Computer-implemented systems and methods of analyzing spatial, temporal and contextual elements of data for predictive decision-making

1. A computer-implemented method for predictive decision-making, comprising:

receiving data comprising spatial, temporal and contextual elements from a plurality of sources;

identifying each rule of a set of rules for which the received data is a candidate; and

for the identified rules for which the received data is a candidate, indexing the received data in memory by its spatial, temporal, or contextual elements as a function of said identified rules.

2. The method of claim 1 , further comprising:

disregarding the received data that is not a candidate for any rule of the set of rules.

3. The method of claim 1 , further comprising:

creating a relationship in memory between two or more respective spatial, temporal or contextual elements of said indexed data; and

providing a rule suggestion based on the created relationship.

4. The method of claim 3 , wherein the rule suggestion comprises a modification of one or more rules in the set of rules.

5. The method of claim 4 , wherein the modification comprises modifying a value in a field of the one or more rules.

6. The method of claim 4 , wherein the modification comprises adding a new field to the one or more rules.

7. The method of claim 3 , wherein the rule suggestion comprises an addition of a new rule to the set of rules.

8. The method of claim 1 , further comprising:

dynamically creating one or more spatial, temporal or contextual data structures in memory as a function of the identified rules for which the received data is a candidate; and

wherein the step of indexing comprises placing the respective spatial, temporal or contextual elements of the received data in an appropriate dynamically created data structure as a function of the identified rules.

9. The method of claim 1 , further comprising:

creating a respective data structure in memory for each rule of the set of rules; and

identifying whether received data is a candidate for one or more rules of the set of rules using the created data structures.

10. The method of claim 9 , further comprising:

associating an uncertainty value with a spatial, temporal or contextual element placed in at least one of the created data structures;

receiving data from a different source than the plurality of sources; and

modifying the uncertainty value based on a spatial, temporal, or contextual element of the received data from the different source.

11. The method of claim 1 , further comprising:

identifying an event as satisfying an identified rule in memory using the indexed data.

12. The method of claim 11 , further comprising:

providing an indication that the identified rule is satisfied.

13. The method of claim 12 , wherein the step of providing an indication comprises one or more of the following steps:

displaying a recommended action sequence based on the identified rule;

displaying a result based on the identified rule;

changing a display based on the identified rule;

providing an alert based on the identified rule; and

transmitting a notification message based on the identified rule.

14. A computer-implemented method for predictive decision-making, comprising:

retrieving stored data comprising spatial, temporal and contextual elements;

identifying data from the retrieved data that is a candidate for one or more rules of a set of rules;

disregarding data from the retrieved data that is not a candidate for any rule of the set of rules; and

indexing the identified data in memory by its temporal, spatial or contextual elements as a function of the one or more rules.

15. The method of claim 14 , further comprising:

identifying an event as satisfying at least one of the one or more rules using the indexed data.

16. The method of claim 14 , further comprising:

identifying a plurality of events as satisfying a rule of the one or more rules using the indexed data; and

providing a rule suggestion based on the identified plurality of events.

17. A system for predictive decision-making, comprising:

a rules manager configured to receive a respective set of rules for a user and to define one or more distributed data structures in memory for placing spatial, temporal or contextual elements of data that is determined to be a candidate for rules of the set of rules;

one or more data modules configured to receive data comprising spatial, temporal and contextual elements from a plurality of sources; and

a rules/decision engine module configured to identify each rule of the set of rules for which the received data is a candidate and to index the received data by its spatial, temporal and contextual elements in the one or more distributed data structures.

18. The system of claim 17 , wherein the rules/decision engine module is further configured to disregard received data that is determined not to be a candidate for any rule of the set of rules.

19. The system of claim 17 , wherein the rules/decision engine module is further configured to create a relationship in memory between two or more respective spatial, temporal, or contextual elements of indexed data and to provide a rule suggestion based on the created relationship.

20. The system of claim 17 , wherein the rules/decision engine module is further configured to identify an event as satisfying an identified rule in memory using indexed data; and wherein the system further comprises a communications interface module in communication with the rules/decision engine module and configured to provide an indication that the identified rule is satisfied.