# US 9,053,437 B2 · Extracting enterprise information through analysis of provenance data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,053,437 B2 - Document ID: US9053437B2 - Status: Granted - Kind: B2 - Application number: 12/265,993 - Filed: 2008-11-06 - Published: 2010-05-06 - Granted: 2015-06-09 - Earliest claimed: 2008-11-06 - Assignees: International Business Machines Corporation - Applicants: Sharon C. Adler; Francisco Phelan Curbera; Yurdaer Nezihi Doganata; Chung-Sheng Li; Douglas C. Lovell; Axel Martens; Kevin Patrick McAuliffe; Huong Thu Morris; Nirmal K. Mukhi; Aleksander A. Slominski - Inventors: Sharon C. Adler; Francisco Phelan Curbera; Yurdaer Nezihi Doganata; Chung-Sheng Li; Douglas C. Lovell; Axel Martens; Kevin Patrick McAuliffe; Huong Thu Morris; Nirmal K. Mukhi; Aleksander A. Slominski - Web page: https://patentgrep.com/patent/US9053437B2 ## CPC - G06Q 10/00: Administration; Management - G06Q 10/06334: {using forecasting or predicting} - G06Q 10/0637: Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06Q 10/0633: Workflow analysis - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## 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. ## Claims ### Claim 1 A method of extracting information regarding an execution of an enterprise process, comprising the steps of: probing various hardware and software components of a computing platform executing an enterprise process to collect event data associated with actual end-to-end execution traces of the enterprise process; automatically transforming the collected event data into provenance data by mapping the collected event data to a provenance data model, wherein the provenance data model comprises a list of enterprise objects to he probed and defines correlation rules between data items of the collected event data, and wherein the provenance data provides an indication of a lineage of one or more data items of the collected event data; processing the provenance data to generate a provenance graph that provides a visual representation of the generated provenance data, wherein nodes of the provenance graph represent records associated with the collected data items and edges of the provenance graph represent relations between the records, wherein the records include data object records, task records, and process records that represent data objects, tasks and processes corresponding to the collected event data associated with the actual end-to-end execution traces of the enterprise process; and executing an automated graph analysis process to analyze at least a portion of the generated provenance data from the provenance graph to extract information about the execution of the enterprise process; wherein the probing, transforming, processing and executing steps are performed by a processor executing computer program code. ### Claim 2 (depends on 1) The method of claim 1, wherein the graph analysis further comprises determining one or more process patterns in the enterprise process. ### Claim 3 (depends on 2) The method of claim 2, wherein the one or more process patterns comprise one or more common process patterns. ### Claim 4 (depends on 2) The method of claim 2, wherein the one or more process patterns comprise one or more custom process patterns. ### Claim 5 (depends on 4) The method of claim 4, wherein a custom pattern is specified by a user through a user interface and a pattern search function is invoked to search for this particular pattern. ### Claim 6 (depends on 1) The method of claim 1, wherein the graph analysis further comprises performing a statistical analysis on at least a portion of the generated provenance data. ### Claim 7 (depends on 1) The method of claim 1, wherein the graph analysis further comprises predicting a subsequent evolution of the enterprise process. ### Claim 8 (depends on 1) The method of claim 1, wherein the graph analysis further comprises discovering an actual workflow from at least a portion of the generated provenance data. ### Claim 9 (depends on 1) The method of claim 1, wherein the graph analysis further comprises discovering a relation between two enterprise objects that are part of different nodes that are not connected by an edge in the provenance graph. ### Claim 10 (depends on 1) The method of claim 1, wherein the graph analysis further comprises discovering one or more human resources behind the execution of non-automated tasks and their roles in the enterprise process. ### Claim 11 (depends on 1) The method of claim 1, wherein the graph analysis further comprises discovering a list of one or more executed tasks, orders of the tasks, durations of the tasks and outputs of the tasks in the enterprise process. ### Claim 12 (depends on 1) The method of claim 1, wherein the graph analysis further comprises discovering one or more artifacts and their pedigree in the enterprise process. ### Claim 13 Apparatus for extracting information regarding an execution of an enterprise process, comprising: a memory; and a processor coupled to the memory and configured to: probe various hardware and software components of a computing platform executing an enterprise process to collect event data associated with actual end-to-end execution traces of the enterprise process; automatically transform the collected event data into provenance data by mapping the collected event data to a provenance data model, wherein the provenance data model comprises a list of enterprise objects to be probed and defines correlation rules between data items of the collected event data, and wherein the provenance data provides an indication of a lineage of one or more data items of the collected event data; process the provenance data to generate a provenance graph that provides a visual representation of the generated provenance data, wherein nodes of the provenance graph represent records associated with the collected data items and edges of the provenance graph represent relations between the records, wherein the records include data object records, task records, and process records that represent data objects, tasks and processes corresponding to the collected event data associated with the actual end-to-end execution traces of the enterprise process; and execute an automated graph analysis process to analyze at least a portion of the generated provenance data from the provenance graph to extract information about the execution of the enterprise process. ### Claim 14 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises determining one or more process patterns in the enterprise process. ### Claim 15 (depends on 14) The apparatus of claim 14, wherein the one or more process patterns comprise one or more common process patterns. ### Claim 16 (depends on 14) The apparatus of claim 14, wherein the one or more process patterns comprise one or more custom process patterns. ### Claim 17 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises performing a statistical analysis on at least a portion of the generated provenance data. ### Claim 18 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises discovering an actual workflow from at least a portion of the generated provenance data. ### Claim 19 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises discovering a relation between two enterprise objects that are part of different nodes that are not connected by an edge in the provenance graph. ### Claim 20 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises discovering one or more human resources behind the execution of non-automated tasks and their roles in the enterprise process. ### Claim 21 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises discovering a list of one or more executed tasks, orders of the tasks, durations of the tasks and outputs of the tasks in the enterprise process. ### Claim 22 (depends on 13) The apparatus of claim 13, wherein the graph analysis further comprises discovering one or more artifacts and their pedigree in the enterprise process. ### Claim 23 An article of manufacture for extracting information regarding an execution of an enterprise process, the article comprising a non-transitory computer readable storage medium including, program code which when executed by a computer performs the steps of: probing various hardware and software components of a computing platform executing an enterprise process to collect event data associated with actual end-to-end execution traces of the enterprise process; automatically transforming the collected event data into provenance data by mapping the collected event data to a provenance data model, wherein the provenance data model comprises a list of enterprise objects to be probed and defines correlation rules between data items of the collected event data, and wherein the provenance data provides an indication of a lineage of one or more data items of the collected event data; processing the provenance data to generate a provenance graph that provides a visual representation of the generated provenance data, wherein nodes of the provenance graph represent records associated with the collected data items and edges of the provenance graph represent relations between the records, wherein the records include data object records, task records, and process records that represent data objects, tasks and processes corresponding to the collected event data associated with the actual end-to-end execution traces of the enterprise process; and executing an automated graph analysis process to analyze at least a portion of the generated provenance data from the provenance graph to extract information about the execution of the enterprise process.