Visual display method and system for multi-dimensional data

Abstract

The invention discloses a visual display method and system for multi-dimensional data, and belongs to the technical field of data processing.The visual display method and system for the multi-dimensional data comprise the following specific steps that firstly, data obtaining and preprocessing are carried out, an original data set containing N dimensions is obtained, and data cleaning, standardization and normalization processing are carried out; and 2, correlation analysis: analyzing the relative importance of each dimension or the correlation strength between the dimensions by using a statistical method. According to the method, through dynamic selection of key dimensions and innovative non-fixed layout or combination of dimension reduction and original views, unnecessary visual element overlapping is remarkably reduced, the core dimension relation is focused, the layout better conforms to cognitive habits, visual coding is clearer, and a user can more quickly understand the structure and mode of high-dimensional data.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of data processing, and particularly relates to a multi-dimensional data visualization display method and system. BACKGROUND

[0002] Traditional two-dimensional / three-dimensional charts, such as scatter plots, line charts, and column charts, cannot effectively display data of more than three dimensions, resulting in information loss or non-intuitive expression. Common high-dimensional visualization techniques, such as parallel coordinate charts, radar charts, and scatter plot matrices, have limitations: when the number of dimensions increases, lines / points overlap excessively, making it difficult to identify patterns and outliers, users need to learn and understand complex visual encoding, interpretation efficiency is low, there is a lack of flexible, efficient dimension selection, filtering, scaling, correlation analysis, and other interactive methods, and high-dimensional information cannot be effectively displayed in limited screen space. The traditional method has limited ability to reveal complex nonlinear relationships or clustering structures between dimensions. SUMMARY

[0003] The technical problem to be solved by the application is to overcome the shortcomings of the prior art and provide a multi-dimensional data visualization display method and system.

[0004] The technical solution adopted to solve the above technical problems is as follows: Step one: data acquisition and preprocessing, acquiring an original data set containing N dimensions, and performing data cleaning, standardization, and normalization processing; Step two: correlation analysis, using statistical methods to analyze the relative importance of each dimension or the correlation strength between dimensions; Step three: core visualization layout generation, based on the analysis results of step two, using a dynamic dimension axis layout; Step four: visual encoding, assigning visual properties to data points, lines, and surfaces for encoding multiple additional dimension information and data point attributes; Step five: interactive mechanism implementation, providing a rich user interaction interface; Step six: view rendering, rendering the processed data and layout information to a display device in combination with visual encoding and interactive state.

[0005] Through the above technical solution, by dynamically selecting key dimensions, innovating non-fixed layouts, or combining dimension reduction with original views, unnecessary visual element overlap is significantly reduced, core dimension relationships are focused on, layouts are more consistent with cognitive habits, visual encoding is clearer, and users can more quickly understand the structure and patterns of high-dimensional data.

[0006] Further, the dynamic dimension axis dynamically selects, sorts and layouts the K most key or most relevant dimension axes according to the current analysis focus and user interaction, K is less than N, and arranges the K most key or most relevant dimension axes in a non-orthogonal and non-parallel manner on a two-dimensional plane to form a focused layout.

[0007] Through the above technical solution, the complex relationship between dimensions, the clustering structure of data and the nonlinear mode can be more intuitively displayed.

[0008] Further, the user interaction interface includes dimension selection, dimension filtering, dimension sorting, weight adjustment, dynamic query, dimension relationship exploration and view linkage.

[0009] Through the above technical solution, the user can be conveniently operated, and the user can actively explore data.

[0010] Further, the system comprises a data acquisition module, a data preprocessing module, a dimension analysis module, a visualization layout engine module, a visual coding module, an interaction processing module, a view rendering module and a storage module, the data acquisition module is responsible for acquiring original data, the data preprocessing module is responsible for cleaning, standardizing and normalizing the collected data, and the visualization layout engine module is responsible for mapping high-dimensional data to a two-dimensional space layout.

