Computer systems and methods for automatically viewing multidimensional databases

• US 8,099,674 B2
• Filed: 09/09/2005
• Issued: 01/17/2012
• Est. Priority Date: 09/09/2005
• Status: Active Grant

• Current Assignee: Tableau Software Incorporated (Salesforce.com, Inc.)
• Original Assignee: Tableau Software LLC (Salesforce.com, Inc.)
• Inventors: Mackinlay, Jock Douglas, Stolte, Christopher Richard, Hanrahan, Patrick
• Primary Examiner(s): Ke, Simon
• Assistant Examiner(s): Stitt, Erik
• Application Number:
  US11/223,658
• Publication Number:
  US 20070061611A1
• Time in Patent Office: 2,321 Days
• Field of Search: 715/764, 715/215, 715/212, 715/700, 715/810, 705/38
• US Class Current: 715/764
• 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

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.

Claims

1. A computer implemented method for displaying a graphical representation of a dataset, comprising:

at a computer having one or more processors and memory storing programs executed by the one or more processors;

displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

receiving a user selection of at least a subset of the multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type; and

in response to the user selection and the user ordering,

forming a plurality of alternative views using the dataset based on the user ordering of the user-selected terms;

determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system;

selecting from among the plurality of alternative views a resulting view for displaying the dataset based on comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

displaying the dataset or a transformation of the dataset in the data visualization region according to the resulting view.

2. The computer implemented method of claim 1, wherein the selecting step further comprises:

with no further user instruction;

choosing one or more rules that are associated with adding the user selected fields; and

applying the one or more rules to determine the resulting view'"'"'s view type.

3. The computer implemented method of claim 2, further comprising, before the choosing step:

determining whether a first view exists;

wherein the one or more rules selected is also based upon the first view, if the first view is determined to exist.

4. The computer implemented method of claim 1, wherein the dataset is a database.

5. The computer implemented method of claim 4, wherein the database is remote.

6. The computer implemented method of claim 4, wherein the database is a relational database.

7. The computer implemented method of claim 4, wherein the database is a multidimensional database.

8. The computer implemented method of claim 4, wherein the database contains semantic extractions of another database.

9. The computer implemented method of claim 1, wherein the dataset is retrieved from a remote database.

10. The computer implemented method of claim 2, wherein the rules are predetermined.

11. The computer implemented method of claim 2, wherein the rules relate to user preference.

12. The computer implemented method of claim 2, wherein the rules relate to user usage.

13. The computer implemented method of claim 1, the selecting step further comprising:

computing the cardinalities of all the fields in the resulting view.

14. The computer implemented method of claim 2, wherein the rules relate to the cardinalities of all the fields in the resulting view.

15. The computer implemented method of claim 1, the selecting step further comprising:

computing the functional dependencies of all the fields in the resulting view, using an algorithm.

16. The computer implemented method of claim 2, wherein the rules relate to the functional dependency of all the fields in the resulting view.

17. The computer implemented method of claim 1, the displaying of the dataset step further comprising:

choosing a mark for the resulting view; and

rendering the dataset according to the mark.

18. The computer implemented method of claim 1, wherein the receiving step is accomplished when the user drags and drops a representation of a field.

19. The computer implemented method of claim 1, wherein the receiving step is accomplished when the user double clicks a representation of a field.

20. The computer implemented method of claim 1, wherein the receiving step is accomplished when the user right clicks a representation of a field and selects an option to drop or add the field.

21. The computer implemented method of claim 1, wherein the receiving step is accomplished when the user inputs text to designate the plurality of user selected fields and their order.

22. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a text table when the resulting view'"'"'s first field is of the dimension data type.

23. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a bar chart when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has no field of the date dimension data type.

24. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a line when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has at least one field of the date dimension data type.

25. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a discrete line when the resulting view'"'"'s first field is of the date dimension data type, and the resulting view'"'"'s second field is of the measure data type.

26. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a continuous line when the resulting view'"'"'s first field is of the continuous dimension data type, and the resulting view'"'"'s second field is of the measure data type.

27. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a scatter plot when the resulting view'"'"'s first and second fields are of the measure data type, and the resulting view'"'"'s subsequent fields are of the dimension data type.

28. The computer implemented method of claim 2, wherein the one or more rules state that the resulting view is a scatter matrix when the resulting view'"'"'s first, second, and a subsequent field is of the measure data type.

29. The computer implemented method of claim 17, wherein when the resulting view is a text table, the mark is text.

30. The computer implemented method of claim 17, wherein when the resulting view is a heat map, the mark is a square.

31. The computer implemented method of claim 17, wherein when the resulting view is a bar chart, the mark is a bar.

32. The computer implemented method of claim 17, wherein when the resulting view is a line graph, the mark is a line segment.

33. The computer implemented method of claim 17, wherein when the resulting view is a circle chart, the mark is a circle.

34. The computer implemented method of claim 17, wherein when the resulting view is a Gantt plot, the mark is a bar.

35. The computer implemented method of claim 17, wherein when the resulting view is a scatter plot, the mark is a point or shape.

36. The computer implemented method of claim 1, wherein the selecting step uses heuristics.

201. The computer implemented method of claim 1, the selecting step further comprising:

displaying the plurality of alternative views; and

receiving a user selection of one of the plurality of alternative views as the resulting view.

37. A computer implemented method for displaying a graphical representation of a dataset with a plurality of tuples, comprising:

at a computer having one or more processors and memory storing programs executed by the one or more processors;

displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

receiving a user instruction for generating a graphical representation of the dataset, wherein the user instruction includes a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type; and

in response to the user selection and the user ordering,

forming a plurality of alternative views based on the user ordering of the user-selected terms, each alternative view showing all tuples, or a transformation of all tuples, in the dataset;

determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system;

selecting a resulting view from the plurality of rated alternative views, based upon a user selected option and comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

displaying the dataset or a transformation of the dataset in the data visualization region according to the resulting view.

38. The computer implemented method of claim 37, wherein the dataset is a database.

39. The computer implemented method of claim 38, wherein the database is remote.

40. The computer implemented method of claim 38, wherein the database is a relational database.

41. The computer implemented method of claim 38, wherein the database is a multidimensional database.

42. The computer implemented method of claim 38, wherein the database contains semantic extractions of another database.

43. The computer implemented method of claim 37, wherein the dataset is retrieved from a remote database.

44. The computer implemented method of claim 37, wherein the forming step further comprises:

computing the cardinality of the fields in the plurality of tuples.

45. The computer implemented method of claim 37, wherein the forming step further comprises:

computing the functional dependency on the plurality of tuples, using an algorithm.

46. The computer implemented method of claim 37, wherein, when the user selected option is a first option, the selecting step further comprises:

ranking the plurality of alternative views according to a rating system; and

assigning the resulting view as the highest ranked alternative view.

47. The computer implemented method of claim 46, wherein the rating system is predetermined.

48. The computer implemented method of claim 46, wherein the rating system relates to user preference.

49. The computer implemented method of claim 46, wherein the rating system relates to user usage.

50. The computer implemented method of claim 37, wherein, when the user selected option is a second option, the selecting step further comprises:

displaying a list of the alternative views;

receiving the user'"'"'s selection of an alternative view; and

assigning the resulting view as the alternative view selected by the user.

51. The computer implemented method of claim 37, wherein the forming step further comprises:

determining the applicable view types according to the dataset'"'"'s data types;

identifying the associated mark for each applicable view type; and

forming an alternative view for each applicable view type according to the associated mark.

52. The computer implemented method of claim 51, wherein the determining step is accomplished using a set of criteria.

53. The computer implemented method of claim 52, wherein the set of criteria is predetermined.

54. The computer implemented method of claim 52, wherein the set of criteria relates to user preference.

55. The computer implemented method of claim 52, wherein the set of criteria relates to user usage.

56. The computer implemented method of claim 52, wherein an applicable view type is a text table and the associated mark for such an applicable view type is text, if all the data contained in the dataset are aggregated according to their fields, and no data type is independently quantitative.

57. The computer implemented method of claim 52, wherein an applicable view type is a heat map and the associated mark for such an applicable view type is a colored shape, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data type is independently quantitative.

