Systems and methods for ranking data visualizations using different data fields

• US 10,712,903 B2
• Filed: 02/17/2017
• Issued: 07/14/2020
• Est. Priority Date: 09/09/2005
• Status: Active Grant

• Current Assignee: Tableau Software Incorporated (Salesforce.com, Inc.)
• Original Assignee: Tableau Software Incorporated (Salesforce.com, Inc.)
• Inventors: Mackinlay, Jock Douglas, Stolte, Christopher Richard, Hanrahan, Patrick
• Primary Examiner(s): Savla, Arpan P.
• Assistant Examiner(s): Stitt, Erik V
• Application Number:
  US15/436,706
• Publication Number:
  US 20170249369A1
• Time in Patent Office: 1,243 Days
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/2393 Updating materialised views
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/252 between a Database Management System and a front-end application
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 3/04817 using icons graphical or visual programming using iconic symbols G06F8/34
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

The implementations described herein include methods and systems for ranking data visualizations. A method is performed at a computing device having one or more processors and memory storing programs for execution by the processors. The method receives user selection of a set of data fields and identifies data visualizations that use each data field in the user-selected set. The method automatically forms modified sets of data fields that each differ from the user-selected set by at most two atomic operations, each selected from: removing or adding a data field; replacing a user-selected data field with a hierarchically narrower or broader data field; or adding, removing, or modifying a filter for a data field. The method identifies alternative data visualizations using each respective modified set, computes a score for each data visualization and alternative data visualization, and presents high scoring data visualizations and high scoring alternative data visualizations to the user.

Claims

1. A method of ranking data visualizations, comprising:

at a computing device having one or more processors and memory, wherein the memory stores one or more programs for execution by the one or more processors;

receiving user selection of a set of data fields from a set of data;

identifying a plurality of data visualizations that use each data field in the user-selected set of data fields;

automatically forming a plurality of modified sets of data fields, each differing from the user-selected set by a limited sequence of at most two atomic operations, wherein each of the atomic operations is selected from the group consisting of;

removing a single data field from the user-selected set;

adding a single data field to the user-selected set;

replacing a user-selected data field with a hierarchically narrower data field from the set of data;

replacing a user-selected data field with a hierarchically broader data field from the set of data;

adding a filter to a data field that limits values retrieved to a specified subset of values;

removing a user-selected filter from a data field so that there is no limit on values retrieved for the data field; and

modifying a filter for a data field, thereby altering values retrieved for the data field;

identifying a plurality of respective alternative data visualizations, each respective alternative data visualization using each data field in a respective one of the modified sets of data fields;

for each of the data visualizations and each of the alternative data visualizations, computing a score based on a set of ranking criteria, wherein at least one ranking criterion used to compute each score is based on patterns of data values of one or more of the data fields in the set of data; and

presenting data visualization options to the user, wherein the presented options correspond to high scoring data visualizations and high scoring alternative data visualizations.

2. The method of claim 1, wherein the data visualization options are presented to the user in a single ranked list that is ordered according to the computed scores of the data visualizations and the computed scores of the alternative data visualizations.

3. The method of claim 1, wherein the data visualization options are presented to the user in two ranked lists, a first ranked list comprising high scoring data visualizations, ordered according to corresponding computed scores, and a second ranked list comprising high scoring alternative data visualizations, ordered according to corresponding computed scores.

4. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by including an additional data field from the set of data.

5. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by removing a user-selected data field.

6. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically narrower than the first user-selected data field.

7. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically broader than the first user-selected data field.

8. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by applying a filter to a user-selected data field, thereby limiting values of the user-selected data field to a first set of values, wherein the filter is not selected by the user.

9. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by removing a user-selected filter for a user-selected data field.

10. The method of claim 1, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by modifying a user-selected filter for a data field, thereby altering values retrieved for the data field.

