Abstract: Some embodiments are directed to systems for authoring predictive models. An embodiment includes a computer system implementing a development environment for generating predictive models. The predictive model authoring tool is configured to perform a modeling operation based on one or more user inputs provided to interface controls of the predictive model authoring tool, determine a modeling context for the modeling operation, log the one or more user inputs, generate a predictive model based on one or more model parameters defined during the modeling operation, link the predictive model to an asset, such that one or more sets of data received from the asset are provided to the predictive model during execution of the predictive model, cause the predictive model to be executed such that the predictive model receives data from the asset, and provide the modeling context, the one or more user inputs, and the one or more model parameters.

Abstract: According to some embodiments, system and methods for representing nodes and data flows in a network are provided, comprising providing a hierarchical taxonomy for one or more concepts; providing one or more hierarchical taxonomies for one or more boundary types, wherein one or more values from each boundary type are combined to form a definition of a boundary; and associating the at least one concept and at least one boundary with a transmission of data between a first node and a second node, wherein the transmitted data is a data flow. Numerous other aspects are provided.

Abstract: According to some embodiments, system and methods for representing nodes and data flows in a network are provided, comprising providing a hierarchical taxonomy for one or more concepts; providing one or more hierarchical taxonomies for one or more boundary types, wherein one or more values from each boundary type are combined to form a definition of a boundary; and associating the at least one concept and at least one boundary with a transmission of data between a first node and a second node, wherein the transmitted data is a data flow. Numerous other aspects are provided.

Abstract: Some embodiments are directed to systems for authoring predictive models. An embodiment includes a computer system implementing a development environment for generating predictive models. The predictive model authoring tool is configured to perform a modeling operation based on one or more user inputs provided to interface controls of the predictive model authoring tool, determine a modeling context for the modeling operation, log the one or more user inputs, generate a predictive model based on one or more model parameters defined during the modeling operation, link the predictive model to an asset, such that one or more sets of data received from the asset are provided to the predictive model during execution of the predictive model, cause the predictive model to be executed such that the predictive model receives data from the asset, and provide the modeling context, the one or more user inputs, and the one or more model parameters.

Abstract: Disclosed are systems, methods, and machine-readable storage media for converting process data extracted from one or more data source systems into a data-source-independent intermediate representation, and then applying a domain-specific semantic ontology to the intermediate representation to create a semantic representation of the process data. The intermediate representation may specify, for each instances of a process object within a process flow, a unique identifier, a set of observations, and references to process-object instance immediately preceding or following the process-object instance at issue.

Abstract: A method includes storing a database search query for searching a semantic database. The database search query includes references to a plurality of data classes. The data classes correspond to data stored in the semantic database. The database search query includes a plurality of filter values and a plurality of return values. Relationship data is stored in association with the stored database search query. The relationship data indicates relationships among data classes included in the plurality of data classes. A data entry form is automatically generated. The data entry form includes a respective data entry mechanism that corresponds to each filter value included in the database search query. The data entry form also includes a respective data display column that corresponds to each return variable. A respective set of permissible input values is automatically generated for each of the data entry mechanisms.

Abstract: Provided is a method and system for detecting changes in models applied to analyze time series data. A method includes receiving at a processor a data stream transmitted from a sensor configured to measure an operating parameter of a component being monitored, wherein the data stream comprises at least time series data. The method also includes analyzing the data stream to identify a sequence of interest in the time series data, searching metadata stored separately for an appropriate model to apply to the time series data, and selecting the appropriate model. Information about the selected appropriate model is carried forward with the time series data.

Abstract: A first attribute is associated with a first data storage device and a second attribute is associated with a second data storage device. The first data storage device stores first time series data and the second data storage device stores second time series data. In parallel, the first attribute is applied to the first time series data and the second attribute is applied to the second time series data. The application is effective to cause an alteration of one or more of the first time series data or the second time series data. The alteration may be a thinning or reduction of the time series data.

Abstract: Characterization information related to time series data is obtained. A data storage rule is automatically determined based upon the characterization information. The rule defines at least one of a location for the storage of the time series data and a format for storage of the time series data. The rule is applied to the time series data and the time series data is stored according to the rule.

Abstract: A user query or analytic user is received. The user query or analytic requires one or more portions of time series data from a plurality of transient memories. The time series data is linked together across the transient memories devices. A location of one or more portions of the time series data is identified at the plurality of transient memories. One or more portions of the time series data is automatically retrieved from the transient memories.

Abstract: A data storage policy is determined. Time series data is received and a score for the time series data is determined. The score prioritizes the time series data according to a likelihood the time series data will be needed for future use. Based upon the data storage policy and the score, the time series data is stored at one or more data storage devices. The score is updated over time to reflect changing priorities regarding the use of the data.