58. The computer implemented method of claim 52, wherein an applicable view type is a Gantt plot and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, less than three data types are dependently quantitative, and at least one data type is either independently quantitative or a date.

59. The computer implemented method of claim 52, wherein an applicable view type is a side-by-side bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, at least one data type is dependently quantitative, and no data type is independently quantitative.

60. The computer implemented method of claim 52, wherein an applicable view type is a stacked bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, no more than two data types are ordinal, and no data types are independently quantitative.

61. The computer implemented method of claim 52, wherein an applicable view type is a measure bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data types are independently quantitative.

62. The computer implemented method of claim 52, wherein an applicable view type is a dimension line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, at least one data type is a date, and no data types are independently quantitative.

63. The computer implemented method of claim 52, wherein an applicable view type is a measure line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, and at least one data type is either independently quantitative or a date.

64. The computer implemented method of claim 52, wherein an applicable view type is a circle chart and the associated mark for such an applicable view type is a circle, if at least one data type is ordinal, at least one data type is dependently quantitative, and no data type can be aggregated or is independently quantitative.

65. The computer implemented method of claim 52, wherein an applicable view type is a single scatter chart and the associated mark for such an applicable view type is a point, if the data contained in the dataset included between two to four dependently quantitative data types, and no independently quantitative data type.

66. The computer implemented method of claim 52, wherein an applicable view type is a matrix scatter chart and the associated mark for such an applicable view type is a point, if the dataset included at least three dependently quantitative data types, and no independently quantitative data type.

67. The computer implemented method of claim 52, wherein an applicable view type is a histogram and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, and no data types are independently quantitative.

68. The computer implemented method of claim 37, wherein the selecting step uses heuristics.

202. The computer implemented method of claim 37, the selecting step further comprising:

displaying the plurality of alternative views; and

receiving a user selection of one of the plurality of alternative views as the resulting view.

69. A computer program product including a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions that are executed to display a graphical representation of a dataset, the instructions comprising:

a module for displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

a field receiver for receiving a user selection of at least a subset of the multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, wherein each user-selected term has an associated data type;

a resulting view selector for, in response to the user selection and the user ordering,

forming a plurality of alternative views using the dataset based on the user ordering of the user-selected terms;

determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system;

selecting a resulting view from the plurality of alternative views for displaying the dataset based on comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

a dataset displayer for displaying the dataset or a transformation of the dataset according to the resulting view in the data visualization region.

70. The computer program product of claim 69, wherein the resulting view selector further comprises:

with no further user instruction;

a rule chooser for choosing one or more rules that are associated with adding the user selected fields; and

a rule applier for applying the one or more rules to determine the resulting view'"'"'s view type.

71. The computer program product of claim 70, further comprising:

a view determiner for determining whether a first view exists;

wherein the one or more rules selected is also based upon the first view, if the first view is determined to exist.

72. The computer program product of claim 69, wherein the dataset is a database.

73. The computer program product of claim 72, wherein the database is remote.

74. The computer program product of claim 72, wherein the database is a relational database.

75. The computer program product of claim 72, wherein the database is a multidimensional database.

76. The computer program product of claim 72, wherein the database contains semantic extractions of another database.

77. The computer program product of claim 69, wherein the dataset is retrieved from a remote database.

78. The computer program product of claim 70, wherein the rules are predetermined.

79. The computer program product of claim 70, wherein the rules relate to user preference.

80. The computer program product of claim 70, wherein the rules relate to user usage.

81. The computer program product of claim 69, the resulting view selector further comprising:

a cardinality computer computing the cardinalities of all the fields in the resulting view.

82. The computer program product of claim 70, wherein the rules relate to the cardinalities of all the fields in the resulting view.

83. The computer program product of claim 69, the resulting view selector further comprising:

a functional dependency computer for computing the functional dependencies of all the fields in the resulting view, using an algorithm.

84. The computer program product of claim 70, wherein the rules relate to the functional dependency of all the fields in the resulting view.

