Querying Dynamic Datasources with Continuously Mapped Sensor Data
In Proceedings of the 15th International Semantic Web Conference: Posters and Demos (2016)
The world contains a large amount of sensors that produce new data at a high frequency. It is currently very hard to find public services that expose these measurements as dynamic Linked Data. We investigate how sensor data can be published continuously on the Web at a low cost. This paper describes how the publication of various sensor data sources can be done by continuously mapping raw sensor data to RDF and inserting it into a live, low-cost server. This makes it possible for clients to continuously evaluate dynamic queries using public sensor data. For our demonstration, we will illustrate how this pipeline works for the publication of temperature and humidity data originating from a microcontroller, and how it can be queried.