# Social Choice Methods for Database Aggregation

## TL;DR

This paper explores how to aggregate multiple databases from different sources using social choice theory, ensuring integrity constraints are maintained and query answers are consistent after aggregation.

## Contribution

It introduces classes of aggregators that preserve integrity constraints and characterizes query languages for consistent answers in aggregated databases.

## Key findings

- Identifies aggregators respecting integrity constraints in combined databases.
- Characterizes query languages with consistent answers post-aggregation.
- Provides a foundation for applying social choice techniques to database knowledge representation.

## Abstract

Knowledge can be represented compactly in multiple ways, from a set of propositional formulas, to a Kripke model, to a database. In this paper we study the aggregation of information coming from multiple sources, each source submitting a database modelled as a first-order relational structure. In the presence of integrity constraints, we identify classes of aggregators that respect them in the aggregated database, provided these are satisfied in all individual databases. We also characterise languages for first-order queries on which the answer to a query on the aggregated database coincides with the aggregation of the answers to the query obtained on each individual database. This contribution is meant to be a first step on the application of techniques from social choice theory to knowledge representation in databases.