SemaPlorer is an easy to use application that allows end users to interactively explore and visualize a very large, mixed-quality and semantically heterogeneous distributed semantic data set in realtime. Its purpose is to acquaint oneself about a city, touristic area, or other area of interest. By visualizing the data using a map, media, and different context views, we clearly go beyond simple storage and retrieval of large numbers of triples. The interaction with the large data set is driven

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... the user. SemaPlorer leverages different semantic data sources such as DBpedia, GeoNames, WordNet, and personal FOAF files. These make a significant portion of the data provided for the billion triple challenge. It intriguingly connects with a large Flickr data set converted to RDF. SemaPlorer's storage infrastructure bases on Amazon's Elastic Computing Cloud (EC2) and Simple Storage Service. We apply NetworkedGraphs as additional layer on top of EC2, performing as a large, federated data infrastructure for semantically heterogeneous data sources from within and outside of the cloud. Therefore, the application is scalable with respect to the amount of distributed components working together as well as the number of triples managed overall. Hence, SemaPlorer is flexible enough to leverage for exploration almost arbitrary additional data sources that might be added in the future.