[0011] Further, the visual coding module is responsible for assigning visual properties to data according to analysis results, and the interaction processing module is responsible for dynamically updating parameters of the layout engine and the visual coding module and triggering view redrawing in response to user interaction.

[0012] Through the above technical solution, the corresponding view can be displayed according to the user demand.

[0013] Further, the view rendering module is responsible for drawing the final visualization result on the screen, and the storage module is used to store original data, processed data, configuration parameters and user interaction history.

[0014] Through the above technical solution, the data source can be clearly determined, and the user can be facilitated to find and process.

[0015] Further, the visualization layout engine module determines K target dimensions from the N dimensions based on a preset rule, K is an integer greater than or equal to 2 and less than N, determines a non-orthogonal and non-parallel dynamic layout position and direction of a visualization axis corresponding to the K target dimensions in a two-dimensional display space according to an association relationship between the K target dimensions, maps a value of each data point in the K target dimensions of the original data set to a corresponding visualization axis of the dynamic layout, and connects to form a visualization representation of each data point.

[0016] By the technical solution, the original information of key dimensions is reserved while the global structure is displayed, and data loss is less.

[0017] The present application has the following advantages: the present application significantly reduces unnecessary visual element overlap, focuses on core dimension relationships, and makes layout more consistent with cognitive habits and visual coding clearer, so that users can more quickly understand the structure and patterns of high-dimensional data by dynamically selecting key dimensions, innovative non-fixed layouts, or combining dimension reduction and original views. By providing powerful dimension control, focus, filtering, and linkage interaction functions, the present application supports users to actively explore data. Meanwhile, the present application can more intuitively display complex relationships between dimensions, clustering structures of data, and nonlinear patterns. The present application retains the original information of key dimensions while displaying the global structure. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a method flowchart of the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0020] As shown in Figure 1 , the multi-dimensional data visualization display method and system of the present embodiment includes the following specific steps: Step one: data acquisition and preprocessing, acquiring an original data set containing N dimensions, and performing data cleaning, standardization and normalization processing; Step two: correlation analysis, using statistical methods to analyze the relative importance of each dimension or the correlation strength between dimensions; Step three: core visualization layout generation, using dynamic dimension axis layout based on the analysis results of step two; Step four: visual coding, assigning visual properties to data points, lines and surfaces for encoding multiple additional dimension information and properties of data points; Step five: interaction mechanism implementation, providing rich user interaction interfaces; Step six: view rendering, rendering the processed data and layout information to a display device in combination with visual coding and interaction state, significantly reducing unnecessary visual element overlap, focusing on core dimension relationships, making layout more consistent with cognitive habits, and making visual coding clearer by dynamically selecting key dimensions, innovative non-fixed layouts, or combining dimension reduction and original views, so that users can more quickly understand the structure and patterns of high-dimensional data.

[0021] The dynamic dimension axis dynamically selects, sorts and arranges K key or most relevant dimension axes according to the current analysis focus and user interaction, K is less than N, and the K dimension axes are arranged in a non-orthogonal and non-parallel manner on a two-dimensional plane to form a focused layout, so that the complex correlation between dimensions, the clustering structure of data and the nonlinear mode can be more intuitively displayed.

[0022] The user interaction interface includes dimension selection, dimension filtering, dimension sorting, weight adjustment, dynamic query, dimension relationship exploration and view linkage, so that the user can conveniently operate and actively explore data.

[0023] The system comprises a data acquisition module, a data preprocessing module, a dimension analysis module, a visualization layout engine module, a visual coding module, an interaction processing module, a view rendering module and a storage module, the data acquisition module is responsible for acquiring original data, the data preprocessing module is responsible for cleaning, standardizing and normalizing the collected data, and the visualization layout engine module is responsible for mapping high-dimensional data to a two-dimensional space layout.

