Abstract: Solving for output variable(s) of a model that includes multiple analytically related model variables. The identity of the output model variables and the analytical relationships between the model variables are separately designated. Regardless of the identity of the output variable(s), a solver framework interprets the analytical relationships and solves for the designated output variable(s). The output model variable(s) may be designated separately than the analytical relationships themselves. By simply changing the designation of the output model variable(s), the analytical relationships are reevaluated, and the output variable(s) are solved for. The solver framework itself stays the same regardless of the identity of the output model variable(s).

Abstract: An application entity may be created and defined by a user at an application. Related service entities managed by different service applications may be matched and consolidated. The application entity may be associated with one or more related service entities. Metadata corresponding to the associated service entities may be provided to the application. Such metadata may enable the associated service entities to be managed from within the application.

Abstract: A complex solver that is able to solve a diverse variety of model analytics. Upon identifying the various input variable(s) and output variable(s) of the model variables, if a straight forward solve is not to be performed, it is determined whether the model analytics is to be inverted such that a forward solve can be performed. For instance, it might not be known generally, or at least to the solver, how to invert a particular equation of other model analytics. If the model analytics is to be inverted, the model analytics is inverted, and the forward solve is performed. On the other hand, if the inversion of the model analytics is not to be performed, then a numerical analysis solve is performed.

Abstract: A taxonomy reference model for use in an analytical modeling component. The analytical modeling component defines analytical relationships between the model parameters using analytical relations. The analytical modeling component uses the analytical relations to identify which of the model parameters are known and which are unknown, and solves for the identified unknown model parameter(s). An analytics taxonomy categorizes the analytics relations into analytics categories. This analytics taxonomy may be domain-specific. Also, if the analytics drive visuals, the visuals could be taxonomized as well. If the analytics is driven by data, the data could also be taxonomized.

Abstract: Searching and exploration using a data-driven analytics model. The analytics model includes an analytical modeling component that defines analytical relationships between model variables using a number of analytical relations. In response to a search request, the output variable(s) of the solve operation are identified. The output variable(s) may have even been identified based on the search request. The analytical relations of the model may then be used to solve for the identified output variable(s). The resulting value(s) for the now solved-for output variable(s) may then be used to formulate the response to the search request. The nature of the response may vary depending on the scope of the application that embodied the search request capability. The results of the search request may be used for further exploration of the model by, for example, submitting follow-up search requests, resulting in follow-up solve operations.

Abstract: The composition of a data-driven analytics model that includes at least an analytical modeling component that defines analytical relationships between the model parameters using multiple analytical relations. The analytical modeling component uses the analytical relations to identify which of the model parameters are known and which are unknown, and solves for the identified unknown model parameter(s). The analytics modeling component also includes an analytics taxonomy in which the analytical relations are categorized into related analytics categories. Navigation through the analytics taxonomy assists in the composition of an analytics model. The analytics taxonomy may, but need not, be domain specific.

Abstract: Establishing relationships between one or more entities of a first application and one or more entities of a second application using metadata. At least one entity of the second application is identified for establishing a relationship with at least one entity of the first application. Metadata from the second application is received at the first application. The metadata includes information associated with the identified entity of the second application. An expression is generated, based on the metadata, specifying a relationship between the entity of the first application with the identified entity of the second application.

Abstract: A solver framework for use with an analytical model. The analytical model includes multiple model parameters and includes definitions for analytical relationships between the model parameters. The solver framework coordinates the processing of multiple specialized solvers. In particular, the solver framework identifies which model parameters are input model variables and which are output model variables. The solver framework then analyzes dependencies to determine a solve order to solve for the output model variables. The solver framework then charged the specialized solvers with performing portions of the solve operation such that the specialized solvers solve for the output model variables in an order which considers the dependencies. In one embodiment, additional or replacement solvers may register with the solver framework to thereby make the specialized solver available for solving for output model variables in the future.

Abstract: Visual interaction with an analytics-driven model view composition application. The application includes a data-model binding component that binds input data to model parameters, an analytics solver component that solves for remaining unknown model parameters, and a view composition component that generates a view composition using the model parameters. In one visual interaction, various solutions of the model are provided in alternative views of various view compositions in a single integrated composition. In another interaction, regardless of whether there are multiple view compositions illustrated in a single integrated view, there might be visual prompts in the view composition that suggest an adjustment to make that might move the value of a particular model parameter in a desired direction.

Abstract: A dynamic verification system is described that enables application developers to safely include significant custom business logic in their applications. The dynamic verification system receives application behavior criteria that specify behavior of an application of interest to an application host. The system executes an application and instruments an application execution environment to detect application behavior that meets the application behavior criteria. The system determines when the application has performed an action that satisfies the application behavior criteria and provides a notification about the application behavior that occurred that a system administrator can use to take action against the application.

