Governments and municipalities open up their data and publish spatial data on the Web, to be transparent to their citizens and to stimulate innovation. This spatial open data can be confusing for non-GIS experts, since data is published as either typical geo-formats or metadata is missing. Linked data could benefit in that regard. Linked data is a method to publish data on the Web in a way that it can be easily combined with other datasets on the Web. Linked data has benefits for spatial data regarding the combining of datasets to solve cross knowledge domain issues, the linking of metadata with the spatial data and the possibility to ask spatial queries.
The research focused on how to apply the linked data method for spatial open data in order to profit from the benefits of linked data. The research provided a methodology to create spatial linked open data. In the case study for the Municipality of Rotterdam, four spatial open datasets concerning the composition of areas and neighborhoods in Rotterdam Zuid were converted to spatial linked open data and visualized on a Web map to exemplify the possibilities and limitations for spatial linked open data. The case study showed that there are multiple users who benefit from spatial linked open data. The results also showed that modeling spatial data according to the OGC standard for spatial linked data, the GeoSPARQL ontology, provides the possibility to ask spatial queries over the data to do a simple analysis or inventory over multiple heterogeneous and distributed datasets, by dynamically and implicitly linking datasets together on their location. As of now, not all tools for creating linked data support spatial data yet, therefore it can be time consuming to convert the data to spatial linked data. The on-the-fly method, where the existing spatial data is converted on the fly to linked data would be ideal, in terms of data management, since the data is more up-to-date and not copied. Spatial linked open data has benefits in cross knowledge domain issues where multiple heterogeneous and distributed datasets are required, such as in emergency management and urban planning.