BACKGROUND
In today’s data-driven world, ensuring your data is Findable, Accessible, Interoperable, and Reusable (FAIR) is crucial for maximizing its impact and utility. Applying
FAIR principles allows you to enhance the visibility and accessibility of your research, facilitate collaboration, and increase the reproducibility of your findings.
WORKSHOP GOAL
Join us for an interactive workshop where we’ll harness the power of LEGO® bricks to demonstrate how you can make your survey data FAIR:
Findable,
Accessible,
Interoperable, and
Reusable.
In this engaging session, you’ll:
| Learn the significance of documentation and metadata in achieving FAIRness. |
| Discover practical tools and best practices to seamlessly integrate FAIR principles into your projects. |
| Have a blast building with LEGO® bricks while enhancing your data management skills. |
WORKSHOP CONTENT
LEGO® Challenge and Introduction to FAIR Principles
After a welcome and a short introduction round, we will start with a hands-on LEGO® challenge. This engaging activity will set the stage for an introduction to the FAIR principles, helping you understand their relevance and application in a fun and interactive way.
Tools, Best Practices, and Templates to Make Your Survey Data FAIR
In the second part, we will discover various tools, resources, and best practices that facilitate the integration of FAIR principles into your projects. You will learn how to document your data effectively, use metadata standards, and ensure your data is interoperable and reusable. In an open discussion and Q&A session, we will address specific challenges and share experiences in making data FAIR.
TARGET AUDIENCE & PRIOR KNOWLEDGE
This course is suitable for researchers who work with survey data (open to all disciplines; PhDs, Postdocs). No prior knowledge is required.
TECHNICAL REQUIREMENTS
Bring your own computer.
ABOUT THE TRAINER
With a diploma in Sociology, Heike Thöricht joined the University of Innsbruck in 2018. She contributed to the
e-Infrastructures Austria Plus , its successor project
FAIR Data Austria, and a Research Data Management initiative at the university. Since June 2022, she has served as a Data Steward at the Data Science Center (DSC), advising researchers from the social sciences and humanities within the UBremen Research Alliance on FAIR principles, data management plans, and research data publication.