Multilingual Wikipedia Accessibility Dashboard

Designing a user-centered tool for cross-language content accessibility

With Prof. Ricarose Roque — 2023

I designed and built a multilingual dashboard that helps users navigate, compare, and understand Wikipedia content across languages. Leveraging the multilingual data pipelines I developed for a Wikimedia Research Fund project, I integrated behavioral statistics, cross-language link structure, and LLM-based summarization to support both monolingual and multilingual readers.

Most tools surface Wikipedia content in isolation. My work integrates user needs, behavioral insights, and multilingual data science to create an interface that makes cross-language context transparent—helping users see what information exists, what’s missing, and how narratives vary across language editions.

Research Question

How can we design tools that help monolingual and multilingual users access, compare, and contextualize information across different Wikipedia language editions?

Business Impact

Supports more inclusive and equitable information access across global users—informing product decisions in internationalization (i18n), knowledge accessibility, cross-language search, and user-facing LLM integrations.

What I did

  • Conducted qualitative and quantitative user research to understand barriers in accessing cross-language Wikipedia content.
  • Built multilingual data pipelines using cross-language link analysis, article metadata, and behavioral statistics.
  • Integrated generative LLM components to provide cross-language summaries and contextual cues.
  • Designed and evaluated a user-centered dashboard through iterative prototyping and user feedback.
  • Addressed diverse linguistic and cultural requirements to ensure usability across multilingual communities.

Why it matters

This project demonstrates how user-centered design and multilingual data science can work together to improve global information accessibility. It offers a scalable model for products that aim to support users navigating content across different languages, cultures, and knowledge ecosystems.