WO2017111197A1 - Big data visualisation system and method in learning analysis - Google Patents

Abstract

The present invention relates to a big data visualisation system and method, wherein a big data visualisation system related to an example of the present invention comprises: an analysis manager for managing an analysis module; storage space for storing analysis data; a visualisation server for generating a visualisation page; and a visualisation UI for displaying the visualisation page and for transferring user inputs to the visualisation server, wherein the visualisation server can automatically generate a query using metadata of the analysis module and receive analysis data using the query.

Description

Big Data Visualization System and Method in Learning Analytics

The present invention relates to a big data visualization system and method, and more particularly, to a system and method for automatically generating SPARQL-based query statements using metadata and retrieving data and visualizing them in order to visualize big data in learning analysis. It is about.

Learning analytics measures, gathers, analyzes, and reports data related to learners and learners' contexts in order to understand and optimize learning and learning environments. The amount of data related to such learning is enormous, and it is difficult for an analyst to directly analyze all the individual data, and thus, it is required to visualize it with a chart.

In particular, visualization is receiving attention as an analytical technique for intuitively recognizing the overall meaning of big data, and various visualization charts are disclosed, but it is difficult to use unless it is a program developer.

Accordingly, there is a demand for a technology for conveniently acquiring various visualization charts that can intuitively grasp the overall meaning of the data included in the database.

The present invention has been made to solve the above-mentioned conventional problems, and an object thereof is to provide a user with a system and method for visualizing big data.

Specifically, the purpose is to visualize the data in various ways according to the needs of the user in the learning analysis.

It also aims to make it easier for users or developers who are not familiar with knowledge base technologies such as SPARQL to visualize data.

It also aims to generate visualization charts with simple commands.

On the other hand, the technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems that are not mentioned are clearly to those skilled in the art from the following description. It can be understood.

Big data visualization system according to an embodiment of the present invention for realizing the above object is an analysis manager for managing an analysis module for analyzing the raw data to generate the analysis data; A storage space for storing the analysis data in RDF (Resource Description Framework) format; A visualization server configured to visualize the analysis data to generate a visualization page; And a visualization UI for displaying the visualization page and transmitting a user input to the visualization server. When the visualization UI receives the user's page request input and delivers the user's page request to the visualization server, the visualization server is the analysis manager. Requesting and receiving information of an analysis module managed by the analysis manager, generating a selection page including a list of items of analysis data to be visualized using the information of the analysis module, and returning the selected page to the visualization UI; The UI displays the selection page, selects and transmits at least one analysis data item of the analysis data item list from the user to the visualization server, and the visualization server is associated with the received analysis data item. Query using the information of the analysis module (Qu ery) automatically generated, request the analysis data to the storage space through the query and receive the analysis data, generate the visualization page visualizing the returned analysis data, and return the visualization page to the visualization UI, The visualization UI may display the returned visualization page.

In addition, the information of the analysis module may be metadata of the analysis module.

In addition, the query may be a SPARQL protocol and RDF Query Language (SPARQL) based query.

The visualization server may further include a previously stored visualization chart list to generate the selection page, and the visualization UI receives a selection input of at least one visualization chart from the visualization chart list from the user and delivers the selected visualization chart to the visualization server. The visualization server may visualize the analysis data with the received visualization chart.

On the other hand, the data visualization method related to an embodiment of the present invention for realizing the above-mentioned problem is a visualization UI, a visualization server, an analysis manager for managing the analysis module to generate the analysis data by analyzing the raw data (RDF) and RDF (Resource) 1. A method of visualizing data using a storage space for storing the analysis data in a format, the method comprising: a first step of the visualization UI receiving a user's page request input from a user and transferring the received page request to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of the visualization server generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning the generated page to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; ; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And a seventh step of displaying, by the visualization UI, the returned visualization page.

In addition, the information of the analysis module may be metadata of the analysis module.

In addition, the query may be a SPARQL protocol and RDF Query Language (SPARQL) based query.

