Publishing and Querying Government Multidimensional Data Using QB4OLAP

Abstract

The web is changing the way in which data warehouses are designed, used, and queried. With the advent of initiatives such as Open Data and Open Government, organizations want to share their multidimensional data cubes and make them available to be queried online. The RDF data cube vocabulary (QB), the W3C standard to publish statistical data in RDF, presents several limitations to fully support the multidimensional model. The QB4OLAP vocabulary extends QB to overcome these limitations, and provides the distinctive feature of being able to implement several OLAP operations, such as rollup, slice, and dice using standard SPARQL queries. In this paper we present QB4OLAP Engine, a tool that transforms multidimensional data stored in relational DWs into RDF using QB4OLAP, and apply the solution to a real-world case, based on the national survey of housing, health services, and income, carried out by the government of Uruguay.