CN113050846B - Component-based time-space big data visualization configuration method and system - Google Patents
Component-based time-space big data visualization configuration method and system Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
- G06F3/04817—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
- G06F3/0482—Interaction with lists of selectable items, e.g. menus
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/04845—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/33—Intelligent editors
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/34—Graphical or visual programming
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/38—Creation or generation of source code for implementing user interfaces
Abstract
The invention provides a visual configuration method and a visual configuration system for space-time big data based on components, wherein the method comprises the following steps: acquiring space-time big data to be processed; analyzing the space-time big data and determining the data type; based on the data type, calling corresponding publishing service to publish the space-time big data; receiving a visual configuration component which is processed by a third-party data processing platform on issued space-time big data; and receiving the configuration operation of the user on the visual configuration component to form a visual interface. According to the component-based space-time big data visualization configuration method, all parts are developed in a component form, and a system of the component-based space-time big data visualization configuration method is internally provided with a plurality of public and special components. After the system is on line, a customer can reissue the new demand by only configuring and adjusting the page without secondary development and redeployment. The components are interacted with each other between data, and the stability of the page is not influenced during modification.
Description
Technical Field
The invention relates to the technical field of space-time big data, in particular to a visual configuration method and a visual configuration system of space-time big data based on components.
Background
At present, the large space-time data comprise three-dimensional information of time, space and special attributes, and have the comprehensive characteristics of multiple sources, mass and quick updating. The existing visual development technology for large space-time data has the defects of long development time and low flexibility; stability can be difficult to guarantee in time critical situations. When the visualized data is online and changes occur, such as changes of customer requirements, the problems can be solved only by means of program modification and redeployment.
Disclosure of Invention
The invention aims to provide a component-based space-time big data visualization configuration method, wherein each part is developed in a component form, and a system of the component-based space-time big data visualization configuration method is internally provided with a plurality of common and specific components. After the system is on line, a customer can reissue the new demand by only configuring and adjusting the page without secondary development and redeployment. The components are interacted with each other between data, and the stability of the page is not influenced during modification.
The embodiment of the invention provides a visual configuration method of space-time big data based on components, which comprises the following steps:
acquiring space-time big data to be processed;
analyzing the space-time big data and determining the data type;
based on the data type, calling corresponding publishing service to publish the space-time big data;
receiving a visual configuration component which is processed by a third-party data processing platform on issued space-time big data;
and receiving the configuration operation of the user on the visual configuration component to form a visual interface.
Preferably, the data types include: one or more of raster data, image data, vector data, and structured data.
Preferably, based on the data type, calling a corresponding publishing service to publish the spatiotemporal big data, including;
when the data type is raster data or image data or vector data, the data is published as standard map service through arcgi s or hypergraph service;
and/or the presence of a gas in the gas,
when the data type is structured data, the data is issued through the rest service.
Preferably, the visualization configuration component comprises: one or more of a map base component, a table component, a statistical map component and a button component.
Preferably, the receiving of the configuration operation of the visualization configuration component by the user to form the visualization interface includes:
acquiring a preset configuration operation interface;
receiving a first operation of a user on a corresponding first icon of the map basic component, and displaying the map basic component corresponding to the first icon to a configuration operation interface;
receiving a second operation of the user on a corresponding second icon of the table component, and displaying the table component corresponding to the second icon to the configuration operation interface;
receiving a third operation of position adjustment of the map basic component and/or the table component on the configuration operation interface by the user; and/or receiving a fourth operation of the user for adjusting the relative positions of the map basic component and the table component; and/or receiving a fifth operation of display size adjustment of the map basic component and/or the table component by the user; and/or, receiving a sixth operation of the user for adjusting the display parameter setting of the map basic component and/or the table component; and/or receiving a seventh operation of the user on the setting of the publishing attribute of the map basic component and/or the table component; and/or receiving an eighth operation of setting the subscription attribute of the map basic component and/or the table component by the user;
receiving the storage operation of a user, storing and releasing a configuration operation interface set by the user;
wherein the first operation comprises: selecting and/or dragging;
the second operation includes: selecting and/or dragging;
the third operation includes: selecting and dragging, or selecting and inputting;
the fourth operation includes: sequentially selecting;
the fifth operation includes: selecting and dragging, or selecting and inputting;
the sixth operation includes: selecting and inputting;
the seventh operation includes: selecting;
the eighth operation includes: and (4) selecting.
