Ontology-Driven Compression of Temporal Series: A Case Study in SCADA Technologies

SCADA (supervisory control and data acquisition) technologies are used to provide a framework for transferring data from sensors to micro-controllers, like PLC (programmable logic controllers) to supervising computers. Given a set of active sensors in a given field, connected to a correspondingly complex net of PLCs, the generated stream of measures can be very large even for a short measurement interval. Data compression techniques that usually apply to massive data streams exhibit unacceptable qualities in the application framework we consider, mainly for the reason that the tradeoff between compression factor and efficiency of data retrieval is very restrictive. In this paper we provide a technique of data compression that is simultaneously capable of a significant compression factor and of an acceptable performance in data querying.