Description
Course Overview
Effective data curation and archiving are essential for maintaining data integrity, accessibility, and compliance across various sectors, including academia, research, and industry. This comprehensive 5-day training equips participants with practical skills in data management and preservation, focusing on Dataverse software—a leading open-source platform for data sharing and archiving.
Through interactive workshops, real-world case studies, and hands-on training, participants will learn how to curate, store, and manage data efficiently, ensuring compliance with data stewardship best practices.
Course Details
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Duration: 5 Days
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Level: Intermediate
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Delivery Mode: In-person / Virtual
Who Should Attend?
This training is designed for professionals involved in data management, research, and compliance, including:
✔ Data Managers & Librarians
✔ Researchers & Academics
✔ Data Scientists & Analysts
✔ IT Professionals in Data Management
✔ Archivists & Curators
✔ Compliance & Regulatory Professionals
Why Attend?
Personal Benefits
✅ Gain practical experience with Dataverse software
✅ Enhance your ability to organize, store, and preserve data
✅ Develop expertise in metadata application and data stewardship
✅ Boost your career prospects in data-related roles
Organizational Benefits
🏢 Improve data management and accessibility within the organization
🏢 Ensure compliance with data preservation standards
🏢 Enhance efficiency in data archiving processes
🏢 Strengthen long-term data stewardship practices
Course Objectives
By the end of this training, participants will be able to:
✔ Understand the fundamentals of data curation and archiving
✔ Use Dataverse software to manage and preserve data
✔ Apply best practices for metadata creation and management
✔ Ensure data integrity and long-term accessibility
✔ Implement compliance-driven data stewardship strategies
Course Outline
📌 Module 1: Introduction to Data Curation and Archiving
🔹 Overview of data curation and its importance
🔹 Key concepts and terminologies in data preservation
🔹 Introduction to Dataverse software and its functionalities
🔹 Best practices for implementing data curation strategies
📖 Case Study: Implementing a data curation strategy in a research institution
📌 Module 2: Metadata Standards and Practices
🔹 Understanding metadata and its role in data management
🔹 Common metadata standards and schemas
🔹 Applying metadata effectively in Dataverse
🔹 Techniques for metadata creation and organization
📖 Case Study: Metadata standardization in a university data repository
📌 Module 3: Using Dataverse for Data Management
🔹 Setting up and configuring Dataverse for data curation
🔹 Creating, managing, and sharing datasets
🔹 Uploading data and controlling user access permissions
🔹 Optimizing Dataverse for large-scale data projects
📖 Case Study: Managing large-scale research data projects using Dataverse
📌 Module 4: Data Preservation Techniques
🔹 Best practices for long-term data storage and security
🔹 Ensuring data integrity through validation techniques
🔹 Using Dataverse to implement effective preservation strategies
🔹 Troubleshooting common data preservation challenges
📖 Case Study: Preserving historical data collections in a museum archive
📌 Module 5: Compliance and Data Stewardship
🔹 Understanding data stewardship and its role in compliance
🔹 Legal and regulatory considerations in data management
🔹 Implementing compliance-driven data preservation strategies
🔹 Evaluating and improving data stewardship processes
📖 Case Study: Ensuring regulatory compliance in a corporate data repository