Preferably, before receiving a second operation of the user on the corresponding second icon of the form component, the method further includes:
acquiring a first identification vector of a map basic component displayed to a configuration operation interface;
acquiring second identification vectors of all table components in the component database;
and calculating the association degree of the first identification vector and the second identification vector, wherein the calculation formula is as follows:
g is the association degree of the first identification vector and the second identification vector; a. theiA value of the ith data of the first identification vector; a. thejIs the value of the jth data of the first identification vector; b isiIs the value of the ith data of the second identification vector; b isjIs the value of the jth data of the second identification vector; n is the total number of data of the first identification vector or the second identification vector;
acquiring a second icon corresponding to the table component with the association degree larger than a preset association degree threshold;
constructing a selection list based on the second icon;
the selection list is delivered to the user.
Preferably, the third-party data processing platform processes the published spatiotemporal big data, and the processing comprises:
acquiring a preset standard word bank;
identifying the space-time big data based on a preset standard word bank;
when the space-time big data has unidentified data; calculating the similarity between the data and each standard word in the standard word bank, and extracting the standard words with the similarity larger than a preset similarity threshold; constructing a suspected list;
outputting the suspected list to a user for selection;
and/or the presence of a gas in the gas,
publishing the suspected list on a third-party data processing platform, and receiving joint decisions of a plurality of users on the third-party data processing platform;
and/or the presence of a gas in the gas,
and screening the standard words in the suspected list based on the historical selection records of the user, and determining the standard words corresponding to the data.
Preferably, the suspected list is published on a third-party data processing platform, and joint decisions of a plurality of users on the third-party data processing platform are received; the method comprises the following steps:
acquiring a support value of a support user corresponding to each standard word on the suspected list and a weight value of a corresponding user;
and determining a decision value whether each standard word is matched with the data or not based on the support value and the weight value, wherein a calculation formula of the decision value is as follows:
wherein J is a decision value; beta is aσThe weight value of the sigma-th user; dσA support value for the σ -th user; m is the total number of users supported by the standard words;
and comparing the decision value of each standard word in the suspected list, and acquiring the standard word with the maximum decision value as the standard word corresponding to the data.
Preferably, the component-based spatiotemporal big data visualization configuration method further includes:
when the data determined by the joint decision of the plurality of users and the standard words are accurate in corresponding relation, carrying out up-regulation operation on the support values and/or weight values of the users supported by the standard words; the support value and/or the weight value of the user supported by other standard words in the suspected list are/is adjusted downwards;
wherein, the support value or weight value after the up-regulation operation is determined by the following formula:
in the formula, K' is a support value or a weight value adjusted by an up-regulation operation; k is a support value or a weight value before the adjustment of the up-regulation operation; theta is a preset adjusting amplitude value; theta0Supplementing value for the preset amplitude;
the support value or weight value after the down-regulation operation is determined by the following formula:
in the formula, k' is a support value or a weight value after being adjusted by down-regulation operation; k is a support value or a weight value before down-regulation operation adjustment; and when the support value or the weight value which is calculated by the formula and adjusted by the down-regulation operation is smaller than a preset lower limit value, the lower limit value is the support value or the weight value which is adjusted by the down-regulation operation.
The invention also provides a component-based space-time big data visualization configuration system, which comprises:
the acquisition module is used for acquiring space-time big data to be processed;
the analysis module is used for analyzing the space-time big data and determining the data type;
the publishing module is used for calling corresponding publishing services to publish the space-time big data based on the data type;
the receiving module is used for receiving a visual configuration component which is obtained by processing the issued space-time big data by the third-party data processing platform;
and the configuration module is used for receiving the configuration operation of the visualization configuration component by the user and forming a visualization interface.
The invention has the following beneficial effects:
firstly, high efficiency: through the form of the components, the space-time big data can be displayed through simple dragging and service configuration of page configuration personnel.
Secondly, flexibility: when the customer requirements change, the requirements of the customers are realized by selecting rich self-defined components. When the data format of the service is not satisfied, the data can be filtered through the data custom filtering script provided on the component, and the component style position can also be configured.
