Abstract: Implementations are described related to users directly manipulating visual depictions of aspects of a data set displayed in a user interface to generate or modify visual representations of the data set, such as a chart. The direct manipulation may be either through a computer input device, (e.g., a keyboard or mouse), or based on other input data, such as a touch input. Aspects of a data set include dimensions, which may be used to filter the data set, and metrics, which are quantifiable elements within the data set. In various implementations, input such as drag-and-drop operations corresponding to visual depictions of aspects of a data set may be interpreted in generating or modifying charts.

Abstract: Implementations are described related to users directly manipulating visual depictions of aspects of a data set displayed in a user interface to generate or modify visual representations of the data set, such as a chart. The direct manipulation may be either through a computer input device, (e.g., a keyboard or mouse), or based on other input data, such as a touch input. Aspects of a data set include dimensions, which may be used to filter the data set, and metrics, which are quantifiable elements within the data set. In various implementations, input such as drag-and-drop operations corresponding to visual depictions of aspects of a data set may be interpreted in generating or modifying charts.

Abstract: Implementations are described related to users directly manipulating visual depictions of aspects of a data set displayed in a user interface to generate or modify visual representations of the data set, such as a chart. The direct manipulation may be either through a computer input device, (e.g., a keyboard or mouse), or based on other input data, such as a touch input. Aspects of a data set include dimensions, which may be used to filter the data set, and metrics, which are quantifiable elements within the data set. In various implementations, input such as drag-and-drop operations corresponding to visual depictions of aspects of a data set may be interpreted in generating or modifying charts.

Abstract: An example for processing patient image data workflows can temporarily serially arrange a set of semantic labeling modules in a patient image data workflow pipeline responsive to receiving an event trigger. The example can also remove the set of modules from the patient image data workflow pipeline responsive to receiving an event completion trigger.

Abstract: Database storage of hierarchically structured messages is facilitated based on structural semantic reflection of the message and automatic reconciliation of the messages. The structural semantics of an incoming message may be assessed and database storage provisioned based on the structural semantic reflection of the message. The system may auto-adapt over time as incoming messages from a known source change and automatically generate code which applies the sequential logic to a stream of messages in order to represent the latest state for a given context. Furthermore, the hierarchical semantics of messaging formats may be applied to a flexible set of database structures that represent the raw contents of the messages.

Abstract: Implementations are described related to users directly manipulating visual depictions of aspects of a data set displayed in a user interface to generate or modify visual representations of the data set, such as a chart. The direct manipulation may be either through a computer input device, (e.g., a keyboard or mouse), or based on other input data, such as a touch input. Aspects of a data set include dimensions, which may be used to filter the data set, and metrics, which are quantifiable elements within the data set. In various implementations, input such as drag-and-drop operations corresponding to visual depictions of aspects of a data set may be interpreted in generating or modifying charts.

Abstract: The described implementations relate to expressing terminologies in a hierarchical form. One implementation can receive a terminology that can include concept-code pairs. For example, each of the concept-code pairs can include a concept and a code that is assigned to the concept by the terminology. The implementation can map the concepts to levels of a hierarchical ontology, and associate some of the concepts across different levels of the hierarchical ontology. The implementation can also provide programmatic access to the concept-code pairs of the terminology via the hierarchical ontology.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: Database storage of hierarchically structured messages is facilitated based on structural semantic reflection of the message and automatic reconciliation of the messages. The structural semantics of an incoming message may be assessed and database storage provisioned based on the structural semantic reflection of the message. The system may auto-adapt over time as incoming messages from a known source change and automatically generate code which applies the sequential logic to a stream of messages in order to represent the latest state for a given context. Furthermore, the hierarchical semantics of messaging formats may be applied to a flexible set of database structures that represent the raw contents of the messages.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: Database storage of hierarchically structured messages is facilitated based on structural semantic reflection of the message and automatic reconciliation of the messages. The structural semantics of an incoming message may be assessed and database storage provisioned based on the structural semantic reflection of the message. The system may auto-adapt over time as incoming messages from a known source change and automatically generate code which applies the sequential logic to a stream of messages in order to represent the latest state for a given context. Furthermore, the hierarchical semantics of messaging formats may be applied to a flexible set of database structures that represent the raw contents of the messages.

