KR101788250B1 - Apparatus and method for data visualization - Google Patents
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Abstract
A data visualization apparatus and method thereof are disclosed. The data visualization apparatus grasps the pixel coordinate values in the visualization area for each data element included in the source data, and based on the pixel coordinate values of the respective data elements, at least two data elements among the pixels in the visualization area are superposed After determining one data element to be mapped with the superposed pixel according to a predetermined criterion, a chart is generated in which at least one or more legends of the data elements mapped with each pixel in the visualization area are displayed.
Description
BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data visualization apparatus and method thereof, and more particularly, to an apparatus and a method for visualizing a very large amount of data, such as big data, on a chart.
Big data refers to a set of fixed or unstructured data that is difficult to collect, store, search, analyze, and visualize using existing database management tools. Therefore, separate tools must be developed to analyze and process big data.
For example, if you want to chart millions or tens of millions of big data at a glance, you have to display millions or tens of millions of data on the screen, It is very difficult to draw a single chart for big data because it takes a lot of time.
Therefore, conventionally, some samples are extracted from the big data, analyzed and charted using the samples. However, this is a statistical analysis, which is far from analyzing the big data itself.
An object of the present invention is to provide an apparatus and a method for visualizing all data on a chart regardless of the amount of data.
According to an aspect of the present invention, there is provided a method of visualizing data, the method comprising: receiving source data; Determining pixel coordinate values in the visualization area for each data element included in the source data; Determining a data element to be mapped with an overlapping pixel in which at least two data elements of the pixels in the visualization area overlap based on pixel coordinate values of each data element according to a predetermined criterion; And generating a chart in which at least one or more legends of data elements mapped with each pixel in the visualization area are displayed.
According to an aspect of the present invention, there is provided a data visualization apparatus comprising: an input unit for receiving source data; A coordinate acquiring unit for acquiring, for each data element included in the source data, pixel coordinate values in the visualization area; A redundancy removal unit for determining, based on a predetermined criterion, a data element to be mapped with an overlapping pixel in which at least two data elements of the pixels in the visualization area are overlapped, based on pixel coordinate values of the respective data elements; And an image generation unit for generating a chart in which at least one or more legends of the data elements mapped with each pixel in the visualization area are displayed.
According to the present invention, a very large amount of data, such as big data that can not be visualized by a conventional database management tool, can be visualized in a chart, so that a value can be effectively found in a wide range of data. In addition, the time required for visualizing the chart can be greatly shortened, and the size of the visualization result (for example, a chart, etc.) is small so that it can be easily shared with other users or transmitted.
FIG. 1 illustrates an example of a data visualization apparatus according to the present invention.
2 is a diagram showing an example of source data used for visualization according to the present invention;
FIG. 3 is a diagram showing an example of chart visualization of source data according to the present invention,
4 is a diagram showing the configuration of an embodiment of a data visualization apparatus according to the present invention,
5A is a diagram illustrating an example of visualization data for storing information on each pixel in the visualization area according to the present invention;
FIG. 5B is a diagram showing an example of a matrix representation of the visualization data of FIG. 5A,
6 is a diagram illustrating an example of a redundancy elimination method for data visualization according to the present invention.
7 is a diagram illustrating another example of a redundancy elimination method for data visualization according to the present invention.
8 is a diagram illustrating another example of a redundancy elimination method for data visualization according to the present invention.
Figure 9 illustrates an example of a multi-layered structure for data visualization in accordance with the present invention;
Figure 10 is a flow diagram of one embodiment of a data visualization method according to the present invention,
11 is a view showing an example of a distributed processing system for data visualization according to the present invention.
12 is a diagram illustrating an example of a method of inquiring a specific value in a chart according to the present invention,
13 and 14 are views showing an example of a chart image generated through the data visualization method according to the present invention.
Hereinafter, a data visualization apparatus and method according to the present invention will be described in detail with reference to the accompanying drawings.
