Metadata automated system

1. A method comprising:

providing, with a processor from computer memory, a schema definition language defining trait observations linked to an entity and the trait observations grouped together in a module with metadata, and the trait observations being observable facts about the entity;

capturing a schema definition model table, the schema definition model table including a row for each of the trait observations, the schema definition model table including columns for an entity type and module types, the entity type defining the type of the entity the trait observations are linked to, the module types defining the type of the module the trait observations are linked to, and the schema definition model table including cells containing the metadata;

generating, in an operational data store, separate physical tables for each of the module types within the schema definition model table, the separate physical tables including columns for each of the trait observations in the schema definition model table, the module and the entity having a link therebetween based on at least one of the trait observations; and

populating the separate physical tables with data in accordance with the metadata.

2. The method of claim 1 , further comprising referencing the metadata of the schema definition language to locate a selected trait within the separate physical tables and determine whether the separate physical tables for the module or the entity includes the selected trait.

3. The method of claim 2 , further comprising referencing the metadata of the schema definition language to locate the separate physical tables and determine whether the separate physical tables for the module or the entity includes a subsequent selected trait only if the separate physical tables for the module or the entity included the selected trait.

4. The method of claim 1 , further comprising determining the trait observations are one-hop linkages if the trait observations are grouped within the same module as a selected trait.

5. The method of claim 1 , further comprising:

classifying the entity in a matching cohort when a clinical pattern of selected traits corresponds with the trait observations; or

classifying the entity as a non-matching cohort when the clinical pattern of the selected trait does not correspond with the trait observations.

6. The method of claim 1 , further comprising:

determining whether the module is associated with a report data definition; and

referencing the schema definition language if the module is not associated with the report data definition.

7. The method of claim 1 , wherein populating the separate physical tables includes referencing the metadata of the schema definition language and determining whether the data is a proper data type for the trait observations.

8. A non-transitory computer readable medium, useful in association with a processor, including instructions configured to:

provide a schema definition language defining trait observations linked to an entity and the trait observations grouped together in a module with metadata, and the trait observations being observable facts about the entity;

capture a schema definition model table, the schema definition model table including a row for each of the trait observations, the schema definition model table including columns for an entity type and module types, the entity type defining the type of the entity the trait observations are linked to, the module types defining the type of the module the trait observations are linked to, and the schema definition model table including cells containing the metadata;

generate separate physical tables for each of the module types within the schema definition model table, the separate physical tables including columns for each of the trait observations in the schema definition model table, the module and the entity having a link therebetween based on at least one of the trait observations; and

populate the separate physical tables with data in accordance with the metadata.

9. The non-transitory computer readable medium of claim 8 , further comprising instructions configured to reference the metadata of the schema definition language to locate a selected trait within the separate physical tables and determine whether the separate physical tables for the module or the entity includes the selected trait.

10. The non-transitory computer readable medium of claim 9 , further comprising instructions configured to reference the metadata of the schema definition language to locate the separate physical tables and determine whether the separate physical tables for the module or the entity includes a subsequent selected trait only if the separate physical tables for the module or the entity included the selected trait.

11. The non-transitory computer readable medium of claim 8 , further comprising instructions configured to determine the trait observations are one-hop linkages if the trait observations are grouped within the same module as a selected trait.

12. The non-transitory computer readable medium of claim 8 , further comprising instructions configured to:

classify the entity in a matching cohort when a clinical pattern of selected traits corresponds with the trait observations; or

classify the entity as a non-matching cohort when the clinical pattern of the selected trait does not correspond with the trait observations.

13. The non-transitory computer readable medium of claim 8 , further comprising instructions configured to:

determine whether the module is associated with a report data definition; and

reference the schema definition language if the module is not associated with the report data definition.

14. The non-transitory computer readable medium of claim 8 , wherein the instructions configured to populate the separate physical tables further includes instructions configured to reference the metadata of the schema definition language and determine whether the data is a proper data type for the trait observations.

15. A system comprising one or more processors configured to:

provide, with a processor from computer memory, a schema definition language defining trait observations linked to an entity and the trait observations grouped together in a module with metadata, the module being a concrete instance of a record having a start date, having an end date, and resulting in an observation of the trait observations, and the trait observations being observable facts about the entity,

capture a schema definition model table, the schema definition model table including a row for each of the trait observations, the schema definition model table including columns for an entity type and module types, the entity type defining the type of the entity the trait observations are linked to, the module types defining the type of the module the trait observations are linked to, and the schema definition model table including cells containing the metadata;

generate, in an operational data store, separate physical tables for each of the module types within the schema definition model table, the separate physical tables including columns for each of the trait observations in the schema definition model table, the module and the entity having a link therebetween based on at least one of the trait observations; and

populate the separate physical tables with data in accordance with the metadata.

16. The system of claim 15 , the one or more processors are configured to reference the metadata of the schema definition language to locate a selected trait within the separate physical tables and determine whether the separate physical tables for the module or the entity includes the selected trait.

17. The system of claim 16 , wherein the one or more processors is configured to reference the metadata of the schema definition language to locate the separate physical tables and determine whether the separate physical tables for the module or the entity includes a subsequent selected trait only if the separate physical tables for the module or the entity included the selected trait.

18. The system of claim 15 , wherein the one or more processors is configured to determine the trait observations are one-hop linkages if the trait observations are grouped within the same module as a selected trait.

19. The system of claim 15 , wherein the one or more processors is configured to:

classify the entity in a matching cohort when a clinical pattern of selected traits corresponds with the trait observations; or

classify the entity as a non-matching cohort when the clinical pattern of the selected trait does not correspond with the trait observations.

20. The system of claim 15 , wherein the one or more processors is configured to:

determine whether the module is associated with a report data definition; and

reference the schema definition language if the module is not associated with the report data definition.