2023:Program/Research, Science, and Medicine/L8PK33-What I've learned from my 5-years PhD journey: Exploring Wikidata as a learning platform
Title: What I've learned from my 5-years PhD journey: Exploring Wikidata as a learning platform
Speakers:
Shani Evenstein Sigalov
Shani Evenstein Sigalov is an educator, researcher and free knowledge advocate, focusing on bridging gender, language and social gaps in free knowledge projects. Her research explores the interaction between Education, Technology, Innovation and Openness, and she has recently completed her PhD on “Learning with the Semantic Web: The Case of Wikidata as a learning platform”. A long time Wikimedian, Shani also serves as the Vice Chair of the Wikimedia Foundation’s Board of Trustees.
Room: Room 324
Start time: Fri, 18 Aug 2023 10:30:00 +0800
End time: Fri, 18 Aug 2023 11:00:00 +0800
Type: No (pretalx) session type id specified
Track: Research, Science, and Medicine
Submission state: confirmed
Duration: 30 minutes
Do not record: false
Presentation language: en
Abstract & description[edit source]
Abstract[edit source]
In this session I will share insights from a 5-years long PhD journey researching Wikidata as a learning platform, which involved over 120 members from our global community.
Description[edit source]
Since Tim Berners-Lee published his roadmap to the Semantic Web in 1998, the dream of a new, advanced and semantic web has captivated many. While there have been various attempts to realize this dream, none have been quite as successful at scale as Wikidata, Wikipedia’s youngest sister project, which launched in 2012. Wikidata is a free, multilingual, open knowledge-base that stores structured, linked open data. It has grown rapidly and as of December 2022 contains over 100 million items and millions of statements, all contributed by over 25000 volunteer editors, making it the largest semantic knowledge-base in existence. As such, it has been described as holding “many exciting possibilities” (Erxleben, Günther, Krötzsch, Mendez & Vrandečić, 2014). It was also claimed that it opens the door for a variety of new research opportunities and “potential applications across all areas of sciences, technology and cultures” (Vrandečić & Krötzsch, 2014), which were not possible before. WD’s strength and potential stems from the fact that it has strong ties with Wikipedia, the 6th most visited website in the world. Having a large semantic dataset means one can query it, and the bigger the dataset is the more accurate the results will be. This capacity already means that WD is changing the dynamics and interaction between people and knowledge and in effect holds many learning opportunities for its users. However, academic research regarding using semantic networks as learning platforms is almost non-existent. So, despite its obvious potential, we are yet to fully understand how to best utilize the Semantic Web, and more specifically WD, as a learning platform. My PhD research offers an opportunity to explore the Semantic Web as a learning platform, focusing on Wikidata as a main case study. To achieve this goal, and in order to gain a deeper understanding of learning processes, as well as document use cases and workflows, a mix-method research was designed, targeting early Wikidata adopters from around the world. Research instruments included an online questionnaire filled out by 121 users, followed by 60 semi-structured personal interviews with participants. The research focused on learning processes in Wikidata via two main user interactions - data curation and data extraction. These processes were examined through the lenses of 4 main aspects that influence these interactions with the WD platform: users’ motivations, users’ skills, the technology itself, and the community built around it. The results of this research shed light on learning opportunities while using semantic platforms, more specifically Wikidata’s potential as a lifelong learning process, enabling opportunities for improved Data Literacy and a worldwide social impact. The results are also discussed in a wider perspective, touching on implications for educators, researchers and industries.
Further details[edit source]
Qn. How does your session relate to the event themes: Diversity, Collaboration Future?
Yes. Wikidata has been instrumental in helping us track various knowledge gaps, making them visible, and trackable. In addition, the future of Wikidata, especially with the emergence of generative AI, is especially important, and requires further attention from our community. This session will hopefully help facilitate that.
Qn. What is the experience level needed for the audience for your session?
Everyone can participate in this session
Qn. What is the most appropriate format for this session?
Onsite in Singapore
Remote online participation, livestreamed- Remote from a satellite event
- Hybrid with some participants in Singapore and others dialing in remotely
- Pre-recorded and available on demand