1 is a diagram showing an example of a data visualization apparatus according to the present invention.
Referring to FIG. 1, a data visualization apparatus 110 reads raw data 100 and visualizes it in a chart 120. Here, the chart 120 refers to a graphical representation of two or more mutual relationships or states of change. As an example of the chart 120, there are a circle chart, a bar chart, a line chart, a scatter chart, a box plot, a treemap, and the like. One example of a chart according to the present invention is shown in Figs. 13 and 14. Fig.
In the case where the source data 100 is large data including millions of data elements, in order to display all the data elements in the chart 120, the display operation must be repeatedly performed several million times or more, Or more, the display operation must be performed several billion times or more, which is practically impossible. However, when only a part of the sample of the source data 100 is extracted and visualized in a chart, data elements that actually exist in the source data 100 may not be displayed on the chart, so that the chart properly reflects the information of the source data. There is a problem that can not be done.
When the source data 100 is displayed on the chart 120, the data elements of the source data 100 are often superimposed on the chart 120, It is a data element to be displayed later. For example, when a first data element is displayed on a chart and then a second data element is displayed in the same position as the first data element, the user only sees a second data element. That is, the chart created by performing the operation of displaying both the first data element and the second data element and the chart created by performing the operation of displaying only the second data element, omitting the process of displaying the first data element, It seems.
Thus, the data visualization apparatus 110 of the present embodiment not only enables visualization of high-capacity data such as big data but also shortens the time required for data visualization by omitting the operation of drawing the data elements on a chart.
2 is a diagram showing an example of source data used for visualization according to the present invention.
Referring to FIG. 2, the source data 100 is composed of a plurality of data elements, and each data element has at least one value (212, 214, 216). Each data element may be separated by an index 210.
For example, the source data 100 may be various kinds of sensing information measured at predetermined time intervals by the sensors installed in each line of the factory. The sensing information measured every predetermined time interval can constitute each data element of the source data 100. [ In addition, the source data may be various types of big data, including information on various consumption patterns, information on weather, and the like, including regular or irregular values.
In this embodiment, for convenience of description, the data element includes three values 221, 214, and 216, but the source data 100 can be variously modified according to the embodiment.
FIG. 3 is a diagram showing an example of charting source data according to the present invention in a chart.
Referring to FIG. 3, a chart 120 includes a visualization area 300 that is a space for visually displaying each data element of the source data. Each data element is represented by a legend given to each data element in the visualization area 300. For example, each data element may be represented by legends of various shapes such as a circle 310, a rectangle 320, and a triangle 330. In addition, various types of legends that allow the user to recognize each data element by using shape, color, size, etc., such as a legend composed of one pixel, a legend having a color attached to a point or a certain area, Lt; / RTI > Therefore, the legend is defined as being made visually recognizable by using at least one of shape, color, size, pattern, saturation, brightness, transparency, various symbols, numbers and letters.
When the size of the visualization area 300 in which the chart 120 is to be displayed is set, the number of pixels in the horizontal and vertical directions included in the visualization area 300 is determined. The size setting of the visualization area 300 of the chart can be set through various conventional user interfaces. In order to display each data element of the source data 100 in the visualization area 300, it is necessary to determine which coordinate in the visualization area 300 the data element is located. For example, when the A value and the B value of the source data 100 in FIG. 2 are displayed in correspondence with the horizontal and vertical of the chart, respectively, the horizontal and vertical minimum values (A min , B min ) (A max , B max ) is determined, the minimum size of the displayable value per pixel is determined.
For example, if the visualization area 300 is composed of 100 X 100 pixels, the minimum value of the data elements represented on the horizontal axis of the chart is 0, the maximum value is 10, the minimum value of the data elements represented on the vertical axis of the chart is 0, Let's say this is 20. In this case, the horizontal direction can represent a minimum value of 0.1 (= 10/100) per pixel, and the vertical direction can represent a minimum value of 0.2 (20/100) per pixel. (A, B) of the data element is (2,10) when the vertex at the lower left of the visualization area 300 is the origin (0,0) The coordinate values become (20 (= 2 / 0.1), 50 (= 10 / 0.2)).
