Five challenges for the Semantic Sensor Web
Semantic Web
Semantic Perception: Converting Sensory Observations to Abstractions
IEEE Internet Computing
Automatic reasoner selection using machine learning
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Visualization of the European environmental data
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Eco-informatics modelling via semantic inference
Information Systems
Ontology paper: The SSN ontology of the W3C semantic sensor network incubator group
Web Semantics: Science, Services and Agents on the World Wide Web
Semantics for the Internet of Things: Early Progress and Back to the Future
International Journal on Semantic Web & Information Systems
| Hi-index | 0.00 |
To date, Semantic Sensor Web research and development has focused on establishing common techniques and practices that homogenize how to discover sensors, collect their data, integrate them, extract information from them, etc. However, as these issues are overcome and huge data bases of sensor data begin to emerge, the focus should change to improve the data management and the information overload, discarding the non relevant information from the relevant one, and on the other hand, allow easy and intuitive navigation through it. The objective is to move up the wisdom hierarchy and empower users so they can start discovering new relevant knowledge and making decissions based on that. In this position paper, we start drafting an architecture, aligned with current practices and standards, which facilitates the whole process: from data collecting and storing, to wisdom generation and navigation. Efforts will focus on empower users to spot trends or events in data. Moreover, the system will learn from the discoveries made by users so it can later automatise the detection of similar situations and integrate users wisdom.