Transforming statistical linked data for use in OLAP systems

TLDR: An extract-transform-load (ETL) pipeline is used to convert statistical Linked Data into a format suitable for loading into an open-source OLAP system, and thus it is demonstrated how standard OLAP infrastructure can be used for elaborate querying and visualisation of integrated statistical Linking Data.

Abstract: The amount of available Linked Data on the Web is increasing, and data providers start to publish statistical datasets that comprise numerical data. Such statistical datasets differ significantly from the currently predominant network-style data published on the Web. We explore the possibility of integrating statistical data from multiple Linked Data sources. We provide a mapping from statistical Linked Data into the Multidimensional Model used in data warehouses. We use an extract-transform-load (ETL) pipeline to convert statistical Linked Data into a format suitable for loading into an open-source OLAP system, and thus demonstrate how standard OLAP infrastructure can be used for elaborate querying and visualisation of integrated statistical Linked Data. We discuss lessons learned from three experiments and identify areas which require future work to ultimately arrive at a well-interlinked set of statistical data from multiple sources which is processable with standard OLAP systems.