Thirdly, stability: through the interaction of data between the assemblies, the assemblies can independently perform data processing, and the assemblies are mature, so that the stability of a program can be ensured.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a component-based spatiotemporal big data visualization configuration method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a component-based spatiotemporal big data visualization configuration method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a visualization interface in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides a component-based space-time big data visualization configuration method, as shown in fig. 1, comprising the following steps:
step S1: acquiring space-time big data to be processed;
step S2: analyzing the space-time big data and determining the data type;
step S3: based on the data type, calling corresponding publishing service to publish the space-time big data;
step S4: receiving a visual configuration component which is processed by a third-party data processing platform on issued space-time big data;
step S5: and receiving the configuration operation of the user on the visual configuration component to form a visual interface.
The working principle and the beneficial effects of the technical scheme are as follows:
the preparation work of the configuration of the visual interface is used for summarizing the space-time big data, adopting different publishing services according to the data types, publishing the space-time big data to the network, and processing the space-time big data by a third-party platform on the network to construct a visual configuration component; the processing of the space-time big data is put on a professional processing platform for processing, so that the accuracy of data processing is improved, the data processing pressure of a client is reduced, and the running speed of the client is improved. The third-party data processing platform sends the processed visual configuration component back to the client; the client receives the association combination of the visual configuration components from the user to form a visual interface for publishing; the visual interface can be published to the front end, and other users can obtain access rights in a subscription mode and view the access rights through a browser. The component receives the service interface, for unsatisfied data, can filter the data through the script editor that the component carries on oneself; data among the components are transmitted in three dimensions x, y and z, and the consistency of data formats is guaranteed. The components are linked by monitoring data changes. As shown in fig. 3, is a visual interface after release.
In one embodiment, the data types include: one or more of raster data, image data, vector data, and structured data.
As shown in fig. 2, based on the data type, invoking the corresponding publishing service to publish the spatiotemporal big data, including;
when the data type is raster data or image data or vector data, the data is published as standard map service through arcg i s or hypergraph service;
and/or the presence of a gas in the gas,
when the data type is structured data, the data is issued through the rest service.
The working principle and the beneficial effects of the technical scheme are as follows:
and selecting a proper publishing mode according to the data type of the space-time big data to realize accurate publishing of the space-time big data.
In one embodiment, the visualization configuration component comprises: one or more of a map base component, a table component, a statistical map component and a button component.
Receiving configuration operation of a user on the visual configuration component, and forming a visual interface, wherein the configuration operation comprises the following steps:
acquiring a preset configuration operation interface;
receiving a first operation of a user on a corresponding first icon of the map basic component, and displaying the map basic component corresponding to the first icon to a configuration operation interface;
receiving a second operation of the user on a corresponding second icon of the table component, and displaying the table component corresponding to the second icon to the configuration operation interface;
receiving a third operation of position adjustment of the map basic component and/or the table component on the configuration operation interface by the user; and/or receiving a fourth operation of the user for adjusting the relative positions of the map basic component and the table component; and/or receiving a fifth operation of display size adjustment of the map basic component and/or the table component by the user; and/or, receiving a sixth operation of the user for adjusting the display parameter setting of the map basic component and/or the table component; and/or receiving a seventh operation of the user on the setting of the publishing attribute of the map basic component and/or the table component; and/or receiving an eighth operation of setting the subscription attribute of the map basic component and/or the table component by the user;
receiving the storage operation of a user, storing and releasing a configuration operation interface set by the user;
wherein the first operation comprises: selecting and/or dragging;
the second operation includes: selecting and/or dragging;
the third operation includes: selecting and dragging, or selecting and inputting;
the fourth operation includes: sequentially selecting;
the fifth operation includes: selecting and dragging, or selecting and inputting;
the sixth operation includes: selecting and inputting;
the seventh operation includes: selecting;
the eighth operation includes: and (4) selecting.
