Stream-reasoning query languages such as CQELS and C-SPARQL enable query answering over RDF streams. Unfortunately, there currently is a lack of efficient RDF stream generators to feed RDF stream reasoners. State-of-the-art RDF stream generators are limited with regard to the velocity and volume of streaming data they can handle. To efficiently generate RDF streams in a scalable way, we extended the RMLStreamer to also generate RDF streams from dynamic heterogeneous data streams. This paper introduces a scalable solution that relies on a dynamic window approach to generate RDF streams with low latency and high throughput from multiple heterogeneous data streams. Our evaluation shows that our solution outperforms the state-of-the-art by achi...
RDF Stream Processing (RSP) is gaining momentum. The RDF stream data model is progressively adopted ...
Modern applications are required to process stream data which are semantically tagged. Sometimes sta...
To unlock the value of increasingly available data in high volumes, we need flexible ways to integra...
Stream-reasoning query languages such as CQELS and C-SPARQL enable query answering over RDF streams....
Abstract. In the last years, there has been an increase in the amount of real-time data generated. S...
In the last years, there has been an increase in the amount of real-time data generated. Sensors att...
The Web nowadays is highly dynamic with massive amounts of data being continuously generated from a ...
Sensors, mobile devices and social platforms generate an immense amount of stream data in various fo...
International audienceProcessing data as they arrive has recently gained momentum to mine continuous...
Querying and reasoning over RDF streams are two increasingly relevant areas in the broader scope of ...
Processing data streams is increasingly gaining momentum, given the need to process these flows of i...
International audienceReasoning over semantically annotated data is an emerging trend in stream proc...
Processing data streams is increasingly gaining momentum, given the need to process these flows of i...
Abstract. In recent years, several RDF Stream Processing (RSP) sys-tems have emerged, which allow qu...
Abstract. Stream processing has recently gained a prominent role in Computer Science research. From ...
RDF Stream Processing (RSP) is gaining momentum. The RDF stream data model is progressively adopted ...
Modern applications are required to process stream data which are semantically tagged. Sometimes sta...
To unlock the value of increasingly available data in high volumes, we need flexible ways to integra...
Stream-reasoning query languages such as CQELS and C-SPARQL enable query answering over RDF streams....
Abstract. In the last years, there has been an increase in the amount of real-time data generated. S...
In the last years, there has been an increase in the amount of real-time data generated. Sensors att...
The Web nowadays is highly dynamic with massive amounts of data being continuously generated from a ...
Sensors, mobile devices and social platforms generate an immense amount of stream data in various fo...
International audienceProcessing data as they arrive has recently gained momentum to mine continuous...
Querying and reasoning over RDF streams are two increasingly relevant areas in the broader scope of ...
Processing data streams is increasingly gaining momentum, given the need to process these flows of i...
International audienceReasoning over semantically annotated data is an emerging trend in stream proc...
Processing data streams is increasingly gaining momentum, given the need to process these flows of i...
Abstract. In recent years, several RDF Stream Processing (RSP) sys-tems have emerged, which allow qu...
Abstract. Stream processing has recently gained a prominent role in Computer Science research. From ...
RDF Stream Processing (RSP) is gaining momentum. The RDF stream data model is progressively adopted ...
Modern applications are required to process stream data which are semantically tagged. Sometimes sta...
To unlock the value of increasingly available data in high volumes, we need flexible ways to integra...