According to an embodiment, there may be a data element having a value smaller than a minimum size that can be displayed by the pixel interval in the visualization area among the data elements of the source data. In the above example, assume that the value of the first data element is (2.01, 10.02) and the value of the second data element is (1.98, 9.99). Since the minimum size that can be displayed on the horizontal axis in the visualization area 300 is 0.1 and the minimum size that can be displayed on the vertical axis is 0.2, the value of the second decimal place can not be displayed, so that the values of the first data element and the second data element can be visualized It should be converted to a value within the range that can be displayed in the area. That is, the value of the horizontal axis of the first and second data elements should be converted to an integer multiple of 0.1, which is the minimum size of the horizontal axis, and the value of the vertical axis of the first and second data elements should be converted to an integer multiple of 0.2 . Various mathematical methods such as rounding, discarding, and rounding up the transformation can be applied. If rounding is applied to the second decimal place, the value of the first data element and the value of the second data element are both (2, 10), so that the pixel coordinate values for the first data element and the second data element are also 20, 50).
In this way, pixel coordinate values for all data elements of the source data can be grasped. In the present embodiment, the pixel coordinate values of the data elements are grasped and not drawn directly on the chart, but redundancy of the data elements is removed to prevent redundant drawing.
4 is a diagram showing the configuration of an embodiment of the data visualization apparatus according to the present invention.
Referring to FIG. 4, the data visualization apparatus 110 includes an input unit 400, a coordinate determination unit 410, a redundancy removal unit 420, and an image generation unit 430.
The input unit 400 receives the source data.
When the visualization area in which the chart is to be displayed is defined, the coordinate determination unit 410 grasps the pixel coordinate values in the visualization area for each data element of the source data. The pixel coordinate values of the respective data elements are grasped based on the minimum and maximum values displayed on the horizontal and vertical sides of the chart and the number of pixels in the visualization area, as described with reference to FIG.
For example, after determining the minimum displayable size for each pixel in the visualization area, the coordinate determination unit 410 determines whether the data element is an integer multiple of the minimum size that can be displayed in the visualization area And then the coordinate value of the pixel corresponding to the converted value is grasped. According to the embodiment, the coordinate determination unit 410 may separately store and manage conversion data obtained by converting each data element into an integer multiple of a minimum size that can be displayed in the visualization area.
The redundancy elimination unit 420 recognizes the data elements which are drawn in the same coordinate in the visualization area and removes redundancy. If multiple data elements are drawn at the same coordinates in the visualization area, only the last drawn data element is shown in the chart, so that it is possible to omit the process of drawing data elements with overlapping coordinates.
Specifically, based on the pixel coordinate values of each data element, the redundant removal section 420 deletes one or more data elements to be mapped with overlapping pixels in which at least two data elements among the pixels in the visualization area are overlapped, For example, a reverse order of display order). For example, if the pixel coordinate values (20, 50) of the first data element and the second data element are the same and the display order of the second data element is slower, the redundancy elimination (420) , 50) and the second data element. Thus, each pixel in the visualization area is mapped to one data element.
Each data element of the source data can be sequentially selected in accordance with the display order so that the redundancy of the pixel coordinate value can be grasped. However, whenever redundancy is found, information about data elements mapped to each pixel must be updated every time with information on a data element whose display order is slower, resulting in a time delay due to an update. If the amount of data, such as Big Data, is greater than tens of millions, the latency due to these updates can be so large that it can not be ignored. For example, when checking the redundancy of data elements sequentially according to the display order, after storing information indicating that the first pixel coordinate value and the first data element are mapped, the second data element having the first pixel coordinate value The display order of the second data element is slower, so that the data element mapped with the first pixel coordinate value should be updated with the second data element.
