Abstract: Receiving a recording of a remotely-guided augmented reality (AR) session which includes: images of a scene, captured by a camera of a local user; position and orientation data of the camera; and annotations generated by a remote user at points-of-interest (POIs) in a three-dimensional (3D) representation of the scene. Automatically generating a summary of the session, by: projecting the annotations to matching locations in some of the prominent images, based on the POIs of the annotations and on the position and orientation data of the camera and including, in the summary: the prominent images, including those of the prominent images having the projected annotations.

Abstract: A schema modeler for generating an efficient database schema. Provides intelligent choices for schema structure, generates efficient schemas while minimizing the amount of experience required by a database designer. Architectural elements of a schema design are proposed based on field inputs such as field type or relationship. Schema information is manually entered or imported. Configured for structural compatibility and semantic compatibility checking on fields and relationships for data integrity due to nested structure denormalization, inspection of lookup tables that can hold an unlimited number of records, inspection of taxonomy defined on a non-main table, and inspection of the schema for the existence of a main table. Provide suggested field types or schema structures that allow for a more efficient schema to be generated. Field types may include qualifier, multi-lingual, calculation and may include family or attribute table suggestions as well.

Abstract: Enables a database generator interface configured to map complex constructs and semantics so internal complexities are hidden while providing efficient internal storage and speed. Extracts and analyzes complex relationships in database and exposes schema as XSD to allow for external interfacing. Presents a list of tables and fields that exist in database and accepts user input to determine which tables and fields to create an interface for. Lookup fields are listed which allow for user input for specifying which fields to create XSD enumeration lists for. The generated XSD file may be saved and utilized by other mapping tools to allow for interfacing with other databases. Mapping the schema of a extended SQL database allows for users with limited understanding of the internals of the extended SQL database to connect the database to other systems using commonly available tools. May be coupled with web services to provide universal access.

Abstract: A data generator for database schema verification, system sizing and functional test of data dependent applications. Allows for generation of data from random values or from working databases which may be profiled to generate patterns for occurrences of values and sizes of values. The data may be filled with a fill rate that dictates the percentage of fields assigned nulls. Cardinality allows for a fixed number of values to occur across the records for a field. May utilize reference data associated with an existing database to fill fields. Qualifiers and multi-value fields may be filled to mimic real data. Maximum, nominal and average number of occurrences of sizes of data and qualifiers and multi-value data may be specified. May also utilize dictionaries to fill. Hierarchical levels and number of child nodes may also be specified and used in filling taxonomy tables and hierarchy tables for example.

Abstract: A data generator for database schema verification, system sizing and functional test of data dependent applications. Allows for generation of data from random values or from working databases which may be profiled to generate patterns for occurrences of values and sizes of values. The data may be filled with a fill rate that dictates the percentage of fields assigned nulls. Cardinality allows for a fixed number of values to occur across the records for a field. May utilize reference data associated with an existing database to fill fields. Qualifiers and multi-value fields may be filled to mimic real data. Maximum, nominal and average number of occurrences of sizes of data and qualifiers and multi-value data may be specified. May also utilize dictionaries to fill. Hierarchical levels and number of child nodes may also be specified and used in filling taxonomy tables and hierarchy tables for example.

Abstract: A method for metadata verification of a data repository of a computer system is described comprising accessing a data repository through a data profiler program, querying the data repository for metadata information about the data repository, presenting statistics regarding the metadata information using the profiler, analyzing the metadata information to identify suspect metadata information from the data repository and presenting the suspect metadata information for inspection using the profiler.

Abstract: A data generator for database schema verification, system sizing and functional test of data dependent applications. Allows for generation of data from random values or from working databases which may be profiled to generate patterns for occurrences of values and sizes of values. The data may be filled with a fill rate that dictates the percentage of fields assigned nulls. Cardinality allows for a fixed number of values to occur across the records for a field. May utilize reference data associated with an existing database to fill fields. Qualifiers and multi-value fields may be filled to mimic real data. Maximum, nominal and average number of occurrences of sizes of data and qualifiers and multi-value data may be specified. May also utilize dictionaries to fill. Hierarchical levels and number of child nodes may also be specified and used in filling taxonomy tables and hierarchy tables for example.

Abstract: A method for metadata verification of a data repository of a computer system is described comprising accessing a data repository through a data profiler program, querying the data repository for metadata information about the data repository, presenting statistics regarding the metadata information using the profiler, analyzing the metadata information to identify suspect metadata information from the data repository and presenting the suspect metadata information for inspection using the profiler.

Abstract: Enables a database generator interface configured to map complex constructs and semantics so internal complexities are hidden while providing efficient internal storage and speed. Extracts and analyzes complex relationships in database and exposes schema as XSD to allow for external interfacing. Presents a list of tables and fields that exist in database and accepts user input to determine which tables and fields to create an interface for. Lookup fields are listed which allow for user input for specifying which fields to create XSD enumeration lists for. The generated XSD file may be saved and utilized by other mapping tools to allow for interfacing with other databases. Mapping the schema of a extended SQL database allows for users with limited understanding of the internals of the extended SQL database to connect the database to other systems using commonly available tools. May be coupled with web services to provide universal access.

Abstract: A data generator for database schema verification, system sizing and functional test of data dependent applications. Allows for generation of data from random values or from working databases which may be profiled to generate patterns for occurrences of values and sizes of values. The data may be filled with a fill rate that dictates the percentage of fields assigned nulls. Cardinality allows for a fixed number of values to occur across the records for a field. May utilize reference data associated with an existing database to fill fields. Qualifiers and multi-value fields may be filled to mimic real data. Maximum, nominal and average number of occurrences of sizes of data and qualifiers and multi-value data may be specified. May also utilize dictionaries to fill. Hierarchical levels and number of child nodes may also be specified and used in filling taxonomy tables and hierarchy tables for example.

Abstract: A schema modeler for generating an efficient database schema. Provides intelligent choices for schema structure, generates efficient schemas while minimizing the amount of experience required by a database designer. Architectural elements of a schema design are proposed based on field inputs such as field type or relationship. Schema information is manually entered or imported. Configured for structural compatibility and semantic compatibility checking on fields and relationships for data integrity due to nested structure denormalization, inspection of lookup tables that can hold an unlimited number of records, inspection of taxonomy defined on a non-main table, and inspection of the schema for the existence of a main table. Provide suggested field types or schema structures that allow for a more efficient schema to be generated. Field types may include qualifier, multi-lingual, calculation and may include family or attribute table suggestions as well.