The working principle and the beneficial effects of the technical scheme are as follows:
during specific configuration, a preset configuration operation interface is divided into three parts, namely an effect display area positioned in the middle, visual configuration component display areas positioned on the left side and the right side of the effect display area and a parameter display area; the visual configuration components are displayed in a visual configuration component display area in a classified mode, the map basic components are displayed through first icons, and the table components are displayed through second icons; the first operation is selection and/or dragging, specifically, a first icon in a visual configuration component display area is selected in a clicking mode, a map basic component corresponding to the first icon is displayed at a preset position of an effect display area, dragging is a clicking mode and moves to the effect display area, and the map basic component corresponding to the first icon is displayed at the tail end of dragging; performing a third operation of adjusting the position of the map basic component and/or the table component on the configuration operation interface, specifically, clicking to select and drag the map basic component and/or the table component, or clicking to select and input a target coordinate value on the effect display area by a keyboard; the relative positions of the map basic component and the table component are mainly that the map basic component is arranged above the table component or the map basic component is displayed below the table component; a seventh operation of publishing the setting of the property for the map base component and/or the form component, and an eighth operation of subscribing to the setting of the property for the map base component and/or the form component; the components displayed in the effect display area are selected first, and then preset selectable items are selected in the parameter display area. The editing of the visual interface is realized through simple selection and dragging, and the editing efficiency is improved.
In one embodiment, before receiving a second operation of the user on a corresponding second icon of the form component, the method further comprises:
acquiring a first identification vector of a map basic component displayed to a configuration operation interface;
acquiring second identification vectors of all table components in the component database;
and calculating the association degree of the first identification vector and the second identification vector, wherein the calculation formula is as follows:
g is the association degree of the first identification vector and the second identification vector; a. theiA value of the ith data of the first identification vector; a. thejIs the value of the jth data of the first identification vector; b isiIs the value of the ith data of the second identification vector; b isjIs the value of the jth data of the second identification vector; n is the total number of data of the first identification vector or the second identification vector;
acquiring a second icon corresponding to the table component with the association degree larger than a preset association degree threshold;
constructing a selection list based on the second icon;
the selection list is delivered to the user.
The working principle and the beneficial effects of the technical scheme are as follows:
and after the user selects the map basic component, outputting a selection list of the associated icon components, and quickly selecting in the selection list by the user so as to improve the editing speed of the user on the visual interface. Calculating the degree of association through a preset first identification vector corresponding to the map basic component and a preset second identification vector corresponding to the table component, wherein the first identification vector can comprise time data, space data, item data set by a user and the like; the second identification vector may also include temporal data, spatial data, and user-set transaction data, among others.
In one embodiment, the third-party data processing platform processes published spatiotemporal big data, comprising:
acquiring a preset standard word bank;
identifying the space-time big data based on a preset standard word bank;
when the space-time big data has unidentified data; calculating the similarity between the data and each standard word in the standard word bank, and extracting the standard words with the similarity larger than a preset similarity threshold; constructing a suspected list;
outputting the suspected list to a user for selection;
and/or the presence of a gas in the gas,
publishing the suspected list on a third-party data processing platform, and receiving joint decisions of a plurality of users on the third-party data processing platform;
and/or the presence of a gas in the gas,
and screening the standard words in the suspected list based on the historical selection records of the user, and determining the standard words corresponding to the data.
The working principle and the beneficial effects of the technical scheme are as follows:
when the third-party data processing platform processes space-time big data and encounters data which cannot be identified, the suspected corresponding standard words can be determined firstly, and all the suspected standard words are placed in a suspected list to be identified through at least three ways; the first method is to send the suspected list and the corresponding data to the user, and the selection of the user is taken as the standard; the second method is that the suspected list and the corresponding data are published on a platform, and the joint decision of the user on the platform is received; and thirdly, screening is carried out according to historical selection records generated when the user adopts the first mode, and the accuracy of the third-party data processing platform in processing data is improved by coping with abnormal data during identification of the third-party data processing platform.
In one embodiment, the suspected list is published on a third-party data processing platform, and joint decisions of a plurality of users on the third-party data processing platform are received; the method comprises the following steps:
acquiring a support value of a support user corresponding to each standard word on the suspected list and a weight value of a corresponding user;
and determining a decision value whether each standard word is matched with the data or not based on the support value and the weight value, wherein a calculation formula of the decision value is as follows:
wherein J is a decision value; beta is aσThe weight value of the sigma-th user; dσA support value for the σ -th user; m is the total number of users supported by the standard words;
and comparing the decision value of each standard word in the suspected list, and acquiring the standard word with the maximum decision value as the standard word corresponding to the data.
