Abstract: Techniques are disclosed for extracting information through analysis of provenance data. For example, a computer-implemented method of extracting information regarding an execution of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed so as to extract information about the execution of the enterprise process based on the analysis.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Techniques are disclosed for extracting information through analysis of provenance data. For example, a computer-implemented method of extracting information regarding an execution of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed so as to extract information about the execution of the enterprise process based on the analysis.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Techniques are disclosed for validating compliance with enterprise operations based on provenance data. For example, a computer-implemented method for validating that an enterprise process is in compliance with a rule comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. A correlation is generated between one or more entities in the rule and one or more record types in the provenance data. One or more control points are generated in accordance with the generated correlation.

Abstract: A system, method of use, and a plurality of types of Radio Frequency Transponders (RF Tags). The RF Tags carry a directory or a tag type number which determines the layout of information in the tag memory. The tag type numbers are arranged hierarchically.

Abstract: An RF tag has an enable/disable circuit connected to a critical part of an electronic object/circuit, e.g. a computer mother board. The critical part of the circuit is any circuit component and/or connection that can enable and/or disable the electric circuit operation. Signals are sent to the tag to change data in the tag memory which causes the enable/disable tag circuit to control the critical part to enable and disable the electric circuit. A system checks the status of the tag, e.g. the electronic circuit was paid for, before enabling the electronic circuit.

Abstract: An RF tag has an enable/disable circuit connected to a critical part of an electronic object/circuit, e.g. a computer mother board. The critical part of the circuit is any circuit component and/or connection that can enable and/or disable the electric circuit operation. Signals are sent to the tag to change data in the tag memory which causes the enable/disable tag circuit to control the critical part to enable and disable the electric circuit. A system checks the status of the tag, e.g. the electronic circuit was paid for, before enabling the electronic circuit.

Abstract: A system and method is disclosed for selecting certain subgroups of radio frequency (RF) tags for querying, communicating, and/or identifying by a base station. The base station sends commands to a group tags within a RF field of the base station. The tags use control logic to determine whether or not they meet certain criteria sent out by the commands. This may cause the tags to change state which either prevents or allows a given tag to participate in an identification process. In this way, a given subgroup(s) of tags meeting certain criteria can be selected for querying, communicating, and/or identifying.