Table-based method and system for generating visualization construction process

Abstract

The present invention relates to a table-based method and system for generating a visualization construction process. The method comprises: on the basis of a visualization definition inputted by a user, establishing correspondences between visualization primitives and table cells, determining a part requiring table cell mapping, and performing table visualization mapping one by one on the basis of attribute values and primitives that require mapping; recursively grouping data items on the basis of data attributes; in each data group, on the basis of a user-defined attribute alignment mode and data item sorting mode, arranging primitives corresponding to the data items; performing data aggregation on the data items within the data groups on the basis of a user-defined data aggregation mode, and performing numerical attribute value mapping on the data items within the data groups; and generating an animation on the basis of the above operation sequence. By adopting the method disclosed in the present invention, for different visualizations, the intermediate steps of operations and dynamic transformations starting from the table are automatically computed on the basis of the final visualization form, which can help users to understand visualization mapping and data transformation processes.

Description

A table-based visual construction process generation method and system Technical Field

[0001] The present invention belongs to the field of visualization, and in particular relates to a table-based visualization construction process generation method and system. Background Art

[0002] In today's ubiquitous world of data, the prevalence of visualization helps data analysts quickly uncover hidden patterns within the data. However, with the continuous development of visualization technology, visualization formats and interactions are becoming increasingly complex, and multi-view visualizations complicate understanding, leaving beginners with a steep learning curve. Furthermore, many data processing users, lacking familiarity with visualization and visual analysis tools, choose to use spreadsheets for data analysis and meaning building.

[0003] Existing work to assist with visual understanding primarily focuses on using simple visualizations to facilitate understanding of more complex visualizations related to their form. This work lacks a unified framework, requiring individual design for different visualizations. Other work uses visual animations to help users understand the data transformation process, but these efforts focus solely on simple statistical charts and lack understanding of complex visual mapping methods. Consequently, the process of transforming and visually mapping raw data to generate the final visualization is presented in a tabular format, hindering understanding of complex visualizations.

[0004] Summary of the Invention

[0005] In response to the defects in the prior art, the purpose of the present invention is to provide a table-based visualization construction process generation method and system. For specific types of visualization, the process of data conversion and visual mapping from raw data to generate the final visualization can be automatically displayed to help users understand the visualization process and mapping method.

[0006] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0007] In a first aspect, a table-based visualization construction process generation method is provided, the method comprising the following steps:

[0008] S1. According to the visualization definition input by the user, the visualization primitives are matched with the cells of the table, the parts that need to be mapped to the table cells are determined, and the table visualization mapping is performed one by one according to the attribute values ​​and primitives that need to be mapped;

[0009] S2. recursively grouping the data items according to an arrangement determined by the visualization definition input by the user to form a plurality of data groups;

[0010] S3. Arrange the corresponding primitives of the data items within each data group according to the user-defined attribute alignment and data item sorting method, and place the corresponding data items at the front of the unsorted data items and mark them as sorted. The sorting process is displayed through an animation of the data items moving;

[0011] S4. Determine the data aggregation method based on the user-defined visualization, aggregate the data items within the data group, and map the numerical attribute values ​​of the data items within the data group;

[0012] S5. Generate an animation according to the operation sequence in steps S1-S4 to demonstrate the visualization construction process.

[0013] Furthermore, the visualization definition input by the user in step S1 includes the data uploaded by the user, the visualization type selected, and the data attributes specified for mapping different visual channels.

[0014] Furthermore, according to the visualization type in the visualization definition, it is analyzed that the operations in the visualization generation process include mapping operations, layout operations, and data transformation operations.

[0015] Furthermore, in step S2, the data items are grouped according to data attributes.

[0016] Furthermore, grouping the data items in step S2 includes the following sub-steps:

[0017] S21. Sort and merge attributes within existing visualizations based on data attributes.

[0018] S22. Determine the moving direction of different data groups according to whether the coordinate axis of the data attribute mapping is horizontal or vertical.

[0019] Furthermore, in step S3, by decomposing the ordering of data items and the alignment of data attributes, the graphic elements corresponding to the data items are ordered and the data attributes are aligned within each data group, so as to define the visualization form within the data group.