In addition, in the third step, the visualization server may further include a previously stored visualization chart list to generate the selection page, and in the fourth step, the visualization UI may visualize at least one of the visualization chart list from the user. Receives a chart selection input and delivers it to the visualization server, and in the sixth step, the visualization server may visualize the analysis data with the received visualization chart.

On the other hand, the recording medium related to an embodiment of the present invention for realizing the above-described problem is an analysis manager and RDF (Resource Description) for managing an analysis module for generating analysis data by analyzing the visualization UI, visualization server, raw data (raw data) In order to perform the method of visualizing the data using the storage space for storing the analysis data in the form of a program, a program of instructions that can be executed by the digital processing device is tangibly embodied and read by the digital processing device. The method of visualizing the data, the method comprising: a first step of the visualization UI receiving a user's page request input from a user and delivering the page request input to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning it to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; ; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And a seventh step of displaying, by the visualization UI, the returned graph page.

On the other hand, a computer program related to an embodiment of the present invention for realizing the above-described problem is an analysis manager and RDF (Resource Description) for managing an analysis module for generating analysis data by analyzing the visualization UI, visualization server, raw data (raw data) A computer program that can be executed on a computer to perform a method of visualizing data by using a storage space for storing the analysis data in the form of a framework),

The method of visualizing the data may include: a first step of the visualization UI receiving a page request input from a user and transmitting the page request input from the user to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning it to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; ; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And

And a seventh step of displaying, by the visualization UI, the returned graph page.

The present invention can provide a user with a system and method for visualizing big data.

Specifically, the data may be visualized in various ways according to the needs of the user in the learning analysis.

In addition, users or developers who are not familiar with knowledge base technologies such as SPARQL can easily visualize the data.

You can also create visualization charts with simple commands.

On the other hand, the effect obtained in the present invention is not limited to the above-mentioned effects, other effects that are not mentioned will be clearly understood by those skilled in the art from the following description. Could be.

The following drawings, which are attached to this specification, illustrate one preferred embodiment of the present invention, and together with the detailed description thereof, serve to further understand the technical idea of the present invention. It should not be construed as limited.

1 is a block diagram of a big data visualization system according to an embodiment of the present invention.

2 is a flowchart illustrating a data visualization method according to an embodiment of the present invention.

3 is in accordance with an embodiment of the present invention.

4A and 4B illustrate that a visualization UI selects and inputs an analysis data item according to an embodiment of the present invention.

5 illustrates a visualization chart list according to an embodiment of the present invention.

6A and 6B illustrate a visualization page generated by a visualization server according to an embodiment of the present invention.

Hereinafter, with reference to the drawings will be described a preferred embodiment of the present invention. In addition, one Example described below does not unduly limit the content of this invention described in the Claim, and the whole structure demonstrated by this Embodiment is not necessarily required as a solution of this invention.

1 is a block diagram of a big data visualization system according to an embodiment of the present invention.

Referring to FIG. 1, the big data visualization system may include a visualization UI 110, a visualization server 120, an analysis manager 130, and a storage space 140.

However, since the components shown in FIG. 1 are not essential, a big data visualization system having more or fewer components may be implemented.

First, the visualization UI 110 receives an input from a user and displays a page visualized by the visualization server 120.

That is, the visualization server 120 receives the page request input from the user in order to visualize the data and starts the operation, and the visualization information desired by the user on the page returned from the visualization server 120 (analysis data item, type of visualization chart). Etc.) can be selected.

In addition, the visualization UI 110 displays the page returned from the visualization server 120 to be described later. That is, the visualization server 120 may display a selection page including a list of items of analysis data visualized using the information of the analysis module (metadata of the analysis module), and the visualization server 120 uses the analysis data. To visualize the visualization page.

Next, the visualization server 120 is configured to visualize the analysis data to generate a visualization page.

In detail, when the visualization server 120 receives a page request input from the visualization UI 110, the visualization server 120 requests and receives information (metadata) of the analysis module from the analysis manager 130, which will be described later, and uses the information of the analysis module. A selection page including a list of items of analysis data to be visualized is generated and returned to the visualization UI 110.

