Research Data Management, Open Data and Institutional Repositories Course

Introduction

Research data is a critical asset that drives innovation, academic excellence, and evidence-based decision-making. The Research Data Management, Open Data and Institutional Repositories Course is designed to equip professionals with the skills required to organize, store, share, and preserve research data effectively in compliance with global standards and institutional policies.

Research data management (RDM) is essential for ensuring that data generated through research activities is properly structured, documented, and preserved for future use. This course explores the full data lifecycle, from data creation and collection to storage, analysis, sharing, and long-term preservation. Participants will learn how to implement structured data management plans that enhance research quality and reproducibility.

Open data initiatives are transforming how knowledge is shared globally by promoting transparency, collaboration, and innovation. This course provides participants with an understanding of open data principles, licensing frameworks, and ethical considerations. It emphasizes how organizations can publish and share data responsibly while protecting sensitive and confidential information.

Institutional repositories play a key role in preserving and disseminating research outputs such as publications, datasets, and academic materials. This course examines how to design, implement, and manage institutional repositories that support accessibility, discoverability, and long-term preservation of research outputs in universities, research institutions, and organizations.

The course also highlights the importance of data governance, metadata standards, and interoperability in research data systems. Participants will gain insights into how structured metadata and classification systems improve data discoverability, reuse, and integration across platforms and disciplines.

By the end of the course, participants will be able to design and manage research data systems, implement open data strategies, and establish institutional repositories that support knowledge sharing, academic collaboration, and long-term data preservation.

Who Should Attend

• Research Data Managers
• Academic Researchers and Lecturers
• University Librarians and Archivists
• Information Management Professionals
• Data Scientists and Analysts
• Institutional Repository Managers
• ICT and Systems Administrators
• Knowledge Management Officers
• Policy Makers in Education and Research
• NGO and Development Researchers
• Science and Innovation Officers
• Consultants in Data and Information Systems

Duration

10 Days

Course Objectives

• Develop comprehensive understanding of research data management principles, enabling participants to design structured systems for organizing, storing, and preserving research data throughout its lifecycle.
• Equip participants with skills to develop and implement research data management plans that support data quality, reproducibility, and compliance with institutional and funding requirements.
• Strengthen capacity to design and manage open data systems that promote transparency, collaboration, and responsible sharing of research outputs across disciplines and institutions.
• Enable participants to establish and manage institutional repositories that support long-term preservation, accessibility, and discoverability of research data and academic outputs.
• Provide practical methodologies for applying metadata standards and data classification systems to improve organization and retrieval of research datasets.
• Enhance ability to ensure compliance with data protection laws, ethical standards, and intellectual property rights in research data management and sharing.
• Equip participants with skills to design data governance frameworks that support consistency, quality control, and accountability in research data systems.
• Strengthen competencies in integrating research data management systems with digital libraries, academic platforms, and cloud-based storage solutions.
• Enable participants to implement open data policies and licensing frameworks that support ethical and legal data sharing practices.
• Provide tools for evaluating institutional repository performance using metrics such as usage statistics, accessibility, and data reuse rates.
• Develop leadership capabilities in managing institutional data strategies and supporting research infrastructure development.
• Enhance ability to align research data management practices with global best practices, open science principles, and digital transformation strategies.

Comprehensive Course Outline

Module 1: Introduction to Research Data Management

• Concepts of RDM
• Importance in research
• Data lifecycle overview
• RDM frameworks

Module 2: Research Data Lifecycle

• Data creation and collection
• Data processing and analysis
• Data storage and preservation
• Data sharing and reuse

Module 3: Data Management Planning

• DMP development process
• Funding requirements
• Planning templates
• Implementation strategies

Module 4: Open Data Principles

• Open science concepts
• Data openness levels
• Benefits of open data
• Ethical considerations

Module 5: Data Governance in Research

• Governance frameworks
• Data ownership models
• Policy development
• Accountability systems

Module 6: Metadata for Research Data

• Metadata standards (Dublin Core, etc.)
• Data description techniques
• Interoperability models
• Metadata quality control

Module 7: Institutional Repositories Overview

• Repository concepts
• Types of repositories
• Functional components
• Repository architecture

Module 8: Repository Design and Implementation

• System selection
• Configuration and setup
• User interface design
• Integration with systems

Module 9: Data Storage and Preservation

• Long-term storage strategies
• Digital preservation methods
• Backup systems
• Archiving standards

Module 10: Open Data Licensing and Ethics

• Creative Commons licenses
• Intellectual property rights
• Ethical data sharing
• Legal frameworks

Module 11: Research Data Security

• Data protection measures
• Access control systems
• Encryption techniques
• Risk mitigation

Module 12: Data Sharing and Collaboration

• Data sharing platforms
• Collaborative research systems
• Cross-institutional sharing
• Data reuse strategies

Module 13: Digital Libraries and Repositories

• Library integration
• Digital asset management
• Repository workflows
• User access systems

Module 14: Evaluation of Repositories

• Performance metrics
• Usage analytics
• Quality assessment
• Continuous improvement

Module 15: Emerging Trends in RDM

• AI in data management
• Blockchain for research data
• FAIR data principles
• Open science evolution

Module 16: Implementation and Best Practices

• Implementation roadmaps
• Case studies and benchmarks
• Scaling repository systems
• Sustainability strategies

Training Approach

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

Certification

Upon successful completion of the training, participants will be awarded a certificate of completion by Steady Development Center.

Training Venue

The training will be held online. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, tutorials and all required training manuals. Any other personal expenses are catered by the participant.
For registration and further enquiries, contact us on:

• Tel: +254 701 180 097
• Email: training@steadytrainingcenter.com

Tailor-Made Option

This course can be customized to suit the specific needs of your organization and be delivered on-line to any convenient location.

Terms Of Payment

Upon agreement by both parties’ payment should be made to Steady Development Center’s official account at least 3 working days before training begins to facilitate adequate preparation.

Our Upcoming Training Schedule