Abstract: There is provided a method that includes (a) receiving data from a data source, (b) attributing the data source in accordance with rules, thus yielding an attribute, (c) analyzing the data to identify a confounding characteristic in the data, (d) calculating a qualitative measure of the attribute, thus yielding a weighted attribute, (e) calculating a qualitative measure of the confounding characteristic, thus yielding a weighted confounding characteristic, (f) analyzing the weighted attribute and the weighted confounding characteristic, to produce a disposition, (g) filtering the data in accordance with the disposition, thus yielding extracted data, and (h) transmitting the extracted data to a downstream process. There is also provided a system that executes the method, and a storage device that contains instructions for controlling a processor to perform the method.

Abstract: There is provided a method that includes (a) receiving data from a data source, (b) attributing the data source in accordance with rules, thus yielding an attribute, (c) analyzing the data to identify a confounding characteristic in the data, (d) calculating a qualitative measure of the attribute, thus yielding a weighted attribute, (e) calculating a qualitative measure of the confounding characteristic, thus yielding a weighted confounding characteristic, (f) analyzing the weighted attribute and the weighted confounding characteristic, to produce a disposition, (g) filtering the data in accordance with the disposition, thus yielding extracted data, and (h) transmitting the extracted data to a downstream process. There is also provided a system that executes the method, and a storage device that contains instructions for controlling a processor to perform the method.

Abstract: A system and method for deriving a material change attribute over time to predict a future change in at least one predictor, the method comprising: collecting precursor data from at least one data source; processing the precursor data by assessing at least one characteristic of the precursor data; generating at least one material change signal from the processed precursor data; evaluating the material change signal to determine the signal's value in predicting future changes in the predictor and, optionally, reverting to the collection and processing steps above to process additional precursor data; and generating at least one the material change attribute from the evaluated material change signal.