The visualization server 120 may further generate a selection page by further including a pre-stored visualization chart list.

That is, the chart list is a list in which various types of chart shapes in which analytical data is visualized are displayed. The chart list may include a bar chart and a pie chart. When the visualization server 120 further includes a chart list to generate a selection page, the visualization UI 110 receives and inputs at least one visualization chart from the visualization chart list to the visualization server 120. The visualization server 120 may visualize the data according to the selected visualization chart when visualizing the analysis data.

In addition, the visualization server 120 automatically generates a query for retrieving an input for visualization information desired by the user from the visualization UI 110. That is, a query is generated using information (metadata) of the analysis module associated with the received analysis data item, and the analysis data is returned from the storage space 140 through the query. In this case, the query may be a query based on SPARQL Protocol And RDF Query Language (SPARQL).

Next, the analysis manager 130 is a configuration for managing the analysis module for generating the analysis data by analyzing the raw data (raw data).

The analysis manager 130 may manage a plurality of analysis modules, and each analysis module has metadata. For example, metadata of the analysis module may include a developer, a version of the analysis module, a type of result data analyzed by the analysis module, a type of result data, and the like. The above-described visualization server 120 generates a selection page using the metadata of the analysis module and generates a query.

Next, the storage space 140 is configured to store the analysis data analyzed by the analysis manager 130 in a resource description framework (RDF) format.

In other words, the data is stored in the form of 'subject-predicate-object' as a triple structure.

Hereinafter, a data visualization method will be described in detail with reference to FIG. 2.

2 is a flowchart illustrating a data visualization method according to an embodiment of the present invention.

First, the visualization UI 110 receives the user's page request input from the user and transmits the page request input to the visualization server 120 (S10).

Next, in response to the page request input, the visualization server 120 starts generating the selected page (S20), and the visualization server 120 informs the analysis manager 130 of the analysis module managed by the analysis manager 130. Request (S30).

That is, to request a list of metadata of the analysis module to generate a selection page.

Next, the analysis manager 130 returns a list of metadata (S40), and the visualization server 120 generates a selection page including a list of items of analysis data to be visualized using the metadata to generate a visualization UI 110. Return to the selection page (S50).

At this time, the visualization server 120 may further include a previously stored visualization chart list to generate a selection page and return it to the visualization UI 110.

Next, the visualization UI 110 displays the selection page (S60), and receives at least one analysis data item from the item list of analysis data from the user (S70).

When the selection page includes the visualization chart list, the visualization UI 110 may display the visualization chart list and receive at least one of the visualization charts.

Next, the visualization UI 110 transmits the input information to the visualization server 120 (S80).

Next, the visualization server 120 automatically generates a query using information of the analysis module associated with the received analysis data item (S90), and requests the analysis data to the storage space 140 through the query. It is returned (S100) (S110).

In this case, the query may be generated based on SPARQL Protocol And RDF Query Language (SPARQL).

Next, the visualization server 120 generates a visualization page visualizing the returned analysis data (S120) and returns a visualization page to the visualization UI 110 (S130).

In operation S70, when the visualization chart is selected and received, the visualization server 120 may visualize the analysis data using the selected visualization chart.

Next, the visualization UI 110 displays the returned visualization page (S140).

Hereinafter, an embodiment of a data visualization method will be described with reference to the drawings.

First, the data stored in the storage space 140 of the present embodiment is disclosed.