Accordingly, in order to prevent the delay time due to such an update, the redundancy elimination unit 420 extracts each data element of the source data in the reverse order of the display order to grasp the redundancy of the pixel coordinate value. For example, after storing information about the Kth data element to be mapped with the first pixel coordinate value, even if another data element having the first pixel coordinate value is found, the display order of the Kth data element is further Since it is late, the deduplication unit does not need to update the information once about the data element to be mapped with the first pixel coordinate value.
Each data element of the source data can be displayed in various types of legends in the visualization area. Therefore, the redundant removal section 420 determines whether the data elements to be mapped are overlapped with each other based on the legend of each data element that is grasped based on the pixel coordinate values of the respective data elements, . ≪ / RTI > Various examples of de-duplication are shown in Figs. 6-8.
The image generating unit 430 generates a chart in which each pixel in the visualization area and the data elements mapped are displayed in at least one or more legends. Since one pixel is mapped to each pixel in the visualization area by the redundancy elimination unit 420, the image generator may draw a legend given to each pixel and the mapped data element.
For example, when a legend consisting of one pixel is given to the data element of the source data as shown in FIG. 6, the image generating unit 430 displays the legend given to each pixel and the data element mapped on the corresponding pixel Create a chart.
As another example, when a data element of the source data is given a legend composed of a plurality of pixels as shown in FIGS. 7 and 8, the image generating unit 430 displays a legend given to each pixel and the data element mapped, Lt; / RTI > However, the pixel coordinate values of the two data elements are not the same, but a part of the legend may overlap each other as in Figs. 7 and 8. Fig. In this case, the image generating unit 430 may generate a chart by drawing a legend in consideration of the display order of the data elements mapped with each pixel.
However, in the above example, overlapping drawing of overlapping pixels of the legend occurs. 5A and 5B, which include data element indexes and color information mapped to each pixel, and the like, in addition to drawing the entirety of the legend given to each pixel and the mapped data element, Only one drawing can be performed on the overlapping pixels using the visualization data shown. In other words, the image generating unit 430 generates a chart image showing a legend of the data elements mapped with each pixel as shown in FIGS. 13 and 14 by drawing each pixel using color information of each pixel of the visualization data can do.
FIG. 5A is a diagram illustrating an example of visualization data for storing information on each pixel in the visualization area according to the present invention, and FIG. 5B is a diagram illustrating an example of visualization data of FIG.
Referring to FIG. 5A, the visualization data 500 includes pixel coordinates 510, a data element index 520, color information (or legend information) 530, and the like for each pixel in the visualization area. In the case where the data elements of the source data are represented by one pixel in the chart as shown in FIG. 6, the visualization data can be composed of only the pixel coordinates 510 and the data element index 520.
Pixel coordinates 510 represent coordinate information of each pixel in the visualization area. Pixel coordinates can be represented using a coordinate system with the origin (0,0) at a specific location (one of the corners of the rectangle, or the center of the visualization area) in the visualization area. Various conventional coordinate systems can be utilized.
The data element index 520 indicates which data element each pixel in the visualization area is associated with. For example, when data elements in the visualization area are represented by a legend, as shown in Fig. 6, it indicates to which data element each pixel is related. As another example, when a data element is represented by a square shape legend having a certain area as shown in FIG. 7, it indicates to which data element each pixel constituting the legend for displaying each data element is mapped. At this time, the data element index for the pixel whose legend overlaps represents a data element whose display order is later.
Color information (or legend information) 530 indicates information about the image to be displayed on each pixel. The color information can be represented using various models representing conventional colors such as an RGB model or a CYMK model. In addition, the visualization data may further include other information as needed.
