Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: A particular option selection may be provided by an online service platform (OSP) to a client regarding one or more predefined services that the OSP can be configured to perform. These may include automatic activities option selection(s) that may trigger the OSP to automatically start one or more activities upon one or more thresholds being crossed. The OSP may apply digital rules to the dataset(s) of the client to determine whether or not to automatically start or stop activities, including producing respective resources, upon a threshold being crossed, to determine a requested resource and then push, send, or otherwise cause to be transmitted a notification regarding the produced resource or other activities.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: Systems and methods electronically produce a local estimate of less-than-critical resources based on a client side version of digital rules and a coarse values received from an online service provider. Although using the client side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.

Abstract: Systems and methods electronically produce a local estimate of less-than-critical resources based on a client-side version of digital rules and coarse values received from an online service provider. Although using the client-side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.

Abstract: Systems and methods electronically produce a local estimate of less-than-critical resources based on a client-side version of digital rules and coarse values received from an online service provider. Although using the client-side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.

Abstract: A particular option selection may be provided by an online service platform (OSP) to a client regarding one or more predefined services that the OSP can be configured to perform. These may include automatic activities option selection(s) that may trigger the OSP to automatically start one or more activities upon one or more thresholds being crossed. The OSP may apply digital rules to the dataset(s) of the client to determine whether or not to automatically start or stop activities, including producing respective resources, upon a threshold being crossed, to determine a requested resource and then push, send, or otherwise cause to be transmitted a notification regarding the produced resource or other activities.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.

Abstract: Systems and methods electronically produce a local estimate of less-than-critical resources based on a client-side version of digital rules and coarse values received from an online service provider. Although using the client-side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.

Abstract: Systems and methods electronically produce a local estimate of less-than-critical resources based on a client side version of digital rules and a coarse values received from an online service provider. Although using the client side version of digital rules and the coarse values may not include all the parameters and values needed to provide a fully accurate estimate of the resource, the ability to locally estimate resources without having to make network calls to the online service provider, such as when there are unfavorable conditions or latency of the network, imminent overloading of the online service provider or other operating conditions or demands on the online service provider preventing it from producing a timely more accurate estimate, provides a faster and more efficient way of obtaining a potentially useful estimate of resources.

Abstract: Systems and methods electronically generate sample dots, produce resources associated with the dots and estimate a resource for a target point from known resources of dots near the target point based on client side version of digital rules, cataloged data and coarse values previously received from the online service platform. A client receives cataloged data of a cataloged domain in which the cataloged data includes data representing a plurality of dots and a respective computed resource value for each of the dots and each dot of the plurality of dots represents a point in the cataloged domain. In response to confirming a target point is in the cataloged domain, the system discovers a closest one or more dots to the target point based on the cataloged data, estimates a statistic for a resource for the target point based on the respective computed resource values of the closest one or more dots, stores the estimated statistic in a memory, and produces the local estimate based on the estimated statistic.