// ① Number of pages read by individual date Graph data

// analyzed user, used analysis Component

// example with data from 2015-11-01 to 2015-11-06

<http://ai.uos.ac.kr/PageViews/User001/>

: actor <http://ai.uos.ac.kr/user/User001/>

: using <http://ai.uos.ac.kr/PageViews/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-01/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-02/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-03/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-04/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-05/>

: contains <http://ai.uos.ac.kr/PageViews/user001/2015-11-06/>

// ② Page number data read by date

// analysis component used, number of pages read

<http://ai.uos.ac.kr/PageViews/user001/2015-11-01/>

: using <http://ai.uos.ac.kr/PageViewCounter/>

: viewCount "10"

// ③ Number of pages read per month and total average comparison graph data

<http://ai.uos.ac.kr/PageViewsCompare/User001/>

     : actor <http://ai.uos.ac.kr/user/User001>

     : using <http://ai.uos.ac.kr/PageViewsCompare/>

     : userViewCount <http://ai.uos.ac.kr/PageViews/User001/2015-11/>

     : averageViewCount <http://ai.uos.ac.kr/PageViews/Average/2015-11/>

// ④ page data read per month

<http://ai.uos.ac.kr/PageViews/User001/2015-11/>

: using <http://ai.uos.ac.kr/PageViewCounter/>

: viewCount "100"

// ⑤ average number of pages read per month

<http://ai.uos.ac.kr/PageViews/Average/2015-11/>

: using <http://ai.uos.ac.kr/PageViewCounter/>

: viewCount "90"

Next, metadata of the analysis module managed by the analysis manager 130 of the present embodiment is disclosed.

// ⑥ Metadata of PageViews Component

// developer, version, and result data type generated

// For this Component, the result consists of a list of contains

// Create data such as <http://ai.uos.ac.kr/PageViews/User001/> through this Component

<http://ai.uos.ac.kr/PageViews/>

: developer <http://ai.uos.ac.kr/jinmanKang/>

: version "1.0"

: resultType: list

: resultData: contains

// ⑦ Metadata of PageViewCounter Component

// save as integer Type in viewCount

// duration is the duration over which to count the number of pages read. Day here, so day

// create data like <http://ai.uos.ac.kr/PageViews/user001/2015-11-01/> through this Component

<http://ai.uos.ac.kr/PageViewCounter/>

: developer <http://ai.uos.ac.kr/jinmanKang/>

: version "1.0"

: resultType: integer

: resultData: viewCount

: duration: day

// ⑧ Metadata of PageViewsCompare Component

// print set data consisting of userViewCount and averageViewCount

// create data like <http://ai.uos.ac.kr/PageViewsCompare/User001/>

<http://ai.uos.ac.kr/PageViewsCompare/>

: developer <http://ai.uos.ac.kr/jinmanKang/>

: version "1.0"

: resultType: set

: resultData: userViewCount

: resultData: averageViewCount

// ⑨ Metadata of PageViewCounter Component

// store as integer in viewCount

// data like <http://ai.uos.ac.kr/PageViews/User001/2015-11/>, <http://ai.uos.ac.kr/PageViews/Average/2015-11/> produce

<http://ai.uos.ac.kr/PageViewCounter/>

: developer <http://ai.uos.ac.kr/jinmanKang/>

: version "1.0"

: resultType: integer

: resultData: viewCount

: duration: month

The visualization UI 110 receives the user's page request input from the user and delivers the page request input to the visualization server 120.

Next, the visualization server 120 requests metadata of the analysis module managed by the analysis manager 130 from the analysis manager 130. The analysis manager 130 then returns metadata such as ⑥, ⑦, ⑧, and ⑨ to the visualization server 120.

The visualization server 120 generates a selection page including a list of items of analysis data to be visualized using the returned metadata and returns the selection page to the visualization UI 110.

3 illustrates a selection page including an item list of analysis data according to an embodiment of the present invention, and the visualization server 120 generates an item 'number of pages read by individual' from the returned metadata ⑥ and generates the metadata ⑦. Create a 'number of pages read by date' from, and create a 'number of pages read per month' from metadata ⑧ and 'average number of pages read per month' from metadata ⑨.

The visualization UI 110 displays the returned selection page and selects and receives at least one of a list of items of analysis data displayed by the user.

4A and 4B illustrate that a visualization UI selects and inputs an analysis data item according to an embodiment of the present invention, and FIG. 4A shows the number of pages read by individual and the number of pages read by date in one chart. 4B is a selection input for displaying “personal monthly pages read” and “average monthly pages read” on one chart.