Referring to FIG. 5B, the visualization data 500 is represented by a matrix 600. The position of the matrix is the pixel coordinate value. That is, the second row and the second row represent pixel coordinate values (2,2). The data element V stored in each matrix may include a data element index, color information, and the like. The visualization data may be stored and managed using various data structures in addition to the matrix of FIG. 5B according to an embodiment. Elements that are not mapped to data elements in the visualization data matrix 600 may be empty or filled with predetermined values.
Referring again to FIG. 5B, the redundant removal unit 420 in FIG. 4 reconstructs redundant pixels having redundant data elements based on the pixel coordinate values of the respective data elements of the source data. One of the data elements is selected as the redundant pixel and the mapped data element by a predetermined criterion (for example, a reverse order of display order). For example, in a case where a plurality of data elements are superimposed on the pixel coordinates (2,2), the redundancy elimination unit 420 identifies the data elements whose display order is slowest among the overlapped data elements, 2) stores a visualization (V 22) of the visualization data for the.
As shown in FIG. 4, when data elements are extracted in the reverse order of the display order to remove redundancy, if visualization information (V 22 ) indicating information on a data element is stored in (2, 2) The division unit extracts the next data element without storing the data elements having pixel coordinate values of (2,2), and performs the redundancy elimination process.
In another example, when the legend indicating the data element has transparency, the de-duplication unit may store the visualization data (V 22 ) for (2, 2) If the data element is found by identifying the colors of the (2,2) visualization data (V 22), color information 530, color and transparency, and the other data elements of the newly found in the color of a legend applied to the different data element and it updates the color information 530 of the visualization data (22 V). In this case, the data index information 520 of the visualization data is not updated.
FIG. 6 is a diagram illustrating an example of a redundancy elimination method for data visualization according to the present invention.
Referring to FIG. 6, a portion 600 of a visualization area where a data element is visualized using a legend of one pixel and a portion 605 of pixel coordinate values for data elements of the source data are shown.
If both the pixel coordinate values of the first data element 620 and the m th data element 630 are equal to (x m , y m ), the display order of the first data element 620 is slower The data element to be mapped with the pixel coordinates (x m , y m ) of the visualization area becomes the first data element 620. Therefore, the pixel coordinate values (x m , y m ) and the index information (l) of the first data element are mapped and stored in the visualization data 650.
Information of the first data element 620 to be mapped with the pixel coordinate values (x m , y m ) in the visualization data 650 is stored first in the visualization data 650 in the case of grasping the pixel coordinate values of the data elements arranged in the reverse order of the display order And then the m th data element 630 with the pixel coordinate value (x m , y m ) is ignored without storing. That is, when the data visualization apparatus removes the redundancy of the data elements in the reverse order of the display order, the process of storing the information about the data elements corresponding to each pixel in the visualization data may be performed only once.
In another example, both the first data element 620 and the m th data element 630 are represented by one pixel in the visualization area, but they may have different color legends. That is, the first data element 620 may be displayed in red, and the m th data element 630 may be displayed in yellow. In this case, the visualization data 650 may store further comprises a color information for the red pixel with the coordinates (x m, y m), the index information (l) of the data element.
As another example, the color of the legend given to the data element may have transparency. If the transparency is 50%, not only the red color of the first data element 620 but also the yellow of the mth data element is partially transmitted to the pixel 610 of (x m , y m ). Therefore, the m-th data element 630 is not simply ignored, but rather acquires the color information of the legend of the m-th data element 630 and then stores the color information (x m , y m ) To store the color combination of red and yellow with 50% transparency.
7 is a diagram illustrating another example of a redundancy elimination method for data visualization according to the present invention.
Referring to FIG. 7, an example of a case where a rectangle legend having different colors is given to data elements is shown. In the present embodiment, the legend of the first data element 740 is a red square of 3x3 size, and the legend of the mth data element 750 is a yellow square of 3x3 size.
When it is assumed that each legend 710 and 720 is displayed in the visualization area on the basis of the pixel coordinate value of the first data element 740 and the pixel coordinate value of the second data element, the portions 730 of the two legends may overlap each other have.
