Abstract: Various systems and methods are presented regarding implementing one or more capabilities into a dialog flow occurring at an automated interface (e.g., a chatbot). A capability can be invoked at the interface in accordance with a user's requirements, e.g., the capability is a function to review data. An application programming interface (API) can be generated from the capability, wherein the API has features, parameters, metadata, etc., generated based on those of the capability. The API can be incorporated into a dialog, wherein the dialog can be subsequently presented on the interface (e.g., as part of a dialog flow). Interaction between the user and the dialog can cause the capability to be executed. Based upon the API features, etc., the API can be incorporated into a dialog, for example, by cloning a dialog, appending a dialog with the API, replacing a pre-existing API with the API in a dialog, and suchlike.

Abstract: A method of searching a relational database table which includes: providing a relational database table having a plurality of rows and columns such that each of the plurality of columns has a column name descriptive of data in the each of the columns; providing a relational database management system (RDBMS) to manage access to the relational database table; providing at least one metadata tag to some of the plurality of columns wherein the metadata tag is a non-hierarchical keyword or term that is assigned to the some of the plurality of columns; responsive to selecting at least one metadata tag and responsive to selecting a search string, searching by a search and join function of the RDBMS columns of the some of the plurality of columns corresponding to the at least one metadata tag in the relational database table to find data matching the search string.

Abstract: Energy load forecasts are generated via model(s) for the grid hierarchy elements for different forecast time scale periods as a function of different sets of prioritized contextual influencing factors for respective associated combinations of grid hierarchy elements and forecast time scale periods. Relative priority values of the sets of the contextual influencing factors are iteratively weighted until a revised energy load forecast generated as a function of the weighted values via the model(s) is within a threshold value of a historic energy load data value for the associated combination of the grid hierarchy element and forecast time scale period.

Abstract: Energy load forecasts are generated via model(s) for the grid hierarchy elements for different forecast time scale periods as a function of different sets of prioritized contextual influencing factors for respective associated combinations of grid hierarchy elements and forecast time scale periods. Relative priority values of the sets of the contextual influencing factors are iteratively weighted until a revised energy load forecast generated as a function of the weighted values via the model(s) is within a threshold value of a historic energy load data value for the associated combination of the grid hierarchy element and forecast time scale period.

Abstract: A method of searching a relational database table which includes: providing a relational database table having a plurality of rows and columns such that each of the plurality of columns has a column name descriptive of data in the each of the columns; providing a relational database management system (RDBMS) to manage access to the relational database table; providing at least one metadata tag to some of the plurality of columns wherein the metadata tag is a non-hierarchical keyword or term that is assigned to the some of the plurality of columns; responsive to selecting at least one metadata tag and responsive to selecting a search string, searching by a search and join function of the RDBMS columns of the some of the plurality of columns corresponding to the at least one metadata tag in the relational database table to find data matching the search string.