Abstract: The composition of multiple analytical visual composition models into a single whole. A model importation mechanism allows a model author or other user import all or portions of other models. By so doing, the author might cause the following to be supplemented or changed in an existing analytics-driven model: 1) additional model input data as well to generate a supplemented set of model input data; 2) additional bindings between the supplemental set of model input data to the model parameters; 3) additional model parameters to generate a supplemental set of model parameters; and 4) additional analytical relationships between the supplemental set of model parameters. Accordingly, the author may borrow from models by other authors, allowing for effective collaboration in order to construct increasingly complex models.

Abstract: Technologies are described herein for generating a platform-independent data application. In one method, a definition of a data schema is received for defining data types. A definition of a user interface is also received for access data stored in the data types. Further, a definition of business logic is received for enforcing validation rules and actions associated with the data types. The definitions of the data schema, the user interface, and the business logic are each received in a platform-independent format and used to generate the platform-independent data application.

Abstract: Visual items may each be constructed and placed in position using logic defined by a view component corresponding to each visual item, where that logic may depend on one or more values populated into parameter(s) of the view component. Some of those parameter values may correspond to known model parameter values. Others, however, may have been solved for using a model that defines analytical relationships between the model parameters. In one embodiment, which of the model parameters are known, and which are unknown, may not be predetermined. Accordingly, a solver might be prepared for multiple solve operation paths even using a single model. The view composition process may be entirely data-driven, and may include a mechanism for canonicalizing input data, and binding canonicalized input data to the model parameters. The view composition framework may operate the same regardless of the domain.

Abstract: Visual map items may each be constructed and placed in position using logic defined by a map view component corresponding to each visual item, where that logic may depend on one or more values populated into parameter(s) of the map view component. Some of those parameter values may correspond to known map model parameter values. Others, however, may have been solved for using a model that defines analytical relationships between the map model parameters. In one embodiment, which of the map model parameters are input variable, and which are output model variables, may not be predetermined. Accordingly, a solver might be prepared for multiple solve operation paths even using a single model. The map view composition process may be entirely data-driven, and may include a mechanism for canonicalizing input data, and binding canonicalized input data to the model parameters.

Abstract: System and method for identifying a pattern. A method of the invention compiles a pattern description where the pattern description defines a series of a first event and a second event relating to the first event. The first event is received and includes a type parameter data, a time parameter data, and a substance parameter data. A system of the invention includes a script component for associating or attaching a first script to the first event. The first script defines the type, time, and substance parameters of the second event as a function of the parameters of the first event according to the pattern description. A pattern recognition engine executes the attached first script and the executed script identifies the second event and thereby identifies the pattern.

Abstract: The present invention extends to methods, systems, and computer program products for processing data-centric business models. An execution engine accesses a commingled data-centric application model that includes a data model for a data store and a business logic model for interacting with data entities contained in the data store. The execution engine receives an event related to the data store and identifies an involved data entity corresponding to the received event. The execution engine identifies a business logic rule indicated as affecting the involved data entity. The execution engine establishes a context for evaluating the identified business logic rule. The execution engine evaluates the conditions of the business logic rule in accordance with the established context. The execution engine executes any appropriate actions indicated in the business logic rule as a result of the conditions of the business logic rule being satisfied.

Abstract: Technologies are presented herein for self-describing re-usable software components. Metadata is generated and published with a re-usable software component that identifies the capabilities of the software component, identifies other software components that the re-usable software component may be integrated with, and identifies mechanisms for integrating the re-usable software component with other software components. The metadata can then be used to discover re-usable software components and to integrate the re-usable software components with other software components.

Abstract: Identifying a transaction from a real time event stream having latency. A method of the invention receives events from the real time event stream where events define a plurality of transactions to be identified. Each of the transactions includes a first event and a second event; the first event has a first latency relative to the real time event stream and the second event has a second latency relative to the real time event stream. The first event is identified from the received real time event stream, and a time is record when the first event is received. The method determines a time period during which the second event occurs as a function of the first latency, the recorded time of the first event, and the second latency. The transaction having the first and second events is identified based on the determined time period of the second event.

Abstract: The present invention extends to methods, systems, and computer program products of user-interface architecture for manipulating business models. Embodiments of the invention facilitate efficient generation and extension of business related software applications, including commingled data-centric applications that represent both data elements and business logic in metadata. Modules of the user-interface architecture permit users to enter commands through common metaphors and wizards that abstract underlying (and more complex) modeling commands and data formats from users. The user-interface architecture can automatically search for existing models to provide and extend business related functionality.

Abstract: The present invention extends to methods, systems, and computer program products for processing data-centric business models. An execution engine accesses a commingled data-centric application model that includes a data model for a data store and a business logic model for interacting with data entities contained in the data store. The execution engine receives an event related to the data store and identifies an involved data entity corresponding to the received event. The execution engine identifies a business logic rule indicated as affecting the involved data entity. The execution engine establishes a context for evaluating the identified business logic rule. The execution engine evaluates the conditions of the business logic rule in accordance with the established context. The execution engine executes any appropriate actions indicated in the business logic rule as a result of the conditions of the business logic rule being satisfied.