Greater research transparency.
- Reduced data loss risks.
- Higher research productivity.
- Increased global research visibility.
Target Audiences
- Research Scientists
- University Researchers
- Research Administrators
- Data Managers
- Librarians and Archivists
- Laboratory Managers
- Government Research Officers
- NGO Research Professionals
Course Duration: 5 days
Course Modules
Module 1: Foundations of Research Data Curation
- Research data lifecycle management
- FAIR Data Principles
- Research data policies
- Open Science concepts
- Roles of data stewards
- Case Study: European Open Science Cloud implementation
Module 2: Research Data Planning and Collection
- Data Management Plans
- Research data documentation
- Data collection standards
- Data organization techniques
- Quality assurance methods
- Case Study: NIH Data Management Policy
Module 3: Metadata and Documentation
- Metadata fundamentals
- International metadata standards
- Data cataloguing
- Persistent identifiers
- Documentation best practices
- Case Study: DataCite metadata framework
Module 4: Data Storage and Digital Preservation
- Digital preservation principles
- Repository selection
- Cloud storage solutions
- Backup strategies
- Long-term accessibility
- Case Study: UK Data Service preservation model
Module 5: Data Governance and Compliance
- Research governance frameworks
- Ethical data management
- Privacy regulations
- Intellectual property management
- Risk management
- Case Study: GDPR compliance in European research
Module 6: Data Sharing and Open Science
- Open data publishing
- Repository submission
- Data licensing
- Collaborative research platforms
- Data citation practices
- Case Study: Zenodo Open Research Repository
Module 7: Emerging Technologies in Data Curation
- Artificial Intelligence applications
- Machine learning for data quality
- Automation tools
- Research analytics
- Digital innovation
- Case Study: AI-assisted research repositories
Module 8: Institutional Data Curation Strategy
- Institutional policy development
- Capacity building
- Performance monitoring
- Sustainability planning
- Continuous improvement
- Case Study: Harvard University Research Data Management Program
Training Methodology
- Interactive expert-led presentations
- Practical demonstrations and workshops
- Hands-on metadata development exercises
- Group discussions and collaborative learning
- Software demonstrations and repository practice
- Global case study analysis
- Individual and team assignments
- Research data management simulations
- Knowledge assessments and feedback
- Action planning for workplace implementation
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.org or call +254724527104
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 DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.