Extending the data stream processing strategy to scenario analysis

Abstract

The real-time data processing is continuously demanded by their implications in the real-time decision-making process. The data stream processing strategy implements an automatization of the measurement process based on a measurement and evaluation (M&E) framework for supporting real-time decision making. The decision making is based on the indicators, which have a set of decision criteria established by the experts in the domain in the initial M&E project definition. However, the decision criteria are not isolated from the context in which the decision should be made. This work introduces an extension for the data stream processing strategy, incorporating the scenarios as an interpretation related to the possible states of a context. The transition between scenarios is incorporated through the transition model, obtaining feedback from the processed data for adjusting the decision criteria and their interpretation in terms of the current context. A new complementary schema to the project definition is incorporated for supporting the extensions. In this way, the data stream processing strategy now is able to support the scenario definitions, transition analysis jointly with the possibility of fitting each indicator’s decision criteria to each particular scenario. Finally, a scenario analysis based on the monitoring of outpatients is outlined.