Abstract: The described implementations relate to synchronizing records between databases. One implementation can cause historical data of a source database to be recorded as entries on a transaction log and can subsequently cause new data of the source database to be recorded on the transaction log in a same manner as the historical data. This implementation can also identify a distinct attribute associated with an individual entry and generate a message that reflects the individual entry.

Abstract: The present discussion relates to patient image data workflows. One example can temporarily serially arrange a set of semantic labeling modules in a patient image data workflow pipeline responsive to receiving an event trigger. The example can also remove the set of modules from the patient image data workflow pipeline responsive to receiving an event completion trigger.

Abstract: A data consumer is provided with a system that enables automatic generation of a virtual database schema in order to support a customized pattern of data consumption across one or more source databases. In one embodiment, a metadata manager component is configured to facilitate creation of a first data tag and a second data tag. A schema definition manager component is configured to facilitate creation of a data entity that groups the first data tag with the second data tag. A virtual schema generation service component generates the virtual database schema by analyzing the data entity and, based on the grouping of the first data tag with the second data tag, automatically generating and storing a database query statement that, when executed, causes a retrieval of data consistent with data location indicators included in the first and second data tags.

Abstract: The described implementations relate to expressing terminologies in a hierarchical form. One implementation can receive a terminology that can include concept-code pairs. For example, each of the concept-code pairs can include a concept and a code that is assigned to the concept by the terminology. The implementation can map the concepts to levels of a hierarchical ontology, and associate some of the concepts across different levels of the hierarchical ontology. The implementation can also provide programmatic access to the concept-code pairs of the terminology via the hierarchical ontology.

Abstract: This patent relates to patient data and more specifically to accessing and managing patient data. One example can generate a user interface from which a user can select predefined entities for use by a health care management application, wherein the entities abstract the health care management application from underlying patient data. This example can allow the user to select an individual predefined entity from the list or define a different entity on the user interface. This example can also enable the user to associate the individual entity or the different entity with a semantic tag.

Abstract: The description relates to patient identification and consent. One example can determine that a patient possessing a mobile computing device is at a location associated with a health care provider. This example can request consent from the patient via the mobile computing device for the health care provider to access the patient's health care records.

Abstract: Technology is described for associating semantic meaning with data elements. The system can include a messaging module configured to receive a message having data elements. A storage module can store the data elements from the message in a structured format. A message dictionary can be configured to identify a type of the message received and to lexically identify data elements of the message using the message dictionary and the type of message. In addition, a taxonomy module can be configured to provide a semantic meaning for the data elements of the lexically identified portions of the message. Further, a data definition tag repository can store data definition tags and link the message dictionary, the taxonomy, and storage location of the data elements in the storage module. The data definition tags can enable the semantic meaning of data elements to be queried.

Abstract: The described implementations relate to updating views in a database system. One implementation can identify an active view that retrieves records from a database and determine one or more physical tables in the database that are referenced by the active view. The implementation can track one or more columns in the physical tables that are used by the active view and identify a change to the physical tables in a transaction log of the database. If the change does not affect the one or more columns, the change can be treated as an ignorable change for the active view.

Abstract: The description relates to secure patient information handling. One example can receive encrypted patient data from a first entity. The example can receive a request to view the encrypted patient data from a second entity. The request can include a conditional access code and the example can validate the conditional access code. In an instance where the conditional access code is valid, the example can retrieve an encryption key for the encrypted patient data. The example can decrypt at least a portion of the encrypted patient data to produce decrypted patient data. The example can provide at least some of the decrypted patient data to the second entity.