Abstract: A computer-implemented method of visualizing a dataset is implemented on a computer having memory, one or more processors, and a display. The method includes: rendering multiple objects on the display in a tiled manner, wherein each object is a visualization of a respective set of fields of the dataset and there is no overlap between the objects; in response to detecting a first user instruction, switching the rendition of at least one of the objects from the tiled manner to a floating manner; in response to detecting a second user instruction, moving a first object to a location on top of a second object, wherein the location is determined by the second user instruction such that at least a portion of the second object is covered by the first object; and in response to detecting a third user instruction, updating both the first object and the second object.

Abstract: A method generates a graphical user interface, which includes a schema information region and a data visualization region. The schema information region includes field names, each associated with a data field from a data source, and relationship names, each associated with a relation between rows of the data source. The data visualization region includes a row shelf, a column shelf, and a connector shelf. The method detects user selection of field names and a request to associate those field names with respective shelves in the data visualization region. The method also detects user selection of relationship names and a request to associate those relationship names with respective shelves in the data visualization region. The method generates a visual graphic in the data visualization region according to the associations between the user-selected field names and corresponding shelves and the associations between the user-selected relationship names and corresponding shelves.

Abstract: A method of ranking data visualizations is performed at a computing device having one or more processors and memory. The memory stores one or more programs for execution by the one or more processors. A user selects a set of data fields from a set of data. The computing device identifies a plurality of data visualizations based on the data fields selected by the user. For each of the plurality of data visualizations, a score is computed based on a set of ranking criteria. A first ranking criterion of the set of ranking criteria is based on values of one or more of the user-selected data fields in the set of data. A ranked list of the data visualizations is created, which is ordered according to the computed scores of the data visualizations. The ranked list is presented to the user.

Abstract: A method for automatically forming the clearest and most useful visual plot for a given dataset of tuples. A best view type is selected for a view that includes a subsequently added new field. The visual plot is populated with the data in the view and then automatically rendered for the user. A dataset that is retrieved from a storage is analyzed to identify all the data types found in the dataset, and to determine the best view type to assign to the dataset's views. The visual plot is then populated with the data according to this best view type, and is automatically rendered for the user.

Abstract: A method of ranking data visualizations is performed at a computing device having one or more processors and memory. The memory stores one or more programs for execution by the processors. A user selects a plurality of data fields from a set of data, and the computing device generates a plurality of data visualization options. Each data visualization option associates each of the user-selected data fields with a respective predefined visual specification feature. For each of the generated data visualization options, the device calculates a score based on a set of ranking criteria. A first ranking criterion of the set of ranking criteria is based on values of one or more of the user-selected data fields in the set of data. A ranked list of the data visualization options is then created, where the ranked list is ordered according to the computed scores of the data visualization options.

Abstract: A method dynamically assigns tasks for visually presenting data. A server receives a request, from a client device, to display a visual representation of data in a designated format. The request specifies one or more client device characteristics, including: client memory capacity; current client memory utilization; client processor capability; current client processor utilization; and the client's web browser. The server determines whether to render the requested visual representation at the server or at the client device based on several factors, including the client device characteristics and the size of the data set. When rendering at the client, the server sends the requested data to the client, including data necessary to render the visual representation in the designated format. Otherwise, the server renders the requested visual representation according to the designated format using the data, and sends the rendered image to the client.

Abstract: A method of generating a statistical model for a dataset operates at a computer system having one or more processors and memory. The memory stores one or more programs configured for execution by the one or more processors. The process receives a visual specification. The visual specification defines a graphical representation of a portion of the dataset. The visual specification includes a first field and a second field of the dataset. The method determines a set of data properties for each of the first and second fields. The process then generates a statistical model of a mathematical relationship between the first and second fields based on the data properties of the first and second fields and data values associated with the first and second fields in the dataset. The process displays the graphical representation and the statistical model superimposed on the graphical representation.