The data visualization apparatus displays the pixel coordinate values of the legend (i.e., the coordinate group), the index information of the first data element, and the color information of the red color based on the pixel coordinate value of the first data element 740 in the visualization data . In addition, index information of each pixel of the coordinate group of the legend and the m-th data element, which are grasped based on the pixel coordinate value of the m-th data element 750, and yellow color information are stored in the visualization data. However, there is an overlapping pixel 730 that overlaps with the legend 710 of the first data element 740 of the legend 720 of the m-th data element 750. For this superposition pixel 730, the index information and color information of the first data element 740 whose display order is later is stored in the visualization data. It is possible to eliminate the redundancy of the data elements in the reverse order of the display order.
FIG. 8 is a diagram illustrating another example of the redundancy elimination method for data visualization according to the present invention.
Referring to FIG. 8, there is shown a case where a rectangular shape legend (810, 820) of the same color is given to a data element. The legends 810 and 820 include black borders 815 and 825 on the outside of the rectangle to distinguish data elements of the same color.
Based on the pixel coordinate values (x m , y m ) of the first data element 830, each pixel of the 5x5 magnitude legend 810 is mapped to the first data element 830. At this time, the visualization data stores color information together with index information for the first data element mapped to each pixel of the pixel coordinate group corresponding to the legend of the first data element. For example, such information as is stored in the visualization data - - (1, y m) , the data index l, red coordinates (x m) (the coordinates (x m 2, y m), the data index l, black), .
Since the m-th data element 830 has a display order that is faster than the first data element 830, the visualization data includes a pixel for the area 820 that is not overlapped with the legend 810 of the first data element, Data element index and color information are mapped and stored.
9 is a view showing an example of a multi-layer structure for data visualization according to the present invention.
9, an example is shown in which visualization data 900, 910, and 920 are generated for each legend given to each data element of the source data, and then a chart image is generated by superimposing the visualization data 900, 910, and 920.
For example, assuming that the data elements of the source data are represented by three legends such as a rectangle, a triangle, and a circle, the visualization data device generates visualization data 900, 910, and 920 in each legend. The first visualization data 900 for the data elements to which the square legend is assigned, the second visualization data 910 for the data elements to which the triangular legend is assigned, the third visualization Data 920 is generated. Then, one chart image is generated by superimposing the first to third visualization data according to the display order of each legend.
FIG. 10 is a flowchart illustrating a data visualization method according to an embodiment of the present invention.
Referring to FIG. 10, the data visualization apparatus sets a visualization area and a legend for displaying a chart (S1000). When the display size of the visualization area and the display range of the value are set, the minimum unit of the value that can be displayed by the pixels in the visualization area is determined. The data visualization apparatus receives the source data (S1010), converts the value of each data element of the source data into a range of displayable values in the visualization area, and grasps pixel coordinate values (S1020).
The data visualization device identifies a superimposed pixel in which at least two data elements are superimposed on the basis of the pixel coordinate value of each data element, and assigns any data element to be mapped with the superimposed pixel to a predetermined reference (for example, (Step S1030), the redundancy of the data elements is removed.
The data visualization apparatus can eliminate the redundancy of the data elements in the reverse order of the display order of each data element of the source data in order to speed up the generation of the chart. For example, since the data elements displayed last in the visualization area are displayed to the actual user, the data visualization device grasps the pixel coordinate values of the data elements in the order of display order, stores them in the visualization data, If the same data element is found, it is not stored in the visualization data but ignored. Specific examples of eliminating the redundancy of data elements are shown in Figs. 6 to 8. Fig.
The data visualization apparatus removes the redundancy of all the data elements included in the source data, and generates a chart image showing a legend given to each pixel and the data elements mapped using the generated visualization data at step S1040. The user can view the chart image through the display device.
11 is a diagram showing an example of a distributed processing system for data visualization according to the present invention.
