Implementing Unified Why- and Why-Not Provenance Through Games

Using provenance to explain why a query returns a result or why a result is missing has been studied extensively. However, the two types of questions have been approached independently of each other. We present an efficient technique for answering both types of questions for Datalog queries based on a game-theoretic model of provenance called provenance games. Our approach compiles provenance requests into Datalog and translates the resulting query into SQL to execute it on a relational database backend. We apply several novel optimizations to limit the computation to provenance relevant to a given user question.