Abstract

Working in the open and making source code and data freely available are essential to modern scientific practice, but don’t by themselves help us understand the complex relationships between data and computational outcomes. In this talk I will present (and demonstrate) techniques from programming languages research which automate the creation of data-driven software able to reveal how outputs were computed from data. Our current prototype can automatically highlight relevant parts of an underlying dataset as visual outputs are selected; extending this to produce computational “explanations” of how those data were aggregated or transformed during the computation of the selected outputs is work-in-progress. I will close by talking about some longer-term challenges for this idea in the context of climate science, and the prospects for language-based transparency taking us beyond open source and open data to computations which are able to explain how they work.

Roly is a programming languages researcher at the Institute of Computing for Climate Science, University of Cambridge and a former member of the Research Engineering Group at The Alan Turing Institute.