85. The computer program product of claim 69, the dataset displayer further comprising:

a mark chooser for choosing a mark for the resulting view; and

a dataset renderer for rendering the dataset according to the mark.

86. The computer program product of claim 69, wherein the field receiver allows the user to drag and drop a representation of a field.

87. The computer program product of claim 69, wherein the field receiver allows the user to double click a representation of a field.

88. The computer program product of claim 69, wherein the field receiver allows the user to right click a representation of a field and selects an option to drop or add the field.

89. The computer program product of claim 69, wherein the field receiver allows the user to designate the plurality of user selected fields and their order.

90. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a text table when the resulting view'"'"'s first field is of the dimension data type.

91. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a bar chart when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has no field of the date dimension data type.

92. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a line when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has at least one field of the date dimension data type.

93. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a discrete line when the resulting view'"'"'s first field is of the date dimension data type, and the resulting view'"'"'s second field is of the measure data type.

94. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a continuous line when the resulting view'"'"'s first field is of the continuous dimension data type, and the resulting view'"'"'s second field is of the measure data type.

95. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a scatter plot when the resulting view'"'"'s first and second fields are of the measure data type, and the resulting view'"'"'s subsequent fields are of the dimension data type.

96. The computer program product of claim 70, wherein the one or more rules state that the resulting view is a scatter matrix when the resulting view'"'"'s first, second, and a subsequent field is of the measure data type.

97. The computer program product of claim 85, wherein when the resulting view is a text table, the mark is text.

98. The computer program product of claim 85, wherein when the resulting view is a heat map, the mark is a square.

99. The computer program product of claim 85, wherein when the resulting view is a bar chart, the mark is a bar.

100. The computer program product of claim 85, wherein when the resulting view is a line graph, the mark is a line segment.

101. The computer program product of claim 85, wherein when the resulting view is a circle chart, the mark is a circle.

102. The computer program product of claim 85, wherein when the resulting view is a Gantt plot, the mark is a bar.

103. The computer program product of claim 85, wherein when the resulting view is a scatter plot, the mark is a point or shape.

104. The computer program product of claim 69, wherein the selecting step uses heuristics.

105. A computer program product including a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions that are executed to display a graphical representation of a dataset with a plurality of tuples, the instructions comprising:

a module for displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

an alternative view former for forming a plurality of alternative views in response to a user instruction for generating a graphical representation of the dataset, each alternative view showing all tuples, or a transformation of all tuples, in the dataset, wherein the user instruction includes a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type, and determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system, wherein the user instruction includes a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type;

a resulting view selector for selecting a resulting view from the plurality of rated alternative views in response to the user instruction, based upon a user selected option and comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

a dataset displayer for displaying the dataset or a transformation of the dataset in the data visualization region according to the resulting view in response to the user instruction.

106. The computer program product of claim 105, wherein the dataset is a database.

107. The computer program product of claim 106, wherein the database is remote.

108. The computer program product of claim 106, wherein the database is a relational database.

109. The computer program product of claim 106, wherein the database is a multidimensional database.

110. The computer program product of claim 106, wherein the database contains semantic extractions of another database.

111. The computer program product of claim 105, wherein the dataset is retrieved from a remote database.

112. The computer program product of claim 105, wherein the alternative view former further comprises:

a cardinality computer for computing the cardinality of the fields in the plurality of tuples.

113. The computer program product of claim 105, wherein the alternative view former further comprises:

a functional dependency computer for computing the functional dependency on the plurality of tuples, using an algorithm.

114. The computer program product of claim 105, wherein, when the user selected option is a first option, the resulting view selector further comprises:

an alternative view ranker for ranking the plurality of alternative views according to a rating system; and

a view assignor for assigning the resulting view as the highest ranked alternative view.

115. The computer program product of claim 114, wherein the rating system is predetermined.

116. The computer program product of claim 114, wherein the rating system relates to user preference.

117. The computer program product of claim 114, wherein the rating system relates to user usage.

118. The computer program product of claim 105, wherein, when the user selected option is a second option, the resulting view selector further comprises:

a list displayer for displaying a list of the alternative views;

a selection receiver for receiving the user'"'"'s selection of an alternative view; and

a view assignor for assigning the resulting view as the alternative view selected by the user.