[0020] Further, step S4 includes calculating the size of the aggregate value within each data group, determining the mapping relationship between the attribute value and the display size based on the aggregate value range, number of groups and screen pixels of all data groups; and recalculating the position and size of the data item based on the aggregate value, and displaying the recalculated data item through dynamic change and movement.

[0021] Further, step S4 includes adjusting the sizes of different table cells according to the defined attribute alignment; encoding different channels of the table cells according to the mapping specified by the visualization definition; and arranging the data groups into a matrix, where the final size of each row / column data group is determined by the maximum number of rows / columns of the row / column data group.

[0022] Furthermore, the animation generated in step S5 includes a view for uploading data, a view for displaying the number of attribute categories or the distribution of values, a visualization selection view, an animation path view, an animation main view, and an operation customization view.

[0023] In the second aspect, a table-based visualization construction process generation system adopts a table-based visualization construction process generation method as described in the first aspect of the present invention and any optional embodiment thereof, and automatically generates animations to assist users in understanding the visualization construction process based on the data uploaded by the user, the selected visualization type, and the specified data attributes mapping different visual channels.

[0024] The beneficial technical effect of the present invention is that a table-based visualization construction process generation method and system disclosed in the present invention are used to assist users in understanding the visualization generation process, and automatically generate an animation of the visualization construction process based on the data input by the user, the selected visualization type and the specified data attributes of the mapping of different visual channels. The animation displays the visualization construction process based on the table, and uses the user's familiarity with the table to help the user understand data transformation and visualization mapping, thereby understanding complex forms of visualization. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] FIG1 is a flow chart of a table-based visualization construction process generation method disclosed in Embodiment 1 of the present invention;

[0026] FIG2 is an animation showing a visualization construction process generated by a table-based visualization construction process generation system disclosed in the second embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0028] Example 1

[0029] As shown in FIG1 , an embodiment of the present invention provides a table-based visualization construction process generation method, the method comprising the following steps:

[0030] S1. According to the visualization definition input by the user, the visualization primitives are matched with the cells of the table, and the parts that need to be mapped to the table cells are determined. According to the attribute values ​​and primitives that need to be mapped, the table visualization mapping is performed one by one.

[0031] The visualization definition entered by the user includes the data uploaded by the user, the selected visualization type, and the specified data attributes that map to different visual channels.

[0032] Table-based visualizations treat each data item as a complex primitive, consisting of a primitive column and multiple attribute columns, each of which can be mapped. Initially, a table is treated as a specialized visualization where the primitive columns are empty and the attribute columns use text channels to map the raw data. For cell mapping, mapping is performed first on the corresponding attribute columns, followed by mapping on the primitive columns, with the attribute columns hidden.

[0033] The visualization type in the visualization definition entered by the user can be parsed to reveal the operations involved in the visualization generation process, including mapping operations, layout operations, and data transformation operations. Mapping operations map attributes to the color, border, size, or embedded graphics of table cells or cell groups. Layout operations involve swapping the positions of different data items, including sorting and changing the layout of data groups, such as grouping and horizontal distribution. Data transformation operations include data aggregation operations, such as counting, summing, and averaging, and attribute transformation operations, such as binning and normalization.

[0034] S2. Recursively group the data items according to the arrangement determined by the visualization definition input by the user to form multiple data groups.

[0035] Data items are often grouped based on different attribute values. For example, in a bar chart, the attribute that defines the horizontal axis is used to group data items into multiple groups. When grouping, the attribute value is first used to sort and merge attributes within the existing visualization. The direction of movement of the different data groups is determined by whether the axis to which the attribute is mapped is horizontal or vertical.

[0036] S3. Arrange the corresponding graphics elements of each data group according to the user-defined attribute alignment and data item sorting method, and place the corresponding data items at the front of the unsorted data items and mark them as sorted. The sorting process is displayed through the animation of the data items moving.

