High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Data Management in the Worldwide Sensor Web
IEEE Pervasive Computing
Magpie: Experiences in supporting Semantic Web browsing
Web Semantics: Science, Services and Agents on the World Wide Web
A comparison of two modelling paradigms in the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Taverna Workflows: Syntax and Semantics
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
The two cultures: Mashing up Web 2.0 and the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Collective knowledge systems: Where the Social Web meets the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Tsoft: graphical and interactive software for the analysis of time series and Earth tides
Computers & Geosciences
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
Web Semantics: Science, Services and Agents on the World Wide Web
Invited Paper: Semantic Web and Social Web heading towards Living Documents in the Life Sciences
Web Semantics: Science, Services and Agents on the World Wide Web
How is the Semantic Web evolving? A dynamic social network perspective
Computers in Human Behavior
Ontology Mapping and Reasoning in Semantic Time Series Processing
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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In this paper, we present a new approach of time series enrichment with semantics, and the usage of this technology for building various kinds of communities interested in time series data. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing and creating target communities. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.