Described are platforms, systems, and methods to discover relationships among equipment in automated industrial or commercial environments by cycling each individual piece of equipment while observing sensors in all other equipment in order to measure how each part reacts to each other part. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; issue one or more commands to cycle a current data source in the a plurality of data sources; monitor the automation environment for events or state changes in the data sources; detect one or more events or one or more state changes in one or more other data sources in the a plurality of data sources; and determine one or more relationships between the current data source and the one or more other data sources.

Described are platforms, systems, and methods to automatically discover, extract, map, merge, and enrich data found in on-premises in automated industrial and commercial environments and cloud systems for purposes of providing developers access to normalized, merged, and enriched data through an API. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; retrieve data from at least one of the identified data sources; apply a first algorithm to map the retrieved data to a predetermined ontology; merge the mapped data into a data store comprising timeseries of the mapped data; apply a second algorithm to identify patterns in the merged data and enriching the data based on one or more identified patterns; and provide one or more APIs or one or more real-time streams to provide access to the enriched data.

Described are platforms, systems, and methods to discover relationships among equipment in automated industrial or commercial environments by looking for synchrony in state changes among the equipment. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; detect one or more events or one or more state changes in the data sources; store the detected events or state changes; detect synchrony in the detected events or state changes by performing operations comprising: identifying combinatorial pairs of data sources having an event or state change within a predetermined time window; and conducting pairwise testing for each identified combinatorial pair of data sources by applying an algorithm to the stored detected events or state changes; and determine one or more relationships for at least one identified combinatorial pair of data sources.

Described are platforms, systems, and methods to automatically discover, extract, map, merge, and enrich data found in on-premises in automated industrial and commercial environments and cloud systems for purposes of providing developers access to normalized, merged, and enriched data through an API. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; retrieve data from at least one of the identified data sources; apply a first algorithm to map the retrieved data to a predetermined ontology; merge the mapped data into a data store comprising timeseries of the mapped data; apply a second algorithm to identify patterns in the merged data and enriching the data based on one or more identified patterns; and provide one or more APIs or one or more real-time streams to provide access to the enriched data.

Described are platforms, systems, and methods to combine counts of activity correlations over time with a link salience method to identify collections of digital devices in an automated environment to identify sub-systems comprised of portions of the overall environment. The platforms, systems, and methods detect activity in a plurality of data sources associated with an automation environment; determine correlation in the detected activity between two or more of the data sources; store records of determined correlation in the detected activity over time in a data storage system; apply a link salience algorithm to the stored records of determined correlation in the detected activity to determine a salience property; and identify one or more subsystems in the automation environment based on the salience property.

A program development support device for supporting development of a safety program to be executed in a safety controller includes: a development module that develops the safety program in response to user operation; a calculation module that calculates an identification value according to data of the developed safety program, in accordance with a function for calculating a random value with respect to an input; and an output module that outputs a document related to the safety program. The output module provides the identification value calculated by the calculation module to all pages of the document which are related to the safety program.

An electronic-manual browsing apparatus includes an electronic-manual-display processing section that displays, on an electronic-manual display screen on a display section, an electronic manual including a sample program concerning a control apparatus, a program-creation-screen-display processing section that displays, on the display section, a program creation screen for creating a program used in the control apparatus, and a program copy section that copies the sample program in the electronic manual selected according to an instruction from a user and temporarily stores the sample program. The program-creation-screen-display processing section pastes the stored sample program in the program creation screen in a format editable on the program creation screen.