After the datasets have been transformed and filtered based on the current Technology Life Cycle stage, Dynamic Time Warping is then used to calculate the Euclidean distance between each pair of technology time series when compared using the time series dimensions specified by each patent indicator grouping in turn. This process is depicted visually in Fig. \ref{497938}, illustrating the successive layers of filtering that are applied for each technology pairing and each patent indicator grouping considered. The output from this process is an i x j x 1023 distance matrix, where i and j specify the current technology pairing being considered, and the value quoted is the measured distance between multi-dimensional time series based on the current patent indicator subset being used. In parallel to this the corresponding warping paths required to measure the distance between the N-dimensional curves in each condition are stored in two separate matrices for later use.