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Day 3
Session 3

Hands on Exercise: Data Cleaning & Preparation with OpenRefine

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Find out more about this session

1. What is the main objective of this session?expand collapse

The session aims to teach participants how to clean, standardize, and enrich research data to improve quality, interoperability, and FAIR compliance using tools like OpenRefine.

2. What tools will I learn to use?expand collapse

The primary tool used in this session is OpenRefine, a powerful open-source application for data cleaning and transformation. Participants will also explore how to link data to external resources like Wikidata.

3. Who should attend this session?expand collapse

This session is ideal for early-career data stewards, researchers, and RDM professionals who work directly with raw data and want to learn practical cleaning and standardization techniques.

4. What kind of hands-on activities will be included?expand collapse

Participants will perform tasks like: Clustering and merging duplicate entries Standardizing formats (e.g., dates, numbers) Reconciling values with external authority sources Documenting each step for transparency and reproducibility

5. How does this session relate to FAIR principles?expand collapse

The session directly supports FAIR goals by enhancing data consistency, making it more Findable, Interoperable, and Reusable through structured cleaning and semantic linking.

6. Do I need to have prior experience with OpenRefine?expand collapse

No prior experience is required. The session is designed to be beginner-friendly, with step-by-step guidance on OpenRefine’s core functions.

7. Will there be example datasets provided?expand collapse

Yes, participants will work with real or mock datasets that simulate common cleaning challenges in research data management.

8. What will I take away from this session?expand collapse

You will gain: Practical skills in cleaning and preparing data Experience using OpenRefine A clearer understanding of how to make datasets machine-readable and reusable Awareness of best practices in documenting cleaning workflows

9. How does this session complement other bootcamp sessions?expand collapse

While other sessions focus on repository use, metadata, or policy, this one zooms in on the data itself, helping participants build the foundational skill of data preparation.

10. Is this session open or restricted?expand collapse

This session is a closed workshop. Participants will be selected upon priority of registration and profile compatibility. This session is one or the required sessions marked with a star in order for the participants to fill requirements and claim the Certificate of Completion.

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Meet Our Trainers & Mentors

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 Daniel Garijo

Associate Professor, Universidad Politecnica de Madrid

Madrid

 Daniel Garijo

Daniel Garijo Verdejo, Distinguished Researcher at UPM’s Ontology Engineering Group and Beatriz Galindo Awardee, focuses on e-Science, scientific software metadata, provenance, and knowledge graphs. He previously worked at USC’s Information Sciences Institute.

Wanna dive deeper and get certified?

Register here to join our closed and advanced-level workshops on FAIR Research Data Management & Data Stewardship.
Spaces are limited – priority is given to early-career data stewards with relevant experience that register first.

You will receive all necessary info's for Certificate of Completion upon selection.

Register

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Hands on Exercise: Data Cleaning & Preparation with OpenRefine

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OpenPlato is a modular learning platform developed by OpenAIRE to support training in Open Science, Research Data Management, and related topics across Europe. It offers self-paced courses, live sessions, and community-driven resources tailored for Research communities.

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