Systems and methods are provided for using point-in-time architecture (PTA) databases. An exemplary method includes: entering first data, received from a first data source, into a first PTA database; receiving a first instruction to process the first data using a first statistical operation; executing the first statistical operation for the first data, resulting in first output data; filtering the first output data based on a user-selected attribute; and performing multiple stages of a data processing operation for the first output data.

Systems and methods are provided for using point-in-time architecture (PTA) databases. An exemplary method includes: entering first data, received from a first data source, into a first PTA database; receiving a first instruction to process the first data using a first statistical operation; executing the first statistical operation for the first data, resulting in first output data; filtering the first output data based on a user-selected attribute; and performing multiple stages of a data processing operation for the first output data.

A system and method are disclosed for the collection and aggregation of data from contributing members of a community, such as health-related, personal, genomic, medical, and other data of interest for individuals and populations. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Steps are taken to determine incompleteness and incorrectness of the data, and the data may be improved or completed automatically, based upon interaction with members, additional contributions of data, and so forth.

A system and method are disclosed for the collection and aggregation of data from contributing members of a community, such as health-related, personal, genomic, medical, and other data of interest for individuals and populations. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Steps are taken to determine incompleteness and incorrectness of the data, and the data may be improved or completed automatically, based upon interaction with members, additional contributions of data, and so forth.

A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

An apparatus and methods are provided to cross-check the reliability of data. Referring to one of the methods, the cross-checking includes receiving a client request containing data in the form of geographic-related information associated with a location. The method also includes determining one or more knowledge providers to determine one or more confidence levels for the data of the client request based on a type of the geographic-related information at the specific location. The method further includes causing the transmission of at least some of the geographic-related information the client request to the one or more knowledge providers. The method still further includes determining one or more confidence levels of the geographic-related information based on a comparison of the geographic-related information and a known resource associated the specific location. A corresponding apparatus and additional method are also provided.

An apparatus and methods are provided to cross-check the reliability of data. Referring to one of the methods, the cross-checking includes receiving a client request containing data in the form of geographic-related information associated with a location. The method also includes determining one or more knowledge providers to determine one or more confidence levels for the data of the client request based on a type of the geographic-related information at the specific location. The method further includes causing the transmission of at least some of the geographic-related information the client request to the one or more knowledge providers. The method still further includes determining one or more confidence levels of the geographic-related information based on a comparison of the geographic-related information and a known resource associated the specific location. A corresponding apparatus and additional method are also provided.

Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.