Unifying Causality, Diagnosis, Repairs and View-Updates in Databases

TL;DR

This paper explores the deep connections between causality, diagnosis, repairs, and view-updates in databases, revealing shared concepts and results that enhance understanding of uncertainty management in big data contexts.

Contribution

It unifies various data management concepts by establishing formal links among causality, diagnosis, repairs, and view-updates, facilitating cross-disciplinary insights.

Findings

Identifies formal relationships among causality, diagnosis, repairs, and view-updates.

Highlights shared notions and results across these data management areas.

Provides a unified perspective on uncertainty management in databases.

Abstract

In this work we establish and point out connections between the notion of query-answer causality in databases and database repairs, model-based diagnosis in its consistency-based and abductive versions, and database updates through views. The mutual relationships among these areas of data management and knowledge representation shed light on each of them and help to share notions and results they have in common. In one way or another, these are all approaches to uncertainty management, which becomes even more relevant in the context of big data that have to be made sense of.