Abstract: A method of data classification includes: identifying a cluster of data classes; classifying columns of a current data set; identifying the cluster in the current data set; determining, based on the cluster, an expected column is missing from the current data set; determining a neighboring data set; identifying the expected column in the neighboring data set; classifying the expected column in the neighboring data set; creating a new data class in the current data set; and classifying an unclassified column in the current data set or the neighboring data set with the new data class.

Abstract: Aspects of the present disclosure relate to controlling virtual reality (VR) content displayed on a VR head mounted display (HMD). Communication can be established between a computer system, a VR HMD, and a mobile device. A user input configured to control VR content displayed on a display of the VR HMD can be received on the mobile device. The VR content displayed on the VR HMD can then be controlled based on the user input received on the mobile device.

Abstract: Aspects of the present disclosure relate to controlling virtual reality (VR) content displayed on a VR head mounted display (HMD). Communication can be established between a computer system, a VR HMD, and a mobile device. A user input configured to control VR content displayed on a display of the VR HMD can be received on the mobile device. The VR content displayed on the VR HMD can then be controlled based on the user input received on the mobile device.

Abstract: Methods and systems for data quality evaluation are disclosed. A method includes: receiving, by a computing device, at least one data set and a list of rule expressions to bind; building, by the computing device, candidate binding combinations between columns of the at least one data set and variables of each rule expression in the list of rule expressions; building, by the computing device, a new bound rule expression candidate based on the candidate binding combinations; generating, by the computing device, a new bound rule expression based on the new bound rule expression candidate and a data transformation applied to at least one of the columns of the at least one data set; and storing, by the computing device, the new bound rule expression.

Abstract: The present disclosure relates to a method for accessing data of one or more data sources using a discovery engine. The method comprises: determining a discovery space content from initial metadata of a data source indicated in a data exploration request. The discovery space content may be rendered. The rendered content may be used for determining a set of one or more tasks for generating further metadata from at least part of the data of the data source, wherein the set of tasks comprises a combination of API calls. The API calls may be issued to the discovery engine. Discovery results of the issued API calls may be received. A data discovery status may be devalued using the discovery results. The discovery space content may be augmented using the further metadata and the data discovery status. The augmented discovery space content may be rendered for receiving further API calls.

Abstract: A method of data classification includes: identifying a cluster of data classes; classifying columns of a current data set; identifying the cluster in the current data set; determining, based on the cluster, an expected column is missing from the current data set; determining a neighboring data set; identifying the expected column in the neighboring data set; classifying the expected column in the neighboring data set; creating a new data class in the current data set; and classifying an unclassified column in the current data set or the neighboring data set with the new data class.

Abstract: Methods and systems for data quality evaluation are disclosed. A method includes: receiving, by a computing device, at least one data set and a list of rule expressions to bind; building, by the computing device, candidate binding combinations between columns of the at least one data set and variables of each rule expression in the list of rule expressions; building, by the computing device, a new bound rule expression candidate based on the candidate binding combinations; generating, by the computing device, a new bound rule expression based on the new bound rule expression candidate and a data transformation applied to at least one of the columns of the at least one data set; and storing, by the computing device, the new bound rule expression.

Abstract: The present disclosure relates to a method for accessing data of one or more data sources using a discovery engine. The method comprises: determining a discovery space content from initial metadata of a data source indicated in a data exploration request. The discovery space content may be rendered. The rendered content may be used for determining a set of one or more tasks for generating further metadata from at least part of the data of the data source, wherein the set of tasks comprises a combination of API calls. The API calls may be issued to the discovery engine. Discovery results of the issued API calls may be received. A data discovery status may be devalued using the discovery results. The discovery space content may be augmented using the further metadata and the data discovery status. The augmented discovery space content may be rendered for receiving further API calls.