MS.3. Business Intelligence over Linked Open Spatio-Temporal Data

OpenStreetMap is a collaborative project for creating a freely editable map of the world. It was inspired by Wikipedia and provides well-known Wiki features such as an edit-tab and a full revision history of the edits. However, rather than editing articles, users edit geographic entities, the three main ones being Nodes, Ways, and Relations. The data is stored in a relational database, and can be accessed, queried and edited by using a Web API.

On the other hand, there is a growing interest from public organisations in publishing data following the Linked Open Data (LOD) principles. The LinkedGeoData project (LGD) aims at providing rich, open, and integrated geographical data to the Semantic Web and use OpenStreetMap as its base. Associated to the LGD project, a geo-ontology has been created, and the dataset is linked to other open data sources like DBPedia, GeoNames and United Nations' Food and Agriculture Organisation (FAO) data.

The question is then how we can exploit this huge corpus of open geographic data to obtain valuable information using BI principles and tools? We conjecture that LGD can be used not only to direcly extract information, but also to enhance existing BI systems. How can we integrate this external source with organisational data warehouses? How can we query these data? In particular, this topic focuses in developing models and tools for integrating warehouse and RDF spatio-temporal data on the Web, and applying these tools on large amounts of data.

Main Advisor at Aalborg Universitet (AAU)
Co-advisor at Université Libre de Bruxelles (ULB)