The visualization server 120 may further generate a selection page by further including a pre-stored visualization chart list. Examples of visualization charts include horizontal bar charts, column charts, pie charts, and the like. When the visualization UI 110 returns a selection page including a list of visualization charts, the visualization chart list is further displayed as shown in FIG. At least one of the visualization chart may be input selection.

Thereafter, when the visualization UI 110 transmits an item of analysis data and a visualization chart selected by the user to the visualization server 120, the visualization server 120 may provide metadata of an analysis module associated with the item of the analysis data. Create a query automatically.

The following is a query (⑩, ⑪) automatically generated by the visualization server 120 based on SPARQL.

// Query Query automatically generated to generate graph of the number of pages read by user001's date.

select? date? viewCount where {? s: actor <http://ai.uos.ac.kr/user/User001>;

: contains? date.

? date: viewCount? viewCount}

// Query Query that is automatically generated to generate graph of comparison with monthly average of User001

select? userViewCount? averageViewCount where

{? s: actor <http://ai.uos.ac.kr/user/User001>;

: userViewCount? user;

: averageViewCount? average.

? user: viewCount? userViewCount.

? average: viewCount? averageViewCount. }

When the visualization UI 110 is selected and input as shown in FIG. 4A, the visualization server 120 uses ⑥ and ⑦ as metadata of the analysis module associated with the “number of pages read by individual” and “number of pages read by date”. Generate the same query automatically.

In addition, when the visualization UI 110 is selected and input as shown in Figure 4b, the visualization server 120 is the metadata ⑧ and ⑨ that is the metadata of the analysis module associated with 'personal monthly pages read' and 'average monthly pages read' Automatically generate a query like

Thereafter, the visualization server 120 receives data such as ⑫ and 하기 below from the storage space 140 based on the generated query.

// Example of data received by query of 때 when there is analysis data such as ⑫ ①, ②

date ViewCount

<http://ai.uos.ac.kr/PageViews/user001/2015-11-01/> 10

<http://ai.uos.ac.kr/PageViews/user001/2015-11-02/> 15

<http://ai.uos.ac.kr/PageViews/user001/2015-11-03/> 15

<http://ai.uos.ac.kr/PageViews/user001/2015-11-04/> 20

<http://ai.uos.ac.kr/PageViews/user001/2015-11-05/> 20

<http://ai.uos.ac.kr/PageViews/user001/2015-11-06/> 20

// Example of data received by query of 때 when there is analysis data such as ⑬ ③, ④, ⑤

? userViewCount? averageViewCount

100 90

The visualization server 120 generates a visualization page using the data returned by the generated query.

6A and 6B illustrate a visualization page generated by a visualization server according to an embodiment of the present invention.

FIG. 6A illustrates a visualization chart obtained by receiving analysis data of B using a query of Q. FIG. 6B illustrates a visualization chart by receiving analysis data of B using a query of Z.

In addition, FIG. 6A illustrates a selection of a vertical bar chart when a user selects a type of visualization chart in the selection page, and FIG. 6B illustrates a selection of a bar chart.

The visualization server 120 returns a visualization page including the generated visualization chart to the visualization UI 110, and the visualization UI 110 displays the visualization page as shown in FIGS. 6A and 6B.

On the other hand, the present invention can also be embodied as computer readable codes on a computer readable recording medium. Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like, which are also implemented in the form of carrier waves (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the art to which the present invention belongs.

The big data visualization system and method described above may not be limitedly applied to the configuration and method of the embodiments described above, but the embodiments may be selectively implemented in whole or in part in each of the embodiments so that various modifications may be made. It may be configured in combination.

The present invention applying the above-described configuration can provide a user with a system and method for visualizing big data.

Specifically, the data may be visualized in various ways according to the needs of the user in the learning analysis.

In addition, users or developers who are not familiar with knowledge base technologies such as SPARQL can easily visualize the data.

You can also create visualization charts with simple commands.

