IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Water resources and hydroinformatics : Towards a semantic and holistic architecture for water sensor data integration
Towards a semantic and holistic architecture for water sensor data integration
To date, Semantic Sensor Web research and development has focused on establishing common techniques and practices
that homogenize how to discover, collect and integrate information from sensors. However, as solutions for this part of the
problem are starting to become successful, huge databases of sensor data begin to accumulate. Therefore, the focus
should now change to improve data management and reduce information overload, helping users discard irrelevant
information and make its exploration easy and intuitive. This paper depicts the development of an architecture that focuses
on water sensors data fusion, plus additional data from heterogeneous sources that contextualizes sensors output. By
mixing and semantically annotating data, the architecture better assist users to autonomously understand data and then,
generate new management strategies. The proposal is based on applying Semantic Streams Technology (SST) to collect
and integrate continuous sensor data from multiple databases in form of RDF streams. The RDF streams are generated
by transforming SQL-structured data into semantic data by using a knowledge base, thus enriching the information
contained in the database. Hence, abstracting sensor data stored in a database through the R2RML technique generates
the RDF streams. Moreover, SST processes sensor data using real-time semantic stream reasoning over the generated
RDF streams from noisy sensor data to support the decision process even in large and complex scenarios. The proposed
architecture has been analyzed by combining it with the infrastructure deployed over the water supply and distribution
chain implemented in the context of the FP7-WatERP project, where sensor data is continuously stored in OGC-SOS
server database. This data is transformed into RDF streams using also the Water Management Ontology developed in
WatERP. The semantic stream reasoning is performed by C-SPARQL permitting the architecture to register and execute
queries, which provide water managers knowledge to improve water resource management. Consequently, the proposed
architecture enhances current state of the art in: (i) avoiding information replication by wrapping data streams with
semantic stream technologies; and (ii) proving real-time reasoning, decision support and rapid actuation against resource
mismanagements or other critical situations.
File Size : 975,836 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Water resources and hydroinformatics
Date Published : 20/08/2015
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