Abstract: A computer system obtains a data model that encodes a data source as a tree of logical tables. Each logical table includes respective data fields of the data source. For each data field in the logical tables, the system automatically assigns a semantic role to the data field based on a concept obtained from a concept graph, a data type of the data field, and data values of the data field. The system determines hierarchies between the data field and other data fields in the data source based on their respective semantic roles. The system validates the data field based on the assigned semantic role and the determined hierarchies. The system displays transformations to clean the data field based on the assigned semantic role. The system transforms data values for the data field according to a user input and updates the logical tables according to the transforming.

Abstract: A computer user interface displays a two-dimensional grid of data values. A user selects a first set of two or more columns of data values from the grid, and the computer performs a first pivot on the first set of two or more columns to form a modified grid having a plurality of new rows and a first set of two or more new columns. The user selects a second set of two or more columns of data values from the grid. The second set is distinct from the first set. The computer performs a second pivot on the second set of two or more columns to form a second new column added to the modified grid. Each data value from the second set of two or more columns is added to the second new column in a respective row of the new rows. The computer redisplays the modified grid.

Abstract: A method executes at a computing device that includes a display, one or more processors, and memory. The device displays a data visualization based on a dataset retrieved from a database. The device also displays one or more first phrases in a first region. The first phrases define the data visualization. The device receives a first user input in a second region to specify a natural language command related to the displayed data visualization. In response to the first user input, the device displays one or more proposed actions. The device receives user selection of a first proposed action of the proposed actions. In response to the user selection, the device generates an updated data visualization. The device displays the updated data visualization and displays a plurality of second phrases in the first region. The second phrases define the updated data visualization.

Abstract: A data visualization application receives user actions to (i) associate a first data field with a first shelf and (ii) associate second and third data fields with a second shelf. The method receives an additional user action to specify a nested sort according to data for the first and third data fields. The method generates and displays a data visualization in accordance with the received actions, including: (i) partitioning retrieved data into groups of tuples, each tuple including data for the data fields, and each group of tuples corresponding to a distinct value of the second data field, (ii) forming panes, each pane corresponding to a respective group of tuples, and (iii) within each pane, displaying data marks, each data mark corresponding to a respective tuple.

Abstract: A method of interactive visual analysis is performed at a computer. The computer generates a data visualization by executing a data visualization data flow graph comprising a directed graph having a plurality of nodes. Each of the nodes specifies either a data retrieval operation or a data transformation operation and the data visualization comprises visual marks having a first set of characteristics, including a first mark type and one or more first visual mark encodings. A user specifies a second mark type and/or one or more second visual mark encodings. In response, the computer updates a portion, less than all, of the data flow graph according to the second mark type and/or the one or more second visual mark encodings, and generates an updated data visualization by executing updated nodes of the data flow graph without executing nodes not updated according to the user input.

Abstract: A computing device displays a data visualization interface and receives user selection of a data source and a natural language command directed to the data source. The device forms a first intermediate expression according to a context-free grammar and a semantic model of data fields in the data source. In accordance with a determination that the first intermediate expression omits sufficient information for generating a data visualization, the device infers the omitted information associated with the data source using one or more inferencing rules based on syntactic and semantic constraints imposed by the context-free grammar. The device forms an updated intermediate expression, and translates the updated intermediate expression into database queries. It executes the database queries to retrieve data sets from the data source, then generates and displays a data visualization of the retrieved data sets.

Abstract: A computer receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with either data fields (e.g., dimension and/or measures) or filters. The computer obtains a data model encoding the data source as a tree of related logical tables. Each logical table includes logical fields, each of which corresponds to either a data field or a calculation that spans logical tables. The computer generates a dimension subquery for the dimensions and the filters. The computer also generates, for each measure, an aggregated measure subquery grouped by the dimensions. The computer forms a final query by joining the dimension subquery to each of the aggregated measure subqueries. The computer subsequently executes the final query and displays a data visualization according to the results of the final query.

Abstract: The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is either a dimension or a measure. From an object model of the data source, the method identifies a minimal subtree that includes all of the dimension data fields and constructs a query from the minimal subtree. The method executes the query against the data source to retrieve a set of tuples, each tuple comprising a unique ordered combination of data values for the dimension data fields. For each tuple, the method forms an extended tuple by appending aggregated data values corresponding to each measure data field. The method then builds and displays a data visualization according to the data fields in the extended tuples and according to the visual variables to which the data fields are associated.

Abstract: A user selects a node that specifies an operation for a dataset. In response, a computer system displays data values for the dataset, in a grid in a data pane. The grid includes a first column and a second column. In the grid, the user edits a first data value in the first column in a first row. The user input changes the first data value to a replacement data value. The computer system identifies a second data value in the second column in the first row, and identifies one or more additional rows in the grid, whose data values for the first column and the second column match the first data value and the second data value. The computer system then updates the data value in the first column for a second row in the grid to the replacement data value.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.

