Abstract: A hybrid approach for capturing meta data about Business Processing Monitoring (BPM) artifacts is based on a combination of a relational meta data model and a semantic net. Meta data about metrics and situations and their dimensional context are first captured. Then, relational meta data are used to describe a generic data schema for metrics, situations and their dimensional context. The meta data from semantic nets are used to extend the meta data definitions. Data from a data warehouse are searched and managed with the schema described and managed with the relational and semantic net meta data.

Abstract: An architecture, system, and method are provided for a commitment loop solution for on demand business activity management. A Business Performance Management (BPM) loop is defined as a set of nodes each relating to different tasks for processing performance management trigger data generated by a business entity in real time, where the beginning or sensing element of the loop is triggered by a token (representing a business event from a business process) and the ending or executing element provides a business action to be implemented by the business entity. The token is passed from node to node sequentially in a particular order around the loop. Processing of the data represented by the token is governed by policies, which can be changed dynamically and follow a life cycle. On demand business activity management of larger aggregates of business entities (i.e.