Systems and methods for implementing a virtual machine for interactive visual analysis

Patent metadata

Field	Value
Publication number	US-10380140-B2
Application number	US-201514954957-A
Country	US
Kind code	B2
Filing date	Nov 30, 2015
Priority date	Nov 30, 2015
Publication date	Aug 13, 2019
Grant date	Aug 13, 2019

Abstract

A method builds data visualization data flow graphs. A visual specification is received that defines characteristics of a data visualization to be rendered based on data from one or more databases. The method receives metadata for the specified databases. Using the metadata and visual specification, form a data flow graph, which is a directed graph including data nodes and transform nodes. Each transform node specifies a set of inputs for retrieval, where each input corresponds to a data node. Each transform node also specifies a transform operator that identifies an operation to be performed on the inputs. Some transform nodes specify (a) a set of outputs corresponding to respective data nodes and (b) a function for use in performing the operation of the transform node. The method thereby builds a data flow graph that can be executed to render a data visualization according to the visual specification using the databases.

First claim

What is claimed is:

1. A method of building data visualization data flow graphs, comprising:
at a computer having one or more processors and memory storing one or more programs configured for execution by the one or more processors:
receiving a visual specification that defines characteristics of a data visualization to be rendered based on data from one or more specified databases, wherein the data visualization characteristics include mark type and one or more encodings of the marks;
receiving metadata for the specified databases;
using the received metadata and received visual specification to form a data visualization data flow graph, which is a directed graph including a plurality of data nodes and a plurality of transform nodes;
wherein each transform node specifies:
a respective set of one or more inputs for retrieval, each input corresponding to a respective data node; and
a respective transformation operator that identifies a respective operation to be performed on the respective one or more inputs;

wherein each of a subset of the transform nodes specifies:
a respective set of one or more outputs corresponding to respective data nodes; and
a respective function for use in performing the respective operation of the respective transform node;

thereby building a data visualization data flow graph; and
executing the data visualization data flow graph to generate and render a data visualization according to the defined characteristics in the visual specification.

2. The method of claim 1 , further comprising:
displaying a graphical user interface on a computer display, wherein the graphical user interface includes a schema information region and a data visualization region, wherein the schema information region includes multiple field names, each field name associated with a data field from the specified databases, wherein the data visualization region includes a plurality of shelf regions that determine the characteristics of the data visualization, and wherein each shelf region is configured to receive user placement of one or more of the field names from the schema information region; and
building the visual specification according to user selection of one or more of the field names and user placement of each user-selected field name in a respective shelf region in the data visualization region.

3. The method of claim 2 , further comprising after forming the data visualization data flow graph:
receiving user input to modify the visual specification; and
updating the data visualization data flow graph according to the modified visual specification.

4. The method of claim 3 , wherein updating the data visualization data flow graph comprises:
identifying one or more transformation nodes affected by the modified visual specification; and
updating only the identified one or more transformation nodes while retaining unaffected transformation nodes without change.

5. The method of claim 1 , further comprising:
retrieving data from the one or more databases according to the plurality of data nodes; and
storing the retrieved data in a runtime data store distinct from the data visualization data flow graph.

6. The method of claim 1 , wherein forming the data visualization data flow graph further uses one or more style sheets and one or more layout options.

7. The method of claim 1 , wherein the data visualization comprises a dashboard that includes a plurality of distinct component data visualizations, the visual specification comprises a plurality of component visual specifications, and each component data visualization is based on a respective one of the component visual specifications.

8. The method of claim 1 , wherein forming the data visualization data flow graph further uses an analytic specification that defines one or more data visualization analytic features, forming one or more transform nodes corresponding to each analytic feature, which are configured to construct the corresponding analytic features for superposition on the data visualization.

9. The method of claim 8 , wherein the analytic features are selected from the group consisting of reference lines, trend lines, and reference bands.

10. The method of claim 1 , wherein the mark type is selected from the group consisting of bar chart, line chart, scatter plot, text table, and map.

11. The method of claim 1 , wherein the one or more encodings are selected from the group consisting of mark size, mark color, and mark label.

12. The method of claim 1 , further comprising transmitting the data visualization data flow graph to a computing device distinct from the computer, wherein the data visualization is rendered by the computing device according to the data visualization data flow graph.

13. The method of claim 12 , further comprising:
retrieving data from the one or more specified databases according to the plurality of data nodes;
storing the retrieved data in a runtime data store distinct from the data visualization data flow graph; and
transmitting the runtime data store to the computing device.

14. The method of claim 1 , wherein information describing each transform node is written in a visual transform language.

15. The method of claim 1 , further comprising after forming the data visualization data flow graph:
modifying the data visualization data flow graph to reduce subsequent runtime execution time when the data visualization is rendered.

16. The method of claim 15 , wherein modifying the data visualization data flow graph comprises performing one or more optimization steps selected from the group consisting of:
forming a parallel execution path of a first transform node and a second transform node when it is determined that the first transform node and the second transform node are independent;
removing a processing step of saving to a data store output data from a third transform when the output data is used only by subsequent transform nodes; and
combining two or more nodes into a single node when each of the two or more nodes operates on the same inputs and a single node can perform the operations corresponding to the two or more nodes in parallel.

17. The method of claim 1 , wherein each data node specifies a source that is either from the one or more databases or from output of a respective transform node.

18. The method of claim 1 , wherein a subset of the transform nodes specify graphical rendering of data visualization elements.

19. A system for building data visualization data flow graphs, comprising:
one or more processors;
memory; and
one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs comprising instructions for:
receiving a visual specification that defines characteristics of a data visualization to be rendered based on data from one or more specified databases, wherein the data visualization characteristics include mark type and one or more encodings of the marks;
receiving metadata for the specified databases;
using the received metadata and received visual specification to form a data visualization data flow graph, which is a directed graph including a plurality of data nodes and a plurality of transform nodes;
wherein each transform node specifies:
a respective set of one or more inputs for retrieval, each input corresponding to a respective data node; and
a respective transformation operator that identifies a respective operation to be performed on the respective one or more inputs;

wherein each of a subset of the tra

Assignees

• Tableau Software Inc

Inventors

• Sherman Scott

Classifications

• G06F16/26 Primary

  Visual data mining; Browsing structured data · CPC title

• G06F16/54

  Browsing; Visualisation therefor · CPC title