The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
Linear road: a stream data management benchmark
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
IEEE Internet Computing
SP^2Bench: A SPARQL Performance Benchmark
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
ISWC '09 Proceedings of the 8th International Semantic Web Conference
An execution environment for C-SPARQL queries
Proceedings of the 13th International Conference on Extending Database Technology
LUBM: A benchmark for OWL knowledge base systems
Web Semantics: Science, Services and Agents on the World Wide Web
A semantics-based middleware for utilizing heterogeneous sensor networks
DCOSS'07 Proceedings of the 3rd IEEE international conference on Distributed computing in sensor systems
Streaming SPARQL extending SPARQL to process data streams
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Data Stream Management
Enabling ontology-based access to streaming data sources
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
EP-SPARQL: a unified language for event processing and stream reasoning
Proceedings of the 20th international conference on World wide web
Apples and oranges: a comparison of RDF benchmarks and real RDF datasets
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A native and adaptive approach for unified processing of linked streams and linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
StreamRule: a nonmonotonic stream reasoning system for the semantic web
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
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Linked Stream Data, i.e., the RDF data model extended for representing stream data generated from sensors social network applications, is gaining popularity. This has motivated considerable work on developing corresponding data models associated with processing engines. However, current implemented engines have not been thoroughly evaluated to assess their capabilities. For reasonable systematic evaluations, in this work we propose a novel, customizable evaluation framework and a corresponding methodology for realistic data generation, system testing, and result analysis. Based on this evaluation environment, extensive experiments have been conducted in order to compare the state-of-the-art LSD engines wrt. qualitative and quantitative properties, taking into account the underlying principles of stream processing. Consequently, we provide a detailed analysis of the experimental outcomes that reveal useful findings for improving current and future engines.