Referring to FIG. 11, the data visualization method according to the present invention may be distributed through a plurality of servers 1110, 1112, and 1114. Of course, it can be performed by one server. The distribution unit 1100 distributes a plurality of charts to be generated to the source data 100 to the plurality of servers 1110, 1112, and 1114. For example, if there are 10 servers and the number of charts to be generated is 1000, the distribution unit 1100 distributes 100 charts to each server.
Each of the servers 1110, 1112, and 1114 generates each chart from the source data using the visualized data visualization method in FIGS. 1 to 10. For example, if the first server 1110 generates 100 charts, the first server 1110 stores the images of 100 charts generated and the visualization data of 100 charts in the database 1120. There may be one visualization data for one chart or a plurality of visualization data for one chart as shown in FIG.
The user terminal 1130 receives and displays the chart stored in the database 1120. Since the chart itself does not have a large amount of data, more than a thousand of them can be simultaneously displayed on the user terminal. In addition, the user terminal 1130 can easily transmit the chart image to another user terminal.
When the user wants to see the value of the data element of the source data corresponding to the specific coordinate in the chart displayed on the screen, the value of the data element is not stored in the chart image, so a separate process is required. This will be described in detail in Fig.
As another example, when a user wants to zoom in on a portion of a chart, it is necessary to create a new chart image for the area to be enlarged, rather than simply enlarging the chart image. For example, when the user selects an area of a portion of the chart currently displayed, the data elements corresponding to the selected part of the source data are identified, and a new chart image .
As described above, when the user terminal 1130 receives a request from a user for a specific value inquiry in a chart, enlargement or reduction of a chart image, modification, change, addition of original data, the request is transmitted to the server do.
If the user request is enlargement of a part of the area in the chart, the server grasps the data elements corresponding to a part of the area in the chart from the source data 100. In addition, a new chart image is generated by applying the visualized data method shown in FIGS. 1 to 10 to the identified data elements, and then the chart and visualization data are stored in the database 1120. The chart stored in the database 1120 is transmitted to the user terminal 1130 and displayed.
12 is a diagram showing an example of a method of inquiring a specific value in a chart according to the present invention.
Referring to FIG. 12, when a user selects a pixel at a specific position in the chart image displayed on the screen (S1200), the user terminal transmits the coordinate value of the selected specific pixel to the server. The server retrieves the visualization data and grasps the coordinates of the specific pixel and the mapped data element index (S1210). Then, the server refers to the source data to determine the value of the data element corresponding to the data element index (S1220), and provides the value of the determined data element to the user terminal (S1230). The user terminal then displays the value of the data element.
The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like. The computer-readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner.
The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.
Claims (17)
The data visualization apparatus comprising:
Receiving source data;
Determining pixel coordinate values in the visualization area for each data element included in the source data;
When mapping each pixel in the visualization area and each data element of the source data based on pixel coordinate values of each data element, at least two data elements among the pixels in the visualization area are mapped with overlapping overlapping pixels Determining one data element according to a predetermined criterion; And
Generating a chart in which each pixel in the visualization area is mapped with at least one or more legends by performing one drawing for each pixel.
Determining a minimum display size per pixel according to a range of values of the horizontal and vertical values of the visualization area; And
And converting the value of each data element of the source data into an integer multiple of the minimum display size to determine a position of a pixel in which each data element in the visualization area is to be displayed.
And determining a data element to be mapped with the superposed pixel based on a reverse order of display order among at least two or more data elements superimposed on the superposed pixel.
Selecting each data element of the source data in a reverse order of display order;
Determining whether another data element is mapped to a pixel corresponding to a pixel coordinate value of the selected data element by referring to visualization data indicating whether or not a data element is mapped to each pixel in the visualization area; And
And storing in the visualization data that the selected data element is mapped to a pixel to which the other data element is not mapped.
Wherein the visualization data includes color information for each pixel in the visualization area,
And updating the color information of the visualization data using the color information of the legend given to the selected data element for the pixel to which the other data element is mapped.
