OECD Wellbeing Explorer

Inspiration The OECD Well-being dataset offers a unique opportunity to explore the factors influencing quality of life across countries. With the rise of agentic analytics and AI-powered dashboards, we wanted to create an interactive, story-driven platform that transforms raw data into meaningful insights for policymakers, researchers, and curious citizens. Our goal was to make data exploration fast, beautiful, and intuitive.

What it does OECD Wellbeing Explorer is an interactive data app that allows users to:

Compare wellbeing metrics (life satisfaction, income, health, education, etc.) across OECD countries. Visualize trends over time with dynamic charts and maps. Filter by country, year, and metric to uncover patterns. Highlight relationships between economic, social, and environmental indicators. It turns complex datasets into clear, actionable stories.

How we built it

Dataset: OECD Well-being dataset (pre-selected challenge dataset). Platform: Plotly Studio with the Pro Plan.

Approach:

Uploaded and cleaned the dataset. Used natural language prompts to generate an initial app layout. Customized charts (scatter plots, choropleth maps, bar charts, time-series) for clarity and impact. Added interactive filters and annotations for storytelling. Optimized colors, fonts, and layout for a professional, accessible design.

Challenges we ran into

Token Management: Balancing between generating new apps and refining within the 400-edit limit. Data Complexity: The dataset had multiple metrics with varying scales, requiring careful normalization. Design Balance: Making the dashboard visually engaging without overwhelming the user. Accomplishments that we're proud of Built a fully interactive dashboard in under the challenge’s time limit. Created a smooth, intuitive user experience with clear insights. Successfully used AI-assisted analytics to speed up development while preserving control over design.

What we learned

Efficiency matters with AI token usage — most value comes from refining, not regenerating. Storytelling with data is as important as the charts themselves. Accessibility and clarity are key to keeping users engaged.

What's next for OECD Wellbeing Explorer

Add predictive analytics to forecast wellbeing trends. Include non-OECD countries for global comparisons. Enable user-uploaded datasets for custom analysis. Integrate AI-driven insight summaries that auto-generate key findings from selected filters.

Built With

• plotlystudio