High performance linked data processing for virtual reality environments

Felix Leif Keppmann, Tobias Käfer, Steffen Stadtmüller, René Schubotz, Andreas Harth

In: Proceedings of the 2014 International Conference on Posters & Demonstrations Track-Volume 1272. International Semantic Web Conference (ISWC-2014) Seiten 193-196 CEUR-WS. org 2014.


The success of Linked Data (LD) [1] has enabled an environment in which application data can easily be enriched by the abundance of available information on the Web. Many recent approaches of the Linked Data community go beyond the mere exposure of static data and propose the combination of Linked Data and Representational State Transfer (REST) [3, 5, 7] to enable dynamic systems. However, in highly dynamic environments, where near real-time data integration and processing with high update frequencies are required, the perceived overhead of Linked Data query processing and stateless communication pattern often prevents the adoption of resource state exchange-oriented systems. Nevertheless, in our demonstration, we show a Virtual Reality (VR) information system that leverages the REST principles and the integration capabilities of LD. We specifically chose a VR setting, because it requires very low latency [2] in order to enable a natural interaction of the user with the system. Our system consists of loosely coupled components [4] as implicated by REST, and provides an interactive experience by seamlessly integrating existing LD sources from the Web as well as high dynamic body tracking data in a VR environment. We show how sensor data exposed as LD, can be processed with high update frequencies and be rendered in a VR environment. Constantly evaluated queries are employed to realise both gesture recognition and collision detection of objects in the VR. Derived actions like data retrieval from the Web and the subsequent integration of the retrieved data with the sensor data are performed on-the-fly.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence