OpenRefine Workshop: Cleaning, Exploring, and Contributing to Open Knowledge

In this workshop, participants will get more into OpenRefine, a powerful free and open-source software (FOSS) tool designed for cleaning, transforming, and refining messy data. The session will cover the fundamental aspects of using OpenRefine, guiding participants through hands-on activities to explore datasets, identify and correct errors, and prepare data for meaningful contributions to open knowledge platforms like Wikimedia Commons, Wikibase, and Wikidata.

Key Learning Outcomes:

• Data Cleaning and Transformation: Participants will learn how to clean and standardize messy data efficiently.
• Data Preparation for Open Knowledge Platforms: Guidance on preparing data for use in Wikimedia Commons, Wikibase, and Wikidata, ensuring contributions are accurate, reliable, and impactful.
• Reconciliation and Linking Data: A special focus will be placed on OpenRefine's reconciliation feature, which allows for matching data against external databases, enhancing the quality and connectivity of contributions.

As someone who has worked extensively with this feature, I will provide insights and practical tips to maximize its potential.

By the end of the workshop, participants will gain practical skills that enhance the quality and reliability of information on open knowledge platforms, ensuring their contributions are valuable and impactful to the global knowledge community. Additionally, technical contributors will discover how they can further enhance and extend OpenRefine's capabilities by engaging in its open-source development.

Outreachy Program Overview:

As a bonus, Ayushi will briefly introduce the Outreachy program, which offers internships to work on open-source projects, including OpenRefine. Participants will learn how they can get involved, contribute to open-source projects, and potentially secure an internship to deepen their skills and knowledge.