[0037] According to the different visualization types determined in the visualization definition input by the user, the data items within the data group are arranged differently. According to the visualization type input by the user, the sorting method of the data items and the alignment method of the data attributes within the data group are determined. By decomposing the sorting method of the data items and the alignment method of the data attributes, the graphics elements corresponding to the data items are sorted and the data attributes are aligned within each data group, so as to define the visualization form within the data group.

[0038] The data sets in the data group include two forms: data list and matrix, where (1) the data list contains multiple data items, each of which has a categorical attribute, an ordinal attribute, and a numerical attribute; (2) the matrix contains two categorical attributes and a numerical attribute corresponding to the categorical attribute value.

[0039] For example, for a bar chart, only a single column is displayed, and the data items are arranged in the original data order and aligned towards the bottom. For a tree visualization, the data items are arranged in the depth-first traversal order of the tree data, and the attributes are aligned according to the depth of the node. In the actual calculation, this arrangement and alignment corresponds to inserting all child nodes of the main search node into the sorted array of data items and aligning them according to the attributes of the parent and child nodes.

[0040] For matrix visualization, data items are sorted based on the value of one attribute, with items with the same value arranged in the same row. The other attribute is aligned based on the value of the attribute.

[0041] S4. Determine the data aggregation method based on the user-defined visualization, perform data aggregation on the data items within the data group, and map the numerical attribute values ​​of the data items within the data group.

[0042] Step S4 involves calculating the aggregate value size within each data group and determining the mapping relationship between attribute value and display size based on the aggregate value range, number of groups, and screen pixels of all data groups. Subsequently, the position and size of the data items are recalculated based on the aggregate value and displayed through dynamic change and movement.

[0043] Adjust the sizes of different table cells according to the defined attribute alignment; encode different channels of the table cells according to the mapping definition; arrange the data groups into a matrix, and the final size of each row / column data group is determined by the maximum number of rows / columns of the row / column data group.

[0044] S5. Generate an animation according to the operation sequence in steps S1-S4 to demonstrate the visualization construction process.

[0045] The generated animation includes views for uploaded data, views showing the number of attribute categories or value distribution, visualization selection views, animation path views, animation main views, and custom operation views.

[0046] Example 2

[0047] An embodiment of the present invention provides a table-based visualization construction process generation system, which adopts a table-based visualization construction process generation method as described in Example 1 of the present invention and any optional implementation manner thereof, and automatically generates animations to assist users in understanding the visualization construction process based on the data uploaded by the user, the selected visualization type, and the specified data attributes mapping different visual channels.

[0048] As shown in FIG2 , a table-based visualization construction process generation system disclosed in an embodiment of the present invention is used to generate an animation showing the visualization construction process, wherein FIGs. (1) to (4) are animations showing the visualization construction process of the mapping operation, FIGs. (5) to (7) are animations showing the visualization construction process of the layout operation, and FIGs. (8) to (9) are animations showing the visualization construction process of the data transformation operation.

[0049] The specific map (1) is an animation showing the visualization construction process of the color mapping operation: setting the background color of the cell and making the cell background change from transparent to opaque over time.

[0050] Figure (2) is an animation showing the visualization construction process of the length mapping operation: the cell width or height changes from the original length to the length after mapping the data over time.

[0051] Figure (3) is an animation showing the visualization construction process of the area mapping operation: embedding a primitive in a cell and making the area of ​​the primitive change from 0 to the area size after mapping the data over time.

[0052] Figure (4) is an animation showing the visualization construction process of the position mapping operation: embedding a primitive on the left side of the cell and moving the primitive to the position after mapping the data over time.

[0053] Figure (5) is an animation showing the visual construction process of the layout operation: moving the grouped data items so that they are arranged horizontally.

[0054] Figure (6) is an animation showing the visualization construction process of group operations: the specified attribute columns of data items in the same group are merged. During this process, the original cells change from opaque to transparent, while the merged cells change from transparent to opaque over time.

[0055] Figure (7) is an animation showing the visual construction process of the rotation operation: rotating the entire view 90 degrees around the specified center point.

[0056] Figure (8) is an animation showing the sum operation: the data item elements in each group are moved so that they are stacked horizontally or vertically, and then the elements in each group are moved so that the elements in adjacent groups are closely arranged.