11. The method of claim 1, further comprising:

receiving user selection from the presented data visualization options; and

displaying a data visualization on the computing device corresponding to the user-selected option.

12. A computer system for ranking data visualizations, comprising:

one or more processors;

memory; and

one or more programs stored in the memory for execution by the one or more processors, the one or more programs comprising instructions for;

receiving user selection of a set of data fields from a set of data;

identifying a plurality of data visualizations that use each data field in the user-selected set of data fields;

automatically forming a plurality of modified sets of data fields, each differing from the user-selected set by a limited sequence of at most two atomic operations, wherein each of the atomic operations is selected from the group consisting of;

removing a single data field from the user-selected set;

adding a single data field to the user-selected set;

replacing a user-selected data field with a hierarchically narrower data field from the set of data;

replacing a user-selected data field with a hierarchically broader data field from the set of data;

adding a filter to a data field that limits values retrieved to a specified subset of values;

removing a user-selected filter from a data field so that there is no limit on values retrieved for the data field; and

modifying a filter for a data field, thereby altering values retrieved for the data field;

identifying a plurality of respective alternative data visualizations, each respective alternative data visualization using each data field in a respective one of the modified sets of data fields;

for each of the data visualizations and each of the alternative data visualizations, computing a score based on a set of ranking criteria, wherein at least one ranking criterion used to compute each score is based on patterns of data values of one or more of the data fields in the set of data; and

presenting data visualization options to the user, wherein the presented options correspond to high scoring data visualizations and high scoring alternative data visualizations.

13. The computer system of claim 12, wherein the data visualization options are presented to the user in a single ranked list that is ordered according to the computed scores of the data visualizations and the computed scores of the alternative data visualizations.

14. The computer system of claim 12, wherein the data visualization options are presented to the user in two ranked lists, a first ranked list comprising high scoring data visualizations, ordered according to corresponding computed scores, and a second ranked list comprising high scoring alternative data visualizations, ordered according to corresponding computed scores.

15. The computer system of claim 12, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically narrower than the first user-selected data field.

16. The computer system of claim 12, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically broader than the first user-selected data field.

17. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs comprising instructions for:

receiving user selection of a set of data fields from a set of data;

identifying a plurality of data visualizations that use each data field in the user-selected set of data fields;

automatically forming a plurality of modified sets of data fields, each differing from the user-selected set by a limited sequence of at most two atomic operations, wherein each of the atomic operations is selected from the group consisting of;

removing a single data field from the user-selected set;

adding a single data field to the user-selected set;

replacing a user-selected data field with a hierarchically narrower data field from the set of data;

replacing a user-selected data field with a hierarchically broader data field from the set of data;

adding a filter to a data field that limits values retrieved to a specified subset of values;

removing a user-selected filter from a data field so that there is no limit on values retrieved for the data field; and

modifying a filter for a data field, thereby altering values retrieved for the data field;

identifying a plurality of respective alternative data visualizations, each respective alternative data visualization using each data field in a respective one of the modified sets of data fields;

for each of the data visualizations and each of the alternative data visualizations, computing a score based on a set of ranking criteria, wherein at least one ranking criterion used to compute each score is based on patterns of data values of one or more of the data fields in the set of data; and

presenting data visualization options to the user, wherein the presented options correspond to high scoring data visualizations and high scoring alternative data visualizations.

18. The computer readable storage medium of claim 17, wherein the data visualization options are presented to the user in two ranked lists, a first ranked list comprising high scoring data visualizations, ordered according to corresponding computed scores, and a second ranked list comprising high scoring alternative data visualizations, ordered according to corresponding computed scores.

19. The computer readable storage medium of claim 17, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically narrower than the first user-selected data field.

20. The computer readable storage medium of claim 17, wherein at least one of the alternative data visualizations is based on a modified set of data fields that differs from the user-selected set of data fields by replacing a first user-selected data field with a different data field that is hierarchically broader than the first user-selected data field.