Provenance Traces

TL;DR

Provenance traces offer a formal, operational semantics-based approach to capturing and comparing data origin and derivation in database queries, ensuring consistency and fidelity in explanations of data processing.

Contribution

The paper introduces provenance traces as a formal, operational semantics-based model for provenance in the nested relational calculus, unifying and strengthening previous approaches.

Findings

Provenance traces can be derived from existing NRC provenance models.

Traces satisfy semantic guarantees of consistency and fidelity.

They provide a foundation for comparing and unifying provenance models.

Abstract

Provenance is information about the origin, derivation, ownership, or history of an object. It has recently been studied extensively in scientific databases and other settings due to its importance in helping scientists judge data validity, quality and integrity. However, most models of provenance have been stated as ad hoc definitions motivated by informal concepts such as "comes from", "influences", "produces", or "depends on". These models lack clear formalizations describing in what sense the definitions capture these intuitive concepts. This makes it difficult to compare approaches, evaluate their effectiveness, or argue about their validity. We introduce provenance traces, a general form of provenance for the nested relational calculus (NRC), a core database query language. Provenance traces can be thought of as concrete data structures representing the operational semantics derivation of a computation; they are related to the traces that have been used in self-adjusting computation, but differ in important respects. We define a tracing operational semantics for NRC queries that produces both an ordinary result and a trace of the execution. We show that three pre-existing forms of provenance for the NRC can be extracted from provenance traces. Moreover, traces satisfy two semantic guarantees: consistency, meaning that the traces describe what actually happened during execution, and fidelity, meaning that the traces "explain" how the expression would behave if the input were changed. These guarantees are much stronger than those contemplated for previous approaches to provenance; thus, provenance traces provide a general semantic foundation for comparing and unifying models of provenance in databases.