Data paradigms are metaphors we think with.
This talk describes how julia re-united a psychometrician's probability theoretical and technical thinking in "data".
I have thought in terms of
boxes, registers and memory adresses,
value bundles with C structures and Pascal records,
objects with inheritance in C++ and java,
vectors and data frames in R.
All useful but oblique.
Finally julia types liberated from tediously translating theory to implemetation.
More clarity, less mistakes.
Gregor Kappler carries out psychometric research and data science consulting, and is founder of FilingForest, a julia-focused startup developing solutions for fast unbiased measurement in graph data.
Gregor was initially trained as a mathematician and psychologist, has implemented solutions for semantic text analytics for his PhD in 2007, and developed psychometric models for measuring with texts.
He has worked as a lecturer and researcher at the University of Vienna and the University of Jena and worked on a series of predictive analytic projects for software vendors and customers.
Gregor has switched to Julia from R in 2018, and is creator of the CombinedParsers package which provides parser combinators for fast, recursive and type-save parsing in pure Julia.