[0024] The visual coding module is responsible for assigning visual properties to data according to analysis results, and the interaction processing module is responsible for responding to user interaction operations, dynamically updating the parameters of the layout engine and the visual coding module and triggering view redrawing, so that corresponding view display can be performed according to user requirements.

[0025] The view rendering module is responsible for drawing the final visualization result on the screen, and the storage module is used to store original data, processed data, configuration parameters and user interaction history, so that the data source can be clearly determined and the user can conveniently search and process.

[0026] The visualization layout engine module determines K target dimensions from the N dimensions based on a preset rule, K is an integer greater than or equal to 2 and less than N, determines the non-orthogonal and non-parallel dynamic layout position and direction of the visualization axes corresponding to the K target dimensions in a two-dimensional display space according to the association relationship between the K target dimensions, maps the value of each data point in the K target dimensions of the original data set to the corresponding visualization axis of the dynamic layout, and connects to form the visualization representation of each data point, so that the global structure is displayed while the original information of the key dimensions is retained, and the data loss is less.

[0027] The above is only a preferred embodiment of the present application, and is not used to limit the protection scope of the present application.

Claims

1. A method for visualizing multi-dimensional data, characterized in that: The specific steps include: Step 1: Data acquisition and preprocessing: obtain the original data set containing N dimensions, and perform data cleaning, standardization and normalization; Step 2: Correlation analysis, using statistical methods to analyze the relative importance of each dimension or the strength of the correlation between dimensions; Step 3: Generate the core visualization layout, using dynamic dimension axis layout based on the analysis results of step 2; Step 4: Visual encoding, assigning visual attributes to data points, lines, and surfaces to encode multiple additional dimensional information and attributes of data points; Step 5: Implement the interactive mechanism and provide a rich user interaction interface; Step 6: View rendering, combining the processed data and layout information with visual encoding and interaction status, and rendering output to the display device.

2. The method for visualizing multi-dimensional data according to claim 1, wherein: The dynamic dimension axis dynamically selects, sorts and arranges the most critical or relevant K dimension axes according to the current analysis focus and user interaction, where K is less than N, and arranges them non-orthogonally and non-parallel on a two-dimensional plane to form a focused layout.

3. The method for visualizing multi-dimensional data according to claim 2, characterized in that: The user interaction interface includes dimension selection, dimension filtering, dimension sorting, weight adjustment, dynamic query, dimension relationship exploration and view linkage.

4. The system of the method for visualizing multi-dimensional data according to claim 3, characterized in that: It includes a data acquisition module, a data preprocessing module, a dimensional analysis module, a visual layout engine module, a visual encoding module, an interaction processing module, a view rendering module and a storage module. The data acquisition module is responsible for acquiring the original data, the data preprocessing module is responsible for cleaning, standardizing and normalizing the collected data, and the visual layout engine module is responsible for mapping high-dimensional data to a two-dimensional space layout.

5. The system of the method for visualizing multi-dimensional data according to claim 4, characterized in that: The visual encoding module is responsible for assigning visual attributes to the data based on the analysis results, and the interaction processing module is responsible for responding to user interaction operations, dynamically updating the parameters of the layout engine and the visual encoding module and triggering view redrawing.

6. The system of the method for visualizing multi-dimensional data according to claim 5, characterized in that: The view rendering module is responsible for drawing the final visualization result on the screen, and the storage module is used to store original data, processed data, configuration parameters and user interaction history.

7. The system of the method for visualizing multi-dimensional data according to claim 6, characterized in that: The visualization layout engine module determines K target dimensions from the N dimensions based on preset rules, where K is an integer greater than or equal to 2 and less than N. According to the association relationship between the K target dimensions, the module determines the non-orthogonal and non-parallel dynamic layout positions and directions of the visualization axes corresponding to the K target dimensions in the two-dimensional display space, maps the values ​​of each data point in the original data set on the K target dimensions to the corresponding visualization axes of the dynamic layout, and connects them to form a visualization representation of each data point.

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