Abstract: A computer system concurrently displays a plurality of panes in a user interface. The panes include a first pane that displays a flow diagram having one or more nodes. Each node contains one or more icons. Each icon represents a respective data transformation operation. The panes include a second pane that displays a plurality of data rows and/or data columns for an intermediate dataset corresponding to a user-selected node. The computer system receives a user input, in the first pane, to perform a first data transformation operation at a selected node. In response to receiving the user input, the computer system performs the first data transformation operation. The computer system displays, in the first pane, an additional icon corresponding to the first data transformation operation at the selected node. The computer system updates the second pane in accordance with the first data transformation operation.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: An electronic device displays a chart in accordance with contents of a plurality of shelf regions of a data visualization interface. The chart includes visual marks representing a set of data. The electronic device generates a visual analytic object by applying a first analytic operation to the set of data represented by the visual marks, and displays the visual analytic object superimposed over the chart. The device detects user input to select the displayed visual analytic object and place an icon representing the visual analytic object onto a first shelf region of the plurality of shelf regions. In response to the user input, the electronic device updates content of the first shelf region to include an association with the first analytic operation corresponding to the visual analytic object.

Abstract: A computer system obtains a data model that encodes a data source as a tree of logical tables. Each logical table includes respective data fields of the data source. For each data field in the logical tables, the system automatically assigns a semantic role to the data field based on a concept obtained from a concept graph. The system determines hierarchies between the data field and other data fields in the first data source based on a respective semantic role of the data field and semantic roles of the other data fields. The system validates the data field based on the assigned semantic role and the determined hierarchies. The system displays transformations to clean the data field based on the assigned semantic role. The system transforms data values for the data field according to a user input and updates the logical tables according to the transformed data values.

Abstract: A computer system displays a user interface that includes a flow pane, a tool pane, a profile pane, and a data pane. The flow pane displays a node/link flow diagram that identifies data sources, operations, and output datasets. The tool pane includes a data source selector that enables users to add data sources to the flow diagram, and includes an operation palette that enables users to insert nodes into the flow diagram for performing specific transformation operations. The profile pane displays schemas corresponding to selected nodes in the flow diagram, including information about data fields and statistical information about data values for the data fields and enables users to modify the flow diagram by interacting with individual data elements. The data pane displays rows of data corresponding to selected nodes in the flow diagram, and enables users to modify the flow diagram by interacting with individual data values.

Abstract: A computer device receives, via a graphical user interface, a first user input specifying a first data field of the dataset. The first data field has a first data type. In response to receiving the first user input, the device selects a first visualization type of a data visualization, for visualizing a portion of the dataset based on the first data type, and displays the data visualization. The device receives, via the graphical user interface, a second user input specifying a second data field of the dataset. The second data field is distinct from the first data field and has a second data type. In response to receiving the second user input, the device selects a second visualization type based at least in part on the first data type and the second data type, and displays an updated data visualization, having the second visualization type, in the graphical user interface.

Abstract: A method implements data visualization collaboration. The method displays, for a second user, an interface with a comment pane that displays a first comment text and a first thumbnail image of a data visualization generated according to a first visual specification, from a first user. In response to detecting an input from the second user to select the first thumbnail image, the method generates and displays the data visualization. The method receives, from the second user, input modifying the data visualization, and input specifying a second comment that refers to the data visualization. In response, the method generates a second thumbnail image and a second visual specification corresponding to the modified data visualization, and transmits that information along with the second comment text to the first user.

Abstract: A method is executed at a computer system to retrieve data from a database. Upon receiving a database query, a database engine of the computer system parses the query to form an operator tree including a plurality of join operators. For one of the plurality of clauses, the database engine adds to the operator tree a respective node that specifies a mark join operator, a single join operator, an inner join operator, or an outer join operator. Specifically, the database engine adds the mark join operator when the clause includes one of a predetermined set of predicate subqueries, and adds the single join operator when the clause includes a scalar subquery. The database engine performs one or more optimization passes on the operator tree to form an optimized execution plan, and executes the optimized execution plan to retrieve a result set from the database.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database. The computer computes an initial visualization state that includes elements corresponding to data attributes of the data visualization. The computer receives user input to specify a natural language command related to the displayed data visualization. The computer extracts cue phrases from the natural language command. The computer also determines a transitional goal, to transform the data visualization, based on the cue phrases. The computer derives an updated visualization state based on the transitional goal, by applying transitional rules to each element of the initial visualization state. The computer subsequently computes analytical functions associated with the visualization states, thereby creating functional phrases. The computer then updates the data visualization based on the functional phrases.

Abstract: A computing device receives a user input to specify a natural language command directed to a data source. The device identifies a first keyword, corresponding to a first data field from the data source, in the natural language command. The device identifies a second keyword in the natural language command. The second keyword comprises an adjective that provides context for the first data field. The device generates a visual specification based on the first and second keywords. The visual specification specifies the data source, a plurality of visual variables, and a plurality of data fields from the data source, including the first data field. The visual variables include a first visual variable that specifies filtering of the first data field according to the second keyword. The device generates and displays a data visualization based on the visual specification.