Abstract: A mechanism is provided to implement a contract analytic binding and provenance system. The mechanism loads contract rules for an agreement between a plurality of contract parties and creates an analytic entry per rule to form a set of analytic entries, Each analytic entry is associated with an executable analytic function. The mechanism assigns each analytic entry a directed acyclic graph vertex. The mechanism confirms alignment between the contract rules and the set of analytic entries and stores the set of analytic entries in peer ledgers associated with the plurality of contract parties. The mechanism activates the set of analytic entries responsive to confirming provenance of the peer ledgers associated with the plurality of contract parties.

Abstract: A mechanism is provided to review and verify provenance of analytic execution by a contract analytic binding and provenance system. The mechanism is activated to execute a set of analytics for a contract and verifies outcomes of the analytics before writing them to a blockchain network. The mechanism evaluates the provenance data records stored on peer ledgers and establishes transparency of the outcomes by validating consensus between characteristics of the provenance data.

Abstract: A mechanism is provided to implement a contract analytic binding and provenance system. The mechanism loads contract rules for an agreement between a plurality of contract parties and creates an analytic entry per rule to form a set of analytic entries, Each analytic entry is associated with an executable analytic function. The mechanism assigns each analytic entry a directed acyclic graph vertex. The mechanism confirms alignment between the contract rules and the set of analytic entries and stores the set of analytic entries in peer ledgers associated with the plurality of contract parties. The mechanism activates the set of analytic entries responsive to confirming provenance of the peer ledgers associated with the plurality of contract parties.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for identifying symptoms based on digital media. The method includes one or more processors receiving digital media and information associated with a first animal from a user. The method further includes one or more processors identifying data records, stored in a knowledge database, that are respectively associated with an animal that is similar to the first animal. The method further includes one or more processors determining symptom information corresponding to the first animal based on a comparison of the received digital media and information associated with the first animal and the identified data records. The method further includes presenting the determined symptom information to a user.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for identifying symptoms based on digital media. The method includes one or more processors receiving digital media and information associated with a first animal from a user. The method further includes one or more processors identifying data records, stored in a knowledge database, that are respectively associated with an animal that is similar to the first animal. The method further includes one or more processors determining symptom information corresponding to the first animal based on a comparison of the received digital media and information associated with the first animal and the identified data records. The method further includes presenting the determined symptom information to a user.

Abstract: A method, computer system, and computer program product for generating an outcome-based healthcare contract is provided. The embodiment may include defining an outcome-based contract template between a company and a payer, whereby the outcome-based contract template comprises at least one category of a plurality of patient data to be tracked. The embodiment may include generating a contract for a patient based on the outcome-based contract template, whereby at least one specific value associated to the patient is assigned to each at least one category, and whereby the contract comprises a target outcome for the patient. The embodiment may include monitoring the plurality of patient data associated with the patient. The embodiment may include determining the target outcome is achieved based on the plurality of patient data. The embodiment may include transmitting a plurality of outcome data between the company and the payer based on the determined target outcome being achieved.

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: A computer implemented method, apparatus, and computer usable program product for processing application code. In one embodiment, a call is received to invoke a set of methods of annotated application code. The annotated application code includes a set of annotations specifying a selection of the set of methods. A selected method from the set of methods is invoked in response to determining that the call is valid according to the set of annotations. Thereafter, a subsequent set of valid methods for execution is identified based upon an annotation associated with the selected method.

Abstract: A method for modeling a process includes receiving a plurality of graphs representing processes wherein for each graph. A sequence of process steps of the processes are represented as nodes and edges connecting pairs of nodes represent transitions between process steps. A numeric value representative of graph appearance for each of the plurality of received graphs is calculated. Each of the plurality of received graphs is stored within a tree-like data structure according to its corresponding numeric value. Each of the above steps is performed using a computer system.

Abstract: A method for modeling a process includes collecting data pertaining to executed process steps from one or more activity log files. The collected data is parsed to determine a set of process steps that have been performed. An incidence value representing how many times each performed process step follows each of the other performed process steps is determined. A graph representing a model of the executed process by representing each process step that has been performed as a node of the graph and each transition between process steps within each process thread as an edge on the graph is generated. The edges connecting the pairs of nodes are assigned numbers that depend upon the incidence value corresponding to how many times the process step represented by a first node of the pair is followed by the process step represented by a second node of the pair.

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 for role-based service operation status reporting to clients are provided. In one aspect, a method for reporting a status of a service operation to a client is provided. The method includes the following steps. A sequence of business process steps involved in performing the service operation is identified. One or more abstractions of the business process steps are made, each abstraction containing a sequence of a fewer number of steps than the business process, wherein the number of steps in each of the abstractions correlates with a level of detail about the service operation. The status of the service operation is reported to the client based on a given one of the abstractions having the level of detail best suited to a role of the client.

Abstract: A method for predictive analytics for a process includes receiving at least one trace of the process, building a probabilistic graph modeling the at least one trace, determining content at each node of the probabilistic graph, wherein a node represents an activity of the process and at least one node is a decision node, modeling each decision node as a respective decision tree, and predicting, for an execution of the process, a path in the probabilistic graph from any decision node to a prediction target node of a plurality of prediction target nodes given the content.

Abstract: A method of graph simplification includes receiving a connected process graph having a plurality of edges and nodes, parameterizing the connected process graph to determine a mapping where none of the edges overlap, defining respective energies for a plurality of triangles formed by the edges and the nodes in the connected process graph, identifying node clusters in the connected process graph, and collapsing, for each node cluster, ones of the edges and nodes in the connected process graph that are not critical edges or critical nodes according to the energies.

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.