Data exploration through dot-driven development

Data literacy is becoming increasingly important in the modern world. While spreadsheets make simple data analytics accessible to a large number of people, creating transparent scripts that can be checked, modified, reproduced and formally analyzed requires expert programming skills. In this paper, we describe the design of a data exploration language that makes the task more accessible by embedding advanced programming concepts into a simple core language.

The core language uses type providers, but we employ them in a novel way -- rather than providing types with members for accessing data, we provide types with members that allow the user to also compose rich and correct queries using just member access (``dot''). This way, we recreate functionality that usually requires complex type systems (row polymorphism, type state and dependent typing) in an extremely simple object-based language.

We formalize our approach using an object-based calculus and prove that programs constructed using the provided types represent valid data transformations. We discuss a case study developed using the language, together with additional editor tooling that bridges some of the gaps between programming and spreadsheets. We believe that this work provides a pathway towards democratizing data science -- our use of type providers significantly reduce the complexity of languages that one needs to understand in order to write scripts for exploring data.