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 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: A method (and system) for editing rules contained in a first document, where the rules define a transformation of data on a second document and where the first document and second document have elements constructed in a tree structure having nodes, each rule having a template structure including at least one match condition, the match condition being an expression in the template that describes a subset of tree nodes, includes selecting at least one rule in the first document and checking a match condition of the user-selected rule with the tree nodes from the second document to determine which structures in the second document match the selected rule.

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 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 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 method, information processing system, and computer readable medium for generating a plurality of candidate database schemas including relational and mark-up language elements. An information model comprising a plurality of entities and at least one relationship defined there between is received. The information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic. The information model that has been annotated is analyzed. A score is associated with each entity based at least in part on attributes associated with each entity. Each entity is classified as one of a relational element and a mark-up language element. The information model that has been annotated is partitioned into a plurality of relational element mappings and a plurality of mark-up language element mappings. A plurality of database schemas associated with the information model that has been annotated is generated.

Abstract: A method, information processing system, and computer readable medium for generating a plurality of candidate database schemas including relational and mark-up language elements. An information model comprising a plurality of entities and at least one relationship defined there between is received. The information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic. The information model that has been annotated is analyzed. A score is associated with each entity based at least in part on attributes associated with each entity. Each entity is classified as one of a relational element and a mark-up language element. The information model that has been annotated is partitioned into a plurality of relational element mappings and a plurality of mark-up language element mappings. A plurality of database schemas associated with the information model that has been annotated is generated.

Abstract: A method (and structure) for enacting changes to a document containing a template-based program that transforms tree-structured data from a first tree-structured data into a second tree-structured data, including providing an interface to permit selection of a document containing the template-based program, constructing a model of the template-based program in the selected document by parsing elements of the template-based program into a corresponding logical construct having a match condition and at least one generator, where the match condition determines whether an element in the first tree-structure data is to be processed by one or more of the at least one generator, and displaying a representation of the model to the user.

Abstract: A method (and system) for editing rules contained in a first document, where the rules define a transformation of data on a second document and where the first document and second document have elements constructed in a tree structure having nodes, each rule having a template structure including at least one match condition, the match condition being an expression in the template that describes a subset of tree nodes, includes selecting at least one rule in the first document and checking a match condition of the user-selected rule with the tree nodes from the second document to determine which structures in the second document match the selected rule.

Abstract: A method (and structure) for enacting changes to a document containing a template-based program that transforms tree-structured data from a first tree-structured data into a second tree-structured data, including providing an interface to permit selection of a document containing the template-based program, constructing a model of the template-based program in the selected document by parsing elements of the template-based program into a corresponding logical construct having a match condition and at least one generator, where the match condition determines whether an element in the first tree-structure data is to be processed by one or more of the at least one generator, and displaying a representation of the model to the user.