Properties Relevant for Inferring Provenance
Rajput, Abdul Ghani (2011)
Provenance is an important requirement for real-time applications, especially
when sensors act as a source of streams for large-scale, automated process control and decision control applications. Provenance provides important information that is essential to identify the origin of data, to reproduce the results in
real-time applications as well as to interpret and validate the associated scientific results. The term provenance documents the origin of data by explicating
the relationship among the input samples, the transformation and the output
samples. In this thesis, we present a formal stream processing model based on
discrete time signal processing. We use the formal stream processing model to
investigate different data transformations and the provenance relevant characteristics of these transformations. The validity of the formal stream processing
model and transformation properties is demonstrated by providing the four case
studies.
MSc_A_Rajput.pdf