Wherein each data element of the source data is assigned at least one legend of color, shape, and size,
Wherein the step of determining includes determining a data element to be mapped with an overlapping pixel in which a legend of each data element that is grasped based on a pixel coordinate value of each data element is superimposed Visualization method.
Wherein each data element of the source data is assigned at least one legend of color, shape, and size,
Visualization data indicating whether or not a data element is mapped to each pixel in the visualization area exist for each legend,
Wherein the generating of the chart comprises generating a chart on which data elements mapped with each pixel are displayed based on visualization data existing for each legend.
Determining a data element index mapped to the selected specific pixel by referring to visualization data in which a data element index mapped to each pixel in the visualization area is stored, when a specific pixel of the chart is selected by a user; And
And retrieving the source data based on the identified data element index to identify and provide a value of the data element.
A coordinate acquiring unit for acquiring, for each data element included in the source data, pixel coordinate values in the visualization area;
When mapping each pixel in the visualization area and each data element of the source data based on pixel coordinate values of each data element, at least two data elements among the pixels in the visualization area are mapped with overlapping overlapping pixels A redundancy removing unit for determining one data element according to a predetermined criterion; And
And an image generating unit for generating a chart by displaying at least one or more legends of data elements mapped with each pixel in the visualization area by performing one drawing for each pixel.
And a data element to be mapped with the superposed pixel is determined based on a reverse order of display order among at least two or more data elements superimposed on the superposed pixel.
Selecting the data elements of the source data in the reverse order of the display order and referring to visualization data indicating whether or not the data elements are mapped to the respective pixels in the visualization area to generate a pixel corresponding to the pixel coordinate value for the selected data element In the visualization data, that the selected data element is mapped to a pixel for which no other data element is mapped.
And determining color information for a pixel to which the other data element is mapped using the color information of the legend given to the other data element and the color information of the legend given to the selected data element Characterized in that the data visualization device
In the distributed processing system,
Distributing a plurality of chart generation requests for the source data to at least two or more servers;
Storing the generated chart and the visualization data for each chart in a common database by eliminating the redundant drawing of the data elements of the source data by the two or more servers; And
And providing at least one of the charts stored in the database to the user terminal,
Wherein the step of removing redundant drawing comprises the steps of: when mapping each pixel in the visualization area and each data element of the source data based on pixel coordinate values of each data element, at least two of the pixels in the visualization area Determining one of the data elements to be mapped with the overlapped overlapping pixel according to a predetermined criterion,
Wherein each of the charts is generated by performing a drawing for each pixel on a chart in which at least one or more legends of data elements mapped to each pixel in the visualization area are displayed.
Receiving an inquiry request for a data element corresponding to a specific pixel of a chart from the user terminal; And
The server generating the chart of the inquiry request received from the user terminal identifies the data element index mapped with the specific pixel by referring to the visualization data storing the data element index mapped to each pixel of the chart, And retrieving the source data based on the value of the data element and providing the value of the data element.
At least two servers implemented with a data visualization method for generating a chart by removing redundant drawing of data elements included in the source data; And
And a database for storing charts generated by the at least two servers and visualization data for each chart,
Each of the two or more servers, when mapping each pixel of the visualized area and each data element of the source data, based on pixel coordinate values of each data element, at least two of the pixels in the visualized area overlap Determining one of the data elements to be mapped based on the predetermined superposed pixel according to a predetermined criterion and performing a drawing for each pixel on a chart in which at least one or more legends of data elements mapped with each pixel in the visualization area are displayed Wherein the data processing unit generates the data visualization data.
Wherein the database transmits the stored chart to the user terminal, and upon receiving the request for the chart from the user terminal, identifies the server that generated the chart and delivers the request.
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| KR102223090B1 (en) * | 2019-04-15 | 2021-03-04 | 주식회사 스캐터엑스 | Apparatus and method for chart generation |
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