119. The computer program product of claim 105, wherein the alternative view former forms an alternative view for each applicable view type according to an associated mark, the alternative view former further comprising:

a view type determiner for determining the applicable view types according to the dataset'"'"'s data types; and

a mark chooser for choosing the associated mark for each applicable view type.

120. The computer program product of claim 119, wherein the view type determiner uses a set of criteria.

121. The computer program product of claim 120, wherein the set of criteria is predetermined.

122. The computer program product of claim 120, wherein the set of criteria relates to user preference.

123. The computer program product of claim 120, wherein the set of criteria relates to user usage.

124. The computer program product of claim 120, wherein an applicable view type is a text table and the associated mark for such an applicable view type is text, if all the data contained in the dataset are aggregated according to their fields, and no data type is independently quantitative.

125. The computer program product of claim 120, wherein an applicable view type is a heat map and the associated mark for such an applicable view type is a colored shape, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data type is independently quantitative.

126. The computer program product of claim 120, wherein an applicable view type is a Gantt plot and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, less than three data types are dependently quantitative, and at least one data type is either independently quantitative or a date.

127. The computer program product of claim 120, wherein an applicable view type is a side-by-side bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, at least one data type is dependently quantitative, and no data type is independently quantitative.

128. The computer program product of claim 120, wherein an applicable view type is a stacked bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, no more than two data types are ordinal, and no data types are independently quantitative.

129. The computer program product of claim 120, wherein an applicable view type is a measure bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data types are independently quantitative.

130. The computer program product of claim 120, wherein an applicable view type is a dimension line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, at least one data type is a date, and no data types are independently quantitative.

131. The computer program product of claim 120, wherein an applicable view type is a measure line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, and at least one data type is either independently quantitative or a date.

132. The computer program product of claim 120, wherein an applicable view type is a circle chart and the associated mark for such an applicable view type is a circle, if at least one data type is ordinal, at least one data type is dependently quantitative, and no data type can be aggregated or is independently quantitative.

133. A computer system for automatically and visually displaying a graphical representation of a dataset, the computer system comprising:

a central processing unit;

a memory, coupled to the central processing unit, the memory storing;

the dataset;

a programming module comprising, comprising;

instructions for displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

instructions for receiving a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, wherein each field has an associated data type;

instructions for forming a plurality of alternative views using the dataset based on the user ordering of the user-selected terms;

instructions for determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system and selecting a resulting view from the plurality of alternative views for displaying the dataset based on comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

instructions for displaying the dataset or a transformation of the dataset in the data visualization region according to the resulting view.

134. The computer system of claim 133, wherein the instructions for selecting further comprises:

with no further user instruction;

instructions for choosing one or more rules that are associated with adding the user selected fields; and

instructions for applying the one or more rules to determine the resulting view'"'"'s view type.

135. The computer system of claim 134, further comprising, before the instructions for choosing:

instructions for determining whether a first view exists;

wherein the one or more rules selected is also based upon the first view, if the first view is determined to exist.

136. The computer system of claim 133, wherein the dataset is a database.

137. The computer system of claim 136, wherein the database is remote.

138. The computer system of claim 136, wherein the database is a relational database.

139. The computer system of claim 136, wherein the database is a multidimensional database.

140. The computer system of claim 136, wherein the database contains semantic extractions of another database.

141. The computer system of claim 133, wherein the dataset is retrieved from a remote database.

142. The computer system of claim 134, wherein the rules are predetermined.

143. The computer system of claim 134, wherein the rules relate to user preference.

144. The computer system of claim 134, wherein the rules relate to user usage.

145. The computer system of claim 133, the instructions for selecting further comprising:

instructions for computing the cardinalities of all the fields in the resulting view.

146. The computer system of claim 134, wherein the rules relate to the cardinalities of all the fields in the resulting view.

147. The computer system of claim 133, the instructions for selecting further comprising:

instructions for computing the functional dependencies of all the fields in the resulting view, using an algorithm.

148. The computer system of claim 134, wherein the rules relate to the functional dependency of all the fields in the resulting view.

