AUTHORS: Kyriakos Kritikos, Dimitris Plexousakis

ABSTRACT

The Web has been evolving to a sink of disparate information sources which are totally isolated from each other. The technology of Linked Data (LD) promises to connect such information sources in order to enable their better exploitation by humans or automated programs. While various LD management systems have been proposed, only few of them are able to handle geospatial data which are becoming quite popular nowadays and lead to the creation of large geospatial footprints. However, none of the few systems that support Linked Open Geospatial Data is able to scale well to handle the increasing load from user queries. In addition, the publishing of geospatial LD also becomes quite advantageous due to complexity reasons. To this end, this article proposes a novel, cloud-based geospatial LD management system which can scale out or scale in according to the incoming load in order to serve the respective user requests with the appropriate service level. On top of this system lies a LD-as-a-service offering which abstracts away the user from any LD publishing complexities and provides all the appropriate functionality for enabling a full LD management. We also study and propose architectural solutions for the distributed update problem. The proposed system is evaluated under heavy load scenarios and the results show that the respective improvement in performance incurred is quite satisfactory and that the scaling actions are performed at the appropriate time points

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