ObservableHQ

Code is often the best tool we have because it is the most general tool we have; code has almost unlimited expressiveness. Alternatives to code, as well as higher-level programming interfaces and languages, do well in specific domains. But these alternatives must sacrifice generality to offer greater efficiency within their domain.

If you can’t constrain the domain, it’s unlikely you’ll find a viable replacement for code. There is no universal replacement, at least not while humans primarily think and communicate through language. And it’s hard to constrain the domain of science. Science is fundamental: to study the world, to extract meaning from empirical observations, to simulate systems, to communicate quantitative results.

1. Teaching is the most impactful aspect of tool building.

2. Support is a powerful means of research.

3. Beware bells and whistles: interaction, animation, and other technical whizbangery have a cost. 🧙‍♂️

4. Visualization is a spectrum: from exploratory to explanatory.

5. In most cases, working with data should be 80% of the work of visualization.

6. Don’t commit to a specific visual form before seeing your data in it.

7. 10% of code causes 90% of bugs.

8. The internet will make you feel bad.

9. Don’t go it alone.

10. Try to have a good time.