SemaPlorer—Interactive semantic exploration of data and media based on a federated cloud infrastructure
✍ Scribed by Simon Schenk; Carsten Saathoff; Steffen Staab; Ansgar Scherp
- Publisher
- Elsevier Science
- Year
- 2009
- Tongue
- English
- Weight
- 836 KB
- Volume
- 7
- Category
- Article
- ISSN
- 1570-8268
No coin nor oath required. For personal study only.
✦ Synopsis
browsing Amazon EC2 Amazon S3 Billion Triple Challenge a b s t r a c t
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 real-time. Its purpose is to acquaint oneself about a city, touristic area, or other area a user is interested in. By visualizing the data using a map, media, and different context views, SemaPlorer advances beyond simple storage and retrieval of large numbers of triples, as the interaction with the large data set is driven by 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. SemaPlorer intriguingly connects with a large Flickr data set converted to RDF. The storage infrastructure bases on Amazon's Elastic Computing Cloud (EC2) and Simple Storage Service. We apply NetworkedGraphs as a conceptual layer on top of EC2, realizing 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 of almost arbitrary additional data sources that might be added in the future. We conducted a formative evaluation of the SemaPlorer application with 20 test subjects. The results of this evaluation are analyzed and their implication to future work discussed.