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What is the Population of Interest: Population Modeling for BayesDB

BayesDB [1, 2] is a probabilistic programming platform that enables users to solve probabilistic data analysis problems using a simple, SQL-like language. Queries execute against generative population models (GPMs), a new abstraction that can be used to integrate data, metadata, qualitative domain knowledge, and quantitative models. Baseline quantitative models are typically built via an AI modeling assistant then refined by end users. A key challenge in using BayesDB is designing the template, or population schema, that defines the conceptual population of interest. The issues in population design are broadly analogous to relational database schema design, with additional concerns for statistical validity, modeling, and inference queries. Basic population modeling starts with considerations like: