Social Choice Methods for Database Aggregation

  title={Social Choice Methods for Database Aggregation},
  author={Francesco Belardinelli and Umberto Grandi},
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… 



Computational Social Choice Meets Databases

A novel framework is developed that enriches the tasks currently supported in computational social choice with relational database context, thus making it possible to formulate sophisticated queries about voting rules, candidates, voters, issues, and positions.

How to Define Certain Answers

This work combines three previously used approaches, based on the semantics and representation systems, on ordering incomplete databases in terms of their informativeness, and on viewing databases as knowledge expressed in a logical language, to come up with an alternative framework for defining certain answers.

Optimal implementation of conjunctive queries in relational data bases

It is shown that while answering conjunctive queries is NP complete (general queries are PSPACE complete), one can find an implementation that is within a constant of optimal.

Distance semantics for database repair

A uniform way of representing repairs and their semantics clarifies the essence behind several approaches to consistency restoration in database systems, helps to compare the underlying formalisms, and relates them to existing methods of defining belief revision operators, merging data sets, and integrating information systems.

DA2 merging operators

Ontology merging as social choice: judgment aggregation under the open world assumption

The problem of merging several ontologies has important applications in the Semantic Web, medical ontology engineering, and other domains where information from several distinct sources needs to be

Graph Aggregation

A recently introduced formal framework for graph aggregation that is grounded in social choice theory is reviewed, with a main result a powerful impossibility theorem that generalises Arrow's seminal result regarding the aggregation of preference orders to a large collection of different types of graphs.

Binary Aggregation with Integrity Constraints

The generality of this framework is explored, showing that it makes available useful techniques both to prove theoretical results and to analyse practical problems, such as the characterisation of safe agendas in judgment aggregation in a syntactic way.

Arbitration (or How to Merge Knowledge Bases)

The properties that any arbitration operator should satisfy are investigated, in the style of Alchourron, Gardenfors, and Makinson, and proposed actual operators for arbitration are proposed.

Lifting integrity constraints in binary aggregation