A processor-implemented method is disclosed. The method includes: obtaining, from an activity logging system, activity data associated with one or more defined computing tasks, the activity data indicating progress towards completion of the one or more defined computing tasks, the defined computing tasks being associated with one or more projects; obtaining, from a resource usage monitoring system, time-based resource tracking data associated with at least one of the projects, the resource tracking data including project identifying data associated with the at least one project and project time data identifying one or more time periods reflecting use of a computing resource in association with the at least one project; determining mappings of the one or more time periods to the one or more defined computing tasks based on the project identifying data and the activity data associated with the one or more defined computing tasks; determining, based on the mappings, that at least one task-based resource usage criterion is satisfied; and in response to determining that the at least one task-based resource usage criterion is satisfied, generating a notification of resource usage for display on a computing device.

A computing device including a memory and a processor is provided. The memory stores processor executable instructions for an entity engine. The processor is coupled to the memory. The processor executes the entity engine to cause the computing device to model entities, which hold or classify data. The processor executes the entity engine to cause the computing device to store in the memory a list identifying each of the entities and the entities themselves in correspondence with the list. The processor executes the entity engine to cause the computing device to provide, in response to a selection input from an external system, access to the entities based on the list. The access includes providing the list to the external system, receiving the selection input identifying a first entity of the entities, and exporting the first entity from the memory to the external system.

Disclosed herein are embodiments for providing a trusted autonomy framework for unmanned aerial systems. One embodiment of a method includes receiving a request from an entity to participate in secure data sharing within the trusted autonomy framework for unmanned aerial systems, receiving a type of data that will be shared via the entity, and verifying an identity of the entity, a security infrastructure of the entity, and validating the data to be shared. In some embodiments, in response to verifying, accepting the entity into the trusted autonomy framework for unmanned aerial systems.

As described herein, a system, method, and computer program are provided for normalizing a JSON structure. In use, input defining at least one entity type of a target data structure is received. A source JSON structure is identified. The source JSON structure is traversed for a particular JSON data type to map values in the source JSON structure to corresponding entities of the target data structure based on the at least one entity type defined for the target data structure, where each entity of the target data structure is defined using a relative path between nodes of the source JSON structure.

Systems, devices, computer-implemented methods, and tangible non-transitory computer readable media for performing multilayered generation and processing of computer instructions are provided. For example, a computing device may receive a request with instructions in a first computer language, parse the instructions in the first computer language, analyze the instructions in the first computer language in view of information describing structure of a first application, generate instructions in a second computer language different from the first computer language where the instructions in the second computer language are generated based on the instructions in the first computer language and the information describing structure of the first application, obtain a result from a second application where the result comprises information based on the instructions in the second computing language, and provide the result in response to the request comprising the instructions in the first computer language.

One example method includes assessing an environment using a data confidence fabric. Data from sources associated with an environment such as a remote working environment is ingested into the data confidence fabric and associated with confidence scores. The environments can be assessed or monitored to ensure that the conditions of the environment comply with a standard.

Disclosed is a method, a device and equipment for fusing different instances describing the same entity. The method includes: acquiring a connection diagram comprising a plurality of instances, where different nodes in the connection diagram represent different instances, and connection lines between the nodes represent instance relations between the instances corresponding to the nodes; based on the instance relations, identifying different instances describing the same entity in the connection diagram, fusing the nodes corresponding to the identified instances, and updating the connection diagram.

To effectively utilize knowledge of relationship information among material property parameters the users tangibly and intangibly have in a search system that generates a graph in which material property parameters are nodes and relationships of the material property parameters are edges from a database of material property parameter pairs whose relationships are already known, and conducts a path search in the generated graph. A search system, which includes the database, a graph generator that generates the graph, and a graph searcher searches the graph, further includes a user interface and a user information storage unit corresponding to each user. The user conducts a search unique to the user by inputting relationship information between the material property parameters that he has to the user information storage unit and integrating the relationship information into the above graph. Further, by accumulating a history of searches conducted by the user in the user information storage unit and analyzing the search history, the user can be provided with new knowledge.

The present invention discloses methods and systems for improving asset operation based on identification of significant changes in sensor combinations in related events. Methods include the steps of: providing an asset representation of an asset having an alert-aggregation system; creating a calculated indicator listing having at least one calculated indicator in the asset configured to calculate, predict, or estimate an indicated asset behavior; incorporating the calculated indicator listing into a set of entity connections by associating listing elements in the calculated indicator listing, thereby producing the interconnected representation; associating the identified asset behavior with at least one relevant object and/or at least one relevant process that is impairing the asset from optimally performing, conducting, and/or achieving the identified asset behavior; and generating at least one hint associated with at least one relevant object and/or at least one relevant process that is impairing the identified asset behavior.

A computer-implemented method for evaluating team effectiveness and acting on one or more outliers based on the evaluated team effectiveness. The method retrieves electronic data of one or more users, wherein the electronic data comprises a plurality of electronic communications. The method further extracts one or more concepts and metadata from the retrieved electronic data. The method further determines one or more outliers based on the extracted one or more concepts and metadata, wherein the determined one or more outliers are based on one or more poorly connected concepts and one or more poorly connected users. The method further acts on the determined one or more outliers and displays a report based on the determined one or more outliers.