On the other hand, the effect obtained in the present invention is not limited to the above-mentioned effects, other effects that are not mentioned will be clearly understood by those skilled in the art from the following description. Could be.

Claims (10)

An analysis manager for managing an analysis module for analyzing raw data and generating analysis data; A storage space for storing the analysis data in RDF (Resource Description Framework) format; A visualization server configured to visualize the analysis data to generate a visualization page; And And a visualization UI for displaying the visualization page and transmitting a user input to the visualization server. When the visualization UI receives the user's page request input and delivers it to the visualization server, the visualization server requests and receives information of an analysis module managed by the analysis manager, and uses the information of the analysis module. Generate a selection page including a list of items of the analysis data to be visualized and return to the visualization UI; The visualization UI displays the selection page, receives at least one analysis data item of the analysis data item list from the user, and transmits the analysis data item to the visualization server. The visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, requests the analysis data to the storage space through the query and returns the query. And generating the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI, wherein the visualization UI displays the returned visualization page. The method of claim 1, Big data visualization system, characterized in that the information of the analysis module is metadata of the analysis module. The method of claim 1, The query is a big data visualization system, characterized in that SPARQL (SPARQL Protocol And RDF Query Language) based query. The method of claim 1, The visualization server generates the selection page further including a list of previously stored visualization charts, The visualization UI receives a selection input of at least one visualization chart of the visualization chart list from the user and delivers it to the visualization server, The visualization server is a big data visualization system, characterized in that for visualizing the analysis data with the received visualization chart. Visualize the data using a visualization UI, a visualization server, an analysis manager that manages an analysis module that analyzes raw data and generates analysis data, and a storage space for storing the analysis data in a Resource Description Framework (RDF) format. In the way, A first step of the visualization UI receiving a user's page request input from a user and delivering the input to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of the visualization server generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning the generated page to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And And a seventh step of displaying, by the visualization UI, the returned visualization page. The method of claim 5, The information of the analysis module is a data visualization method, characterized in that the metadata of the analysis module. The method of claim 5, The query is a big data visualization method, characterized in that SPARQL (SPARQL Protocol And RDF Query Language) based query. The method of claim 5, In the third step, The visualization server generates the selection page further including a list of previously stored visualization charts, In the fourth step, The visualization UI receives a selection input of at least one visualization chart of the visualization chart list from the user and delivers it to the visualization server, In the sixth step, The visualization server is a big data visualization method characterized in that to visualize the analysis data with the received visualization chart. Visualize the data using a visualization UI, a visualization server, an analysis manager that manages an analysis module that analyzes raw data and generates analysis data, and a storage space for storing the analysis data in a Resource Description Framework (RDF) format. In the recording medium which is tangibly embodied, and which can be read by the digital processing device, a program of instructions that can be executed by the digital processing device to perform the method The method of visualizing the data, A first step of the visualization UI receiving a user's page request input from a user and delivering the page request input to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning it to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And And a seventh step of displaying, by the visualization UI, the returned graph page. Visualize the data using a visualization UI, a visualization server, an analysis manager that manages an analysis module that analyzes raw data and generates analysis data, and a storage space for storing the analysis data in a Resource Description Framework (RDF) format. A computer program that can be run on a computer to perform a method of The method of visualizing the data, A first step of the visualization UI receiving a user's page request input from a user and delivering the page request input to the visualization server; A second step of the visualization server requesting and receiving information of an analysis module managed by the analysis manager from the analysis manager; A third step of generating a selection page including an item list of the analysis data to be visualized by using the information of the analysis module and returning it to the visualization UI; A fourth step of displaying, by the visualization UI, the selection page and receiving at least one analysis data item of the analysis data item list from the user and delivering the selected analysis data item to the visualization server; A fifth step in which the visualization server automatically generates a query using information of the analysis module associated with the received analysis data item, and requests and returns the analysis data to the storage space through the query; A sixth step of generating, by the visualization server, the visualization page visualizing the returned analysis data and returning the visualization page to the visualization UI; And And a seventh step of displaying, by the visualization UI, the returned graph page.

Images