Integrate additional datasets for global indicator

**The idea** At some point I realized that the picture of the world we get from news is often very distorted. Most of the time we only see crises, conflicts and disasters. So I started wondering: Could the state of the world actually be summarized using real global data? **The project** This small project came out of that idea. It aggregates multiple global datasets and calculates a “World Indicator” score from them. The site updates automatically every 6 hours and tries to show whether things are overall improving or getting worse. **About AI** Yes, I did use AI tools (for example Claude Code) to help with parts of the development. But that’s not really the point of the project. The important part is the result: real datasets, transparent code and a reproducible indicator. **What is intentionally NOT behind it** No AI model No machine learning No predictions It's simply code combining real datasets and calculating a transparent score. **Why I built it** Honestly, mostly for myself. I wanted something that balances the constant feeling that “everything is getting worse”. Reality is usually more complex — some things get worse, others actually improve. **If you're curious** Live page: https://beko2210.github.io/World_report/ Open source repository: https://github.com/BEKO2210/World_report **Feedback** I'm genuinely interested in feedback — especially criticism of the methodology or ideas for additional datasets that could improve the indicator.