Semantic Integration & Single-Site Opening of Multiple Governmental Data Sources

TL;DR

This paper presents S3-AI, a semantic web-based approach enabling unified querying of distributed government data sources across multiple sites while preserving data ownership and autonomy.

Contribution

It introduces S3-AI, a novel semantic integration framework that supports federated, ontology-mediated queries across distributed government data sources.

Findings

S3-AI effectively supports federated queries across multiple sites.

The approach preserves data ownership and autonomy.

Demonstrated successfully with a government IT helpdesk case.

Abstract

In many cases, government data is still "locked" in several "data silos", even within the boundaries of a single (inter-)national public organization with disparate and distributed organizational units and departments spread across multiple sites. Opening data and enabling its unified querying from a single site in an efficient and effective way is a semantic application integration and open government data challenge. This paper describes how NARA is using Semantic Web technology to implement an application integration approach within the boundaries of its organization via opening and querying multiple governmental data sources from a single site. The generic approach proposed, namely S3-AI, provides support to answering unified, ontology-mediated, federated queries to data produced and exploited by disparate applications, while these are being located in different organizational sites. S3-AI preserves ownership, autonomy and independency of applications and data. The paper extensively demonstrates S3-AI, using the D2RQ and Fuseki technologies, for addressing the needs of a governmental "IT helpdesk support" case.