Abstract
In disaster and emergency management the integration of different kinds of sensor networks gains in importance and consequently more and more data becomes available. The upcoming NoSQL database systems are flexible and scalable data stores, but up to now lacking in connectivity to traditional data processing systems (data warehouses, business intelligence suites, etc.). Due to that in this work a combined relational and NoSQL data processing approach is proposed to reduce data volume and work load of the relational part and enable the integral solution to process huge amounts of data. In contrast to fully NoSQL-based data warehouse systems, this approach does not face compatibility and integrability issues.
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Notes
- 1.
“Integrated Dynamic Decision Support System Component for Disaster Management Sys-tems”, ERA-NET EraSME program under the Austrian grant agreement No. 836684 (FFG).
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Acknowledgments
The research leading to these results has received funding from the ERA-NET EraSME program under the Austrian grant agreement No. 836684, project “INDYCO - Integrated Dynamic Decision Support System Component for Disaster Management Systems” and has been supported by the COMET program of the Austrian Research Promotion Agency (FFG).
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Stumptner, R., Lettner, C., Freudenthaler, B. (2015). Combining Relational and NoSQL Database Systems for Processing Sensor Data in Disaster Management. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_82
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