Course Details

Empowering Research: Research Data Management (RDM) & Open Science Training Course

INTRODUCTION

"Advance your institution's research capabilities with our Research Data Management (RDM) & Open Science Training Course. Equip researchers and support staff with the skills to implement FAIR data principles (Findable, Accessible, Interoperable, Reusable) and foster a culture of open science. This Research Data Management (RDM) & Open Science Training Course provides comprehensive training on data planning, curation, sharing, and preservation, ensuring research integrity and maximizing impact. Learn to support researchers in navigating the open science landscape and build a robust data management infrastructure."

DURATION

10 days

TARGET AUDIENCE

This course is meticulously designed for:

• Researchers and Faculty: To understand and implement FAIR data principles.
• Research Support Staff (Librarians, Data Stewards): To assist researchers in RDM and open science practices.
• Research Administrators: To develop and implement institutional RDM policies.
• IT Professionals: Responsible for research data infrastructure.
• Graduate Students: To gain foundational knowledge in RDM and open science.
• Anyone involved in research data management and open science initiatives.

COURSE OBJECTIVES

Upon completion of this course, participants will be able to:

• Understand the principles and benefits of 1 research data management and open science.
• Implement FAIR data principles in research workflows.
• Develop data management plans (DMPs) that meet funder requirements.
• Utilize data repositories and platforms for data sharing and preservation.
• Understand metadata standards for research data.
• Apply data curation and quality control techniques.
• Navigate copyright and licensing issues in open data sharing.
• Promote open science practices and engage with researchers.
• Utilize tools and technologies for research data management.
• Understand the importance of data citation and persistent identifiers.

COURSE MODULES

Module 1: Introduction to Research Data Management (RDM) and Open Science:

• Overview of RDM and open science concepts.
• The importance of data management in research integrity.
• Benefits of open data sharing and collaboration.
• Key policies and initiatives in RDM and open science.

Module 2: FAIR Data Principles:

• Detailed explanation of Findable, Accessible, Interoperable, and Reusable data.
• Implementing FAIR principles in research projects.
• Using metadata and persistent identifiers for findability.
• Ensuring data accessibility and interoperability.

Module 3: Data Management Planning (DMPs):

• Developing data management plans that meet funder requirements.
• Identifying data types, formats, and storage solutions.
• Planning for data sharing and preservation.
• Using DMP tools and templates.

Module 4: Data Repositories and Platforms:

• Overview of data repositories and platforms (general and domain-specific).
• Selecting appropriate repositories for data sharing.
• Depositing data and metadata in repositories.
• Using repository APIs and interfaces.

Module 5: Metadata Standards for Research Data:

• Understanding metadata standards for research data (e.g., Dublin Core, DataCite Metadata Schema).
• Applying metadata schemas for data description and discovery.
• Metadata quality control and validation.
• Using controlled vocabularies and ontologies.

Module 6: Data Curation and Quality Control:

• Techniques for data cleaning and validation.
• Ensuring data quality and consistency.
• Developing data curation workflows.
• Applying data documentation and provenance tracking.

Module 7: Copyright and Licensing in Open Data Sharing:

• Understanding copyright and intellectual property issues.
• Creative Commons licenses and open data sharing.
• Developing data sharing agreements and policies.
• Managing data access and reuse.

Module 8: Promoting Open Science and Researcher Engagement:

• Developing communication and outreach strategies.
• Educating researchers on open science practices.
• Organizing workshops and training sessions.
• Building partnerships and collaborations.

Module 9: Tools and Technologies for RDM:

• Overview of data management tools and software.
• Using data analysis and visualization tools.
• Implementing data storage and backup solutions.
• Utilizing data management platforms and services.

Module 10: Data Citation and Persistent Identifiers:

• The importance of data citation in scholarly communication.
• Using persistent identifiers (DOIs, Handles) for data.
• Developing data citation guidelines and policies.
• Understanding data citation metrics and impact.

 CERTIFICATION

• Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

• Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

• Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

• Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com