TierraFirme is a wellbeing information platform designed to help people better understand the state of human wellbeing across countries and contexts. The primary target audience includes students, educators, and members of the general public who are curious about global wellbeing and want to explore it in a way that is accessible, meaningful, and ethical.
The platform is intended for exploration and learning rather than diagnosis or evaluation of individual wellbeing.
There is an abundance of global wellbeing data available today, but it is often difficult to understand, fragmented across sources, or presented in a way that feels overwhelming or disconnected from real life. As a result, many people struggle to form a clear picture of what wellbeing looks like across the world or how different factors interact to shape it.
TierraFirme aims to make global wellbeing data easier to understand and access. Our goal is for users to leave the website with new knowledge about the wellbeing of the world or a specific country they choose, and to feel empowered to reflect on their own wellbeing or that of others. By learning about global patterns and country-level insights, users can gain perspective and context that helps them think more intentionally about wellbeing in their own lives and communities.
The platform includes an interactive global map that allows users to explore wellbeing data for countries around the world. Each country presents a consistent set of curated wellbeing facts derived from the dataset.
In addition to the global exploration view, the site includes a personal area where users can select a country and indicate areas of interest. This personal area includes an AI-powered chatbot that allows users to engage more deeply with the wellbeing data, ask follow-up questions, and explore insights from a wellbeing-focused perspective.
TierraFirme addresses all six wellbeing dimensions outlined in the hackathon brief: physical, mental and emotional, social, economic, environmental, and cultural wellbeing.
Rather than focusing on a single dimension, the platform is designed to show how these dimensions coexist and interact. The wellbeing facts presented for each country draw from multiple categories in the dataset, ensuring that users are exposed to a holistic view of wellbeing. The AI chatbot further supports this by allowing users to explore insights through one or more wellbeing dimensions, depending on what they are most interested in.
Our intention is to give users access to a broad range of wellbeing information so they can be as informed as possible and reflect on wellbeing in a way that feels relevant to them.
AI is used in two main ways within the project. First, AI was used during development to translate raw data from the dataset into clear, human-readable wellbeing facts that are displayed on the website. This processing was done once and the results are stored in the system.
The main AI feature available to users is an interactive chatbot located in the personal area of the website. The chatbot allows users to engage with the wellbeing data conversationally, ask questions, and explore insights in more depth. The chatbot is designed to support understanding and reflection, not to provide medical, psychological, or professional advice.
Due to time and scope constraints, the platform cannot include every possible wellbeing metric available in the dataset. Instead, it prioritizes representing a meaningful and diverse selection of indicators that collectively reflect multiple dimensions of wellbeing.
The AI chatbot is intentionally limited in scope. It does not provide prescriptive recommendations or guidance that would require professional consultation, such as medical or mental health advice. Its purpose is to help users better understand the data and gain perspective, not to replace human expertise.
The chatbot does not access external or real-time sources, and the quality of responses may vary depending on the type of questions asked. User inputs are not stored, and no personal data is saved, in order to respect privacy and ethical considerations.
The project uses Supabase as the primary database. Python and web development tools are used to connect the database to the website and process the data. The website includes the frontend interface as well as the logic for displaying wellbeing facts and enabling interaction with the AI chatbot.
The project is implemented as a working prototype developed within the limited timeframe of the hackathon.
Users begin on the global view of the website, where an interactive map displays countries represented in the dataset. Hovering over or selecting a country allows users to explore general wellbeing facts related to that country.
From the main interface, users can navigate to a personal area where they answer a small number of optional questions about their interests. Based on these selections, they are presented with relevant wellbeing facts and can interact with the AI chatbot to explore the data further.
The website is designed to be flexible, allowing users to explore content in the way that feels most natural to them. Progress in the personal area is not saved between sessions, but the general country-level insights remain consistent so users can revisit or share what they have learned.
The platform does not prescribe specific actions. Instead, it supports awareness, reflection, and learning. By engaging with the wellbeing data, users can better understand how different factors contribute to wellbeing across countries and contexts. These insights can inform personal reflection, conversations with others, or further independent exploration of wellbeing-related topics.
With more time, we would expand the interactivity of the platform and further refine the AI features. This could include additional visualizations, more personalized but ethically constrained AI insights, and interactive elements that help users test or reflect on what they have learned.
We would also focus on improving code quality, performance, and accessibility, as well as exploring additional ways to make complex wellbeing data engaging without becoming overwhelming.