149. The computer system of claim 133, the instructions for displaying the dataset further comprising:

instructions for choosing a mark for the resulting view; and

instructions for rendering the dataset according to the mark.

150. The computer system of claim 133, wherein the instructions for receiving is accomplished when the user drags and drops a representation of a field.

151. The computer system of claim 133, wherein the instructions for receiving is accomplished when the user double clicks a representation of a field.

152. The computer system of claim 133, wherein the instructions for receiving is accomplished when the user right clicks a representation of a field and selects an option to drop or add the field.

153. The computer system of claim 133, wherein the instructions for receiving is accomplished when the user inputs text to designate the plurality of user selected fields and their order.

154. The computer system of claim 134, wherein the one or more rules state that the resulting view is a text table when the resulting view'"'"'s first field is of the dimension data type.

155. The computer system of claim 134, wherein the one or more rules state that the resulting view is a bar chart when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has no field of the date dimension data type.

156. The computer system of claim 134, wherein the one or more rules state that the resulting view is a line when the resulting view'"'"'s first field is of the measure data type, the resulting view'"'"'s second field is of the dimension data type, and the resulting view has at least one field of the date dimension data type.

157. The computer system of claim 134, wherein the one or more rules state that the resulting view is a discrete line when the resulting view'"'"'s first field is of the date dimension data type, and the resulting view'"'"'s second field is of the measure data type.

158. The computer system of claim 134, wherein the one or more rules state that the resulting view is a continuous line when the resulting view'"'"'s first field is of the continuous dimension data type, and the resulting view'"'"'s second field is of the measure data type.

159. The computer system of claim 134, wherein the one or more rules state that the resulting view is a scatter plot when the resulting view'"'"'s first and second fields are of the measure data type, and the resulting view'"'"'s subsequent fields are of the dimension data type.

160. The computer system of claim 134, wherein the one or more rules state that the resulting view is a scatter matrix when the resulting view'"'"'s first, second, and a subsequent field is of the measure data type.

161. The computer system of claim 149, wherein when the resulting view is a text table, the mark is text.

162. The computer system of claim 149, wherein when the resulting view is a heat map, the mark is a square.

163. The computer system of claim 149, wherein when the resulting view is a bar chart, the mark is a bar.

164. The computer system of claim 149, wherein when the resulting view is a line graph, the mark is a line segment.

165. The computer system of claim 149, wherein when the resulting view is a circle chart, the mark is a circle.

166. The computer system of claim 149, wherein when the resulting view is a Gantt plot, the mark is a bar.

167. The computer system of claim 149, wherein when the resulting view is a scatter plot, the mark is a point or shape.

168. The computer system of claim 133, wherein the selecting step uses heuristics.

169. A computer system for automatically and visually displaying a graphical representation of a dataset with a plurality of tuples, the computer system comprising:

a central processing unit;

a memory, coupled to the central processing unit, the memory storing;

the dataset;

a programming module comprising;

instructions for displaying a graphical user interface window including a schema display region and a data visualization region, wherein the schema display region includes multiple terms corresponding to a plurality of fields of the dataset, wherein each field defines a respective category of the dataset;

instructions for forming a plurality of alternative views in response to a user instruction for generating a graphical representation of the dataset, each alternative view showing all tuples, or a transformation of all tuples, in the dataset, wherein the user instruction includes a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type, and determining a rank for each of the plurality of alternative views based on the user-specified order and the associated data types of the user-selected terms and a rating system, wherein the user instruction includes a user selection of at least a subset of multiple terms in the schema display region and a user ordering of the user-selected terms in the data visualization region, each of the user-selected terms having an associated data type;

instructions for selecting a resulting view from the plurality of rated alternative views in response to the user instruction, based upon a user selected option and comparing the rank of the resulting view with the rank of at least another view of the plurality of alternative views; and

instructions for displaying the dataset or a transformation of the dataset in the data visualization region according to the resulting view in response to the user instruction.

