My instinct about numbers (i.e. incl. statistics) is that they should be reproducible: on-demand, with results and workings easily subjected to interrogation.

My instinct about numbers (i.e. incl. statistics) is that they should be reproducible: on-demand, with results and workings easily subjected to interrogation. In reality in many fields - my experience is in finance, but also in science - calculations are scattered across different languages and systems. This adds friction to any process about reproducing, understanding, analysing numbers. This is some motivation for calculang, a language for calculations I develop. https://github.com/calculang/calculang https://github.com/calculang/calculang For the HN crew it's an under-development(!) functional language with properties to permit flexible designs that can scale. It's for numbers and if you share the model alongside your numbers people can check them according to the model and see the workings. It goes well with visual number [dev/person]tools that I will release one of soon, and in the future watch for a browser extension for the workings behind numbers you are reading. Important, it won't address the raw data part of the problem, but where numbers following from that are concerned, it might get closer to that instinct.