[0057] Figure (9) is an animation showing the visualization construction process of the averaging operation: the length of the elements in each group is changed to the length corresponding to the average value over time, and then the elements in each group are moved to the top element of the group to overlap.

[0058] As can be seen from the above examples, the disclosed table-based visualization construction process generation method and system can automatically generate an animation that dynamically transforms a table into a visualization by recursively grouping raw data items, arranging primitives within the data group, and mapping the primitives according to the raw data table, based on user-entered data and visualization type. Based on a table familiar to the user, the visualization construction process is represented, and a unified table format and steps are used to automatically generate animations of the visualization construction process for different visualizations.

[0059] The method and system of the present invention are not limited to the embodiments described in the specific implementation manner. Those skilled in the art may derive other implementation manners based on the technical solution of the present invention, which also fall within the scope of the technical innovation of the present invention.

Claims

1. A method for generating a visualization construction process based on a table, the method comprises the following steps: S1. According to the visualization definition input by the user, correspond the visualization primitives with the cells of the table, determine the parts that need to be mapped to the table cells, and perform table visualization mapping one by one according to the attribute values and primitives to be mapped; S2. Recursively group the data items according to the arrangement method determined by the visualization definition input by the user to form multiple data groups; S3. Arrange the primitives corresponding to the data items within each data group according to the attribute alignment method and data item sorting method defined by the user, and arrange the corresponding data items at the forefront of the unsorted data items, mark them as sorted, and display the sorting process through the animation of data item movement; S4. Determine the data aggregation method according to the visualization defined by the user, aggregate the data items within the data group, and perform numerical attribute value mapping on the data items within the data group; S5. Generate an animation according to the operation sequence in steps S1 - S4 to display the visualization construction process.

2. A method for generating a visualization construction process based on a table as described in claim 1, characterized in that: the visualization definition input by the user in step S1 includes the data uploaded by the user, the selected visualization type, and the data attributes specifying the mapping of different visual channels.

3. A method for generating a visualization construction process based on a table as described in claim 2, characterized in that: parsing the operations in the visualization generation process according to the visualization type in the visualization definition includes mapping operations, layout operations, and data transformation operations.

4. A method for generating a visualization construction process based on a table as described in claim 3, characterized in that: group the data items according to the data attributes in step S2.

5. A method for generating a visualization construction process based on a table as described in claim 4, characterized in that, the grouping of data items in step S2 includes the following sub - steps: S21. Sort and merge attributes within the existing visualization according to the data attributes; S22. Determine the moving direction of different data groups according to whether the coordinate axes mapped by the data attributes are horizontal or vertical.

6. A method for generating a visualization construction process based on a table as described in claim 5, characterized in that: in step S3, by decomposing the sorting method of the data items and the alignment method of the data attributes, sort the primitives corresponding to the data items within each data group and align the data attributes to define the visualization form within the data group.

7. A method for generating a visualization construction process based on a table as described in claim 6, characterized in that: step S4 includes calculating the size of the aggregation value within each data group, determining the mapping relationship between the attribute value and the display size according to the aggregation value range, number of groups, and screen pixels of all data groups; and recalculating the position and size of the data items according to the aggregation value, and displaying the recalculated data items in a dynamically changing and moving manner.

8. A method for generating a visualization construction process based on a table as described in claim 7, characterized in that: Step S4 includes adjusting the sizes of different table cells according to the defined attribute alignment; encoding different channels of the table cells according to the mapping specified by the visualization definition; and arranging the data groups into a matrix, where the final size of each row / column data group is determined by the maximum number of rows / columns in that row / column data group.

9. A method for generating a visualization construction process based on a table according to claim 1, wherein: The animation generated in step S5 includes a view of the uploaded data, a view showing the number of attribute categories or the numerical distribution, a visualization selection view, an animation path view, an animation main view, and an operation customization view.

10. A system for generating a visualization construction process based on a table, wherein: It adopts a method for generating a visualization construction process based on a table according to any one of claims 1-9, and automatically generates an animation to assist the user in understanding the visualization construction process according to the data uploaded by the user, the selected visualization type, and the data attributes specifying different visual channels.

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