170. The computer system of claim 169, wherein the dataset is a database.

171. The computer system of claim 170, wherein the database is remote.

172. The computer system of claim 170, wherein the database is a relational database.

173. The computer system of claim 170, wherein the database is a multidimensional database.

174. The computer system of claim 170, wherein the database contains semantic extractions of another database.

175. The computer system of claim 169, wherein the dataset is retrieved from a remote database.

176. The computer system of claim 169, wherein the instructions for forming further comprises:

instructions for computing the cardinality of the fields in the plurality of tuples.

177. The computer system of claim 169, wherein the instructions for forming further comprises:

instructions for computing the functional dependency on the plurality of tuples, using an algorithm.

178. The computer system of claim 169, wherein, when the user selected option is a first option, the instructions for selecting further comprises:

instructions for ranking the plurality of alternative views according to a rating system; and

instructions for assigning the resulting view as the highest ranked alternative view.

179. The computer system of claim 178, wherein the rating system is predetermined.

180. The computer system of claim 178, wherein the rating system relates to user preference.

181. The computer system of claim 178, wherein the rating system relates to user usage.

182. The computer system of claim 169, wherein, when the user selected option is a second option, the instructions for selecting further comprises:

instructions for displaying a list of the alternative views;

instructions for receiving the user'"'"'s selection of an alternative view; and

instructions for assigning the resulting view as the alternative view selected by the user.

183. The computer system of claim 169, wherein the instructions for forming further comprises:

instructions for determining the applicable view types according to the dataset'"'"'s data types;

instructions for identifying the associated mark for each applicable view type; and

instructions for forming an alternative view for each applicable view type according to the associated mark.

184. The computer system of claim 183, wherein the instructions for determining is accomplished using a set of criteria.

185. The computer system of claim 184, wherein the set of criteria is predetermined.

186. The computer system of claim 184, wherein the set of criteria relates to user preference.

187. The computer system of claim 184, wherein the set of criteria relates to user usage.

188. The computer system of claim 184, wherein an applicable view type is a text table and the associated mark for such an applicable view type is text, if all the data contained in the dataset are aggregated according to their fields, and no data type is independently quantitative.

189. The computer system of claim 184, wherein an applicable view type is a heat map and the associated mark for such an applicable view type is a colored shape, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data type is independently quantitative.

190. The computer system of claim 184, wherein an applicable view type is a Gantt plot and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, less than three data types are dependently quantitative, and at least one data type is either independently quantitative or a date.

191. The computer system of claim 184, wherein an applicable view type is a side-by-side bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is ordinal, at least one data type is dependently quantitative, and no data type is independently quantitative.

192. The computer system of claim 184, wherein an applicable view type is a stacked bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, no more than two data types are ordinal, and no data types are independently quantitative.

193. The computer system of claim 184, wherein an applicable view type is a measure bar chart and the associated mark for such an applicable view type is a bar, if all the data contained in dataset are aggregated according to their fields, at least one data type is ordinal, no more than two data types are dependently quantitative, and no data types are independently quantitative.

194. The computer system of claim 184, wherein an applicable view type is a dimension line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, at least one data type is a date, and no data types are independently quantitative.

195. The computer system of claim 184, wherein an applicable view type is a measure line graph and the associated mark for such an applicable view type is a line, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, and at least one data type is either independently quantitative or a date.

196. The computer system of claim 184, wherein an applicable view type is a circle chart and the associated mark for such an applicable view type is a circle, if at least one data type is ordinal, at least one data type is dependently quantitative, and no data type can be aggregated or is independently quantitative.

197. The computer system of claim 184, wherein an applicable view type is a single scatter chart and the associated mark for such an applicable view type is a point, if the data contained in the dataset included between two to four dependently quantitative data types, and no independently quantitative data type.

198. The computer system of claim 184, wherein an applicable view type is a matrix scatter chart and the associated mark for such an applicable view type is a point, if the dataset included at least three dependently quantitative data types, and no independently quantitative data type.

199. The computer system of claim 184, wherein an applicable view type is a histogram and the associated mark for such an applicable view type is a bar, if all the data contained in the dataset are aggregated according to their fields, at least one data type is dependently quantitative, and no data types are independently quantitative.

200. The computer system of claim 169, wherein the selecting step uses heuristics.