Abstract: A method of ranking data visualizations is performed at a computing device having one or more processors and memory. The memory stores one or more programs for execution by the processors. A user selects a plurality of data fields from a set of data, and the computing device generates a plurality of data visualization options. Each data visualization option associates each of the user-selected data fields with a respective predefined visual specification feature. For each of the generated data visualization options, the device calculates a score based on a set of ranking criteria. A first ranking criterion of the set of ranking criteria is based on values of one or more of the user-selected data fields in the set of data. A ranked list of the data visualization options is then created, where the ranked list is ordered according to the computed scores of the data visualization options.

Abstract: A method ranks data visualizations. A user selects a set of data fields from a set of data. A device identifies a plurality of data visualizations that use each data field in the user-selected set of data fields and identifies a plurality of respective alternative data visualizations. Each respective alternative data visualization uses each data field in a respective modified set of data fields. Each respective modified set differs from the user-selected set by a limited sequence of atomic operations. For each of the data visualizations and each of the alternative data visualizations, the device computes a score based on a set of ranking criteria. At least one criterion used to compute each score uses values of one or more of the data fields in the set of data. The list of high scoring data visualizations and alternative data visualizations is presented to the user.

Abstract: A method of ranking data visualizations is performed at a computing device having one or more processors and memory. The memory stores one or more programs for execution by the one or more processors. A user selects a set of data fields from a set of data. The computing device identifies a plurality of data visualizations based on the data fields selected by the user. For each of the plurality of data visualizations, a score is computed based on a set of ranking criteria. A first ranking criterion of the set of ranking criteria is based on values of one or more of the user-selected data fields in the set of data. A ranked list of the data visualizations is created, which is ordered according to the computed scores of the data visualizations. The ranked list is presented to the user.

Abstract: A computer-implemented method of generating marks in a graphical view includes receiving a first user request to associate a first set of data samples with a first visual mark property. In response to the first user request, area marks are displayed in a graphical view. Respective area marks correspond to respective data samples in the first set. A second user request is received to associate the first set of data samples with a second visual mark property. In response to the second user request, point marks are displayed in the graphical view. Respective point marks correspond to respective data samples in the first set.

Abstract: A method of automatically generating models from a dataset includes multiple steps. First, a description of a view of a dataset is provided. The description includes multiple fields associated with the dataset. Next, a set of properties is determined for each of the multiple fields. Finally, the description is automatically translated into one or more models based on the respective properties of the multiple fields and a set of predefined heuristics.

Abstract: A computer-implemented method of generating a map view includes accessing a dataset having multiple records and multiple fields. One or more of the multiple fields are identified as geographical fields. Geographical codes are automatically associated with a first one of the identified geographical fields. A geographical map is generated for the dataset. Generating the geographical map includes generating a first plurality of marks on the geographical map. The first plurality of marks is positioned on the geographical map in accordance with the geographical codes associated with the first one of the identified geographical fields.

Abstract: In response to a user request, a computer generates a graphical user interface on a computer display. A schema information region of the graphical user interface includes multiple operand names, each operand name associated with one or more fields of a multi-dimensional database. A data visualization region of the graphical user interface includes multiple shelves. Upon detecting a user selection of the operand names and a user request to associate each user-selected operand name with a respective shelf in the data visualization region, the computer generates a visual table in the data visualization region in accordance with the associations between the operand names and the corresponding shelves. The visual table includes a plurality of panes, each pane having at least one axis defined based on data for the fields associated with a respective operand name.

Abstract: A method of automatically generating models from a dataset includes multiple steps. First, a description of a view of a dataset is provided. The description includes multiple fields associated with the dataset. Next, a set of properties is determined for each of the multiple fields. Finally, the description is automatically translated into one or more models based on the respective properties of the multiple fields and a set of predefined heuristics.

Abstract: A method for generating marks when displaying data, such as the results of a query across a database. The method is preferably used in conjunction with a dataset whose fields comprise a plurality of levels. A visual plot is constructed based on a specification. A first level from the plurality of levels is represented by a first component of the visual plot. A second level from the plurality of levels is represented by a second component of the visual plot. The dataset is optionally queried to retrieve data in accordance with the specification. The visual plot is populated with the retrieved data in accordance with the specification.