Exposing IoT Streams on the Semantic Web
Keywords: Linked Data, Semantic Web, Data Streams, Internet of Things, Semantic Sensor Web, open data, smart cities
Supervision: Ruben Verborgh Ruben Taelman
Students: max 1
In the upcoming years the number of devices for the Internet of Things will grow exponentially. IoT will therefore become a major source of streaming data. In order to derive insights from this data it should be converted into a queryable format which allows easy semantic enrichment. Linked Open Data is the ideal candidate to fulfill this task. To prepare for this innovation a prototype environment is required which will reveal the challenges for the upcoming data explosion. The goal is to look into extending the low-cost Linked Data Fragments (http://linkeddatafragments.org/) technique for (static) Web querying so that it allows querying over one or more dynamic data streams and expose data summaries of larger periods of historic and real-time data for faster quering.
Building a scalable solution for exposing one or more sensor streams as Linked Data. Combining this data with other fragments on data on the Web to enable more complex queries. Evaluation of this solution compared to alternative approaches. We have applied this ourselves to parking lot data of cities in Flanders, but look forward discussing with you what our next use case would be!