WikiIndaba 2024/Proposal/Deep Dive into Advanced Wikidata
This is an open submission for WikiIndaba conference 2024 that has been reviewed by the members of the Programs committee. |
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Deep Dive into Advanced Wikidata | ||
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| Author(s): Micheal Kaluba, Baluku Brian | Username(s): Micheal Kaluba, B722N | Session type: Workshop | |
| Affiliation: Wikimedia Community User Group Uganda (WCUGU) | Session track(s): Educational Advocacy and Inclusion. | ||
| Abstract:
In this 60-minute workshop, participants will acquire a more profound comprehension of complex data modeling and querying in Wikidata, the free and open knowledge base that supports structured data across Wikimedia projects. This session is tailored for Wikimedia contributors, data scientists, researchers, and developers with basic knowledge of Wikidata and SPARQL. We will begin by delving into advanced topics in data modeling, including the use of items, properties, qualifiers, and references to create rich and intricate datasets. Participants will learn how to formulate complex SPARQL queries to effectively extract, filter, aggregate, and sort data. Live demonstrations will showcase practical examples, such as querying hierarchical data and performing statistical analyses. To ensure consistent and valuable input, this session will explore effective strategies for incorporating and modifying complex data models in Wikidata. We will delve into various techniques and best practices. The session will conclude with an interactive question-and-answer period and group discussion, offering an opportunity for attendees to share their experiences, ask questions, and collaboratively identify potential avenues for future growth and development. |
Audience : Wikimedia Contributors, Data Scientists, Researchers, Developers and Open Data Enthusiasts | ||
| Mode: In-person | |||
| Special requirements: Translation to other Languages and Basic Wikidata Knowledge. | |||
| How will this session be beneficial for the communities in the region?
This session aims to improve the representation of regional data on Wikidata by providing local contributors, data scientists, researchers, and developers with advanced skills in data modeling and querying. Participants are expected to gain proficiency in these techniques, which will enable them to contribute more effectively to the content and accuracy of Wikidata entries related to their respective regions. | |||
- Interested participants
(register below and ask your questions now to the session organiser)