Research Data Management and Digital Repository Development Course

Course Introduction
Effective research data management has become a critical skill for institutions, researchers, and data-driven organizations as they embrace open science, digital scholarship, and long-term preservation of research outputs. This course provides an in-depth understanding of how well-structured data management practices and well-designed digital repositories enhance the visibility, accessibility, and sustainability of research assets across diverse disciplines.
With the growing volume, complexity, and diversity of research data, organizations increasingly require robust systems, policies, and workflows that support the full research data lifecycle. This course equips participants with the competencies needed to plan, organize, store, secure, and share data using modern technologies, globally accepted standards, and FAIR data principles. It emphasizes practical strategies for improving institutional data governance and compliance with evolving research policies.
Participants explore key components of research data management including metadata standards, data documentation, version control, access protocols, and preservation strategies while gaining hands-on experience with digital repository development. Through guided demonstrations and practical labs, learners interact with leading repository platforms, open-source infrastructures, and workflow tools that support sustainable, scalable repository systems.
The curriculum highlights the emerging role of automation, artificial intelligence, and interoperability technologies in enhancing data management efficiency. Learners gain exposure to cutting-edge approaches such as automated metadata extraction, AI-supported curation, persistent identifier systems, and machine-actionable data management plans, strengthening their ability to build future-ready repository ecosystems.
Using real-world case studies, the course demonstrates how universities, research centers, government agencies, and development organizations deploy institutional repositories to support scientific collaboration, open access publishing, policy implementation, and long-term data stewardship. Participants analyze best practices, governance structures, and sustainability strategies that ensure repositories remain relevant and resilient over time.
By the end of the course, participants will possess the knowledge and practical skills required to design and implement comprehensive data management workflows, develop institutional repositories, and align their practices with global standards. Whether improving organizational efficiencies or supporting open science, learners will be equipped to enhance data value, strengthen research integrity, and support long-term preservation and access.

 

Who Should Attend

 

• Research data managers, librarians, and information specialists responsible for organizing, storing, and preserving institutional research assets.
• University faculty, researchers, and graduate students seeking stronger skills in data planning, documentation, and digital preservation for academic projects.
• ICT officers, system administrators, and digital infrastructure teams implementing or maintaining institutional repositories and data management systems.
• Monitoring, evaluation, and learning (MEL) practitioners who manage datasets requiring standardized storage, sharing, and long-term archiving.
• Knowledge management and open science professionals supporting data access, dissemination, and compliance with institutional or donor requirements.
• Research administrators and project managers overseeing data-intensive projects and institutional data governance frameworks.
• Policy officers and compliance specialists engaged in data protection, open access policies, FAIR principles, and ethical data stewardship.
• Archivists, digital curators, and documentation personnel working with long-term preservation and digital continuity strategies.
• Consultants and analysts supporting digital transformation initiatives involving research data infrastructure and repository development.
• Development and donor-funded program staff needing robust data management approaches to ensure transparency, quality, and reusability.

Duration

5 days

Course Objectives

• Equip participants with a comprehensive understanding of the full research data lifecycle and how to design effective data management workflows that support long-term usability, preservation, and sharing.
• Strengthen participants’ abilities to create detailed data management plans aligned with institutional policies, donor requirements, and FAIR data principles to ensure responsible and transparent research practices.
• Build capacity in implementing metadata standards, documentation frameworks, and controlled vocabularies that enhance data discoverability, interoperability, and scientific reproducibility.
• Develop participants’ skills in selecting, configuring, and managing digital repository platforms, including open-source solutions that support sustainable and scalable research data ecosystems.
• Enhance participants’ understanding of digital preservation strategies, persistent identifiers, version control, and archival standards required for long-term stewardship of research outputs.
• Provide hands-on experience with repository workflows including ingest, curation, quality control, access permissions, and ongoing maintenance of digital collections.
• Strengthen capacity for applying automation, AI-supported curation tools, and machine-actionable data methods to improve processing efficiency and data quality within repositories.
• Improve participants’ knowledge of legal, ethical, and governance considerations, including data protection, copyright, licensing, and risk management in research data environments.
• Support learners in implementing institutional data governance structures that ensure compliance, transparency, and alignment with global research data management standards.
• Enable participants to design organization-specific strategies for scaling repository infrastructures, building institutional capacity, and promoting open access and data sharing cultures.

Comprehensive Course Outline

Module 1: Foundations of Research Data Management

• Understanding the research data lifecycle and key components of effective data stewardship.
• Principles of data organization, documentation, and version management for complex datasets.
• Overview of global RDM standards, FAIR principles, and open science requirements.
• Challenges and opportunities in modern research data ecosystems.

Module 2: Data Management Planning and Compliance

• Developing detailed data management plans aligned with institutional and donor policies.
• Incorporating machine-actionable DMP tools for automation and improved compliance tracking.
• Integrating risk management, ethical considerations, and consent frameworks into DMPs.
• Ensuring alignment with data protection regulations and responsible data sharing practices.

Module 3: Metadata Standards and Interoperability

• Using metadata schemas such as Dublin Core, DataCite, and domain-specific standards.
• Implementing controlled vocabularies and ontologies for structured data organization.
• Techniques for automated metadata extraction and quality assurance.
• Ensuring interoperability across repositories and external systems.

Module 4: Digital Repository Platforms and Architectures

• Evaluating and selecting repository platforms such as DSpace, Dataverse, EPrints, and Invenio.
• Understanding repository architectures, components, and workflows for scalable deployment.
• Integrating APIs, automation tools, and interoperability protocols within repositories.
• Hands-on configuration and setup of repository modules and user interfaces.

Module 5: Ingest, Curation, and Digital Preservation

• Designing ingest workflows, including submission guidelines and quality assurance checks.
• Effective curation strategies for ensuring data accuracy, completeness, and documentation.
• Implementing digital preservation standards, versioning, and long-term access strategies.
• Using persistent identifiers such as DOIs, ORCID, and Handle Systems for continuity.

Module 6: Access, Licensing, and Rights Management

• Creating access protocols and permission systems for sensitive and open datasets.
• Applying copyright, licensing, and Creative Commons frameworks for legal data sharing.
• Balancing openness with compliance through controlled access and anonymization strategies.
• Managing restricted, embargoed, and public-access content within repositories.

Module 7: Data Governance and Institutional Frameworks

• Establishing institutional data governance policies and oversight structures.
• Implementing roles, responsibilities, and workflows for effective data stewardship.
• Aligning data management initiatives with organizational research strategies.
• Monitoring compliance through audit trails, reporting tools, and quality metrics.

Module 8: Automation, AI, and Emerging Technologies

• Using AI-assisted tools for metadata generation, data cleaning, and rapid curation.
• Integrating workflow automation for ingest, classification, and quality validation.
• Understanding machine-actionable metadata and its role in next-generation repositories.
• Exploring emerging technologies such as blockchain and decentralized repository networks.

Module 9: Repository Sustainability and Capacity Building

• Developing long-term sustainability strategies for repository infrastructure.
• Building internal capacity through training, governance frameworks, and resource allocation.
• Creating institutional support structures for long-term digital preservation activities.
• Managing operational costs, infrastructure planning, and repository expansion models.

Module 10: Practical Implementation and Case Studies

• Hands-on exercises using real datasets and repository workflows for practical skill development.
• Reviewing global repository case studies from universities, research institutes, and NGOs.
• Identifying implementation challenges and designing context-appropriate solutions.
• Developing institutional implementation roadmaps and repository deployment plans.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.