The working principle and the beneficial effects of the technical scheme are as follows:
the user participates in the decision of the suspected list issued by the third-party data processing platform through the support value and the weight value; by adopting the principle of taking the cognition of most people as a benchmark; and providing support for the processing of the third-party data processing platform. The support value is configured by the third-party data processing platform according to the use condition of the user; and the weight value is configured according to the authority of the user on the third-party data processing platform.
In one embodiment, the component-based spatiotemporal big data visualization configuration method further comprises:
when the data determined by the joint decision of the plurality of users and the standard words are accurate in corresponding relation, carrying out up-regulation operation on the support values and/or weight values of the users supported by the standard words; the support value and/or the weight value of the user supported by other standard words in the suspected list are/is adjusted downwards;
wherein, the support value or weight value after the up-regulation operation is determined by the following formula:
in the formula, K' is a support value or a weight value adjusted by an up-regulation operation; k is a support value or a weight value before the adjustment of the up-regulation operation; theta is a preset adjusting amplitude value; theta0Supplementing value for the preset amplitude;
the support value or weight value after the down-regulation operation is determined by the following formula:
in the formula, k' is a support value or a weight value after being adjusted by down-regulation operation; k is a support value or a weight value before down-regulation operation adjustment; and when the support value or the weight value which is calculated by the formula and adjusted by the down-regulation operation is smaller than a preset lower limit value, the lower limit value is the support value or the weight value which is adjusted by the down-regulation operation.
The working principle and the beneficial effects of the technical scheme are as follows:
usage based on the decided result, for example: when the user uses the visual configuration component processed according to the decision, namely the visual configuration component is good, namely no abnormity occurs, the decision is correct, the support value or the weight value of the user participating in the decision is adjusted, and the accuracy of the next joint decision of the next third-party data processing platform is improved.
The invention also provides a component-based space-time big data visualization configuration system, which comprises:
the acquisition module is used for acquiring space-time big data to be processed;
the analysis module is used for analyzing the space-time big data and determining the data type;
the publishing module is used for calling corresponding publishing services to publish the space-time big data based on the data type;
the receiving module is used for receiving a visual configuration component which is obtained by processing the issued space-time big data by the third-party data processing platform;
and the configuration module is used for receiving the configuration operation of the visualization configuration component by the user and forming a visualization interface.
The working principle and the beneficial effects of the technical scheme are as follows:
the preparation work of the configuration of the visual interface is used for summarizing the space-time big data, adopting different publishing services according to the data types, publishing the space-time big data to the network, and processing the space-time big data by a third-party platform on the network to construct a visual configuration component; the processing of the space-time big data is put on a professional processing platform for processing, so that the accuracy of data processing is improved, the data processing pressure of a client is reduced, and the running speed of the client is improved. The third-party data processing platform sends the processed visual configuration component back to the client; the client receives the association combination of the visual configuration components from the user to form a visual interface for publishing; the visual interface can be published to the front end, and other users can obtain access rights in a subscription mode and view the access rights through a browser. The component receives the service interface, for unsatisfied data, can filter the data through the script editor that the component carries on oneself; data among the components are transmitted in three dimensions x, y and z, and the consistency of data formats is guaranteed. The components are linked by monitoring data changes.
In one embodiment, the data types include: one or more of raster data, image data, vector data, and structured data.
The issuing module executes the following operations;
when the data type is raster data or image data or vector data, the data is published as standard map service through arcgi s or hypergraph service;
and/or the presence of a gas in the gas,
when the data type is structured data, the data is issued through the rest service.
The working principle and the beneficial effects of the technical scheme are as follows:
and selecting a proper publishing mode according to the data type of the space-time big data to realize accurate publishing of the space-time big data.
In one embodiment, the visualization configuration component comprises: one or more of a map base component, a table component, a statistical map component and a button component.
The configuration module performs the following operations:
acquiring a preset configuration operation interface;
receiving a first operation of a user on a corresponding first icon of the map basic component, and displaying the map basic component corresponding to the first icon to a configuration operation interface;
receiving a second operation of the user on a corresponding second icon of the table component, and displaying the table component corresponding to the second icon to the configuration operation interface;
receiving a third operation of position adjustment of the map basic component and/or the table component on the configuration operation interface by the user; and/or receiving a fourth operation of the user for adjusting the relative positions of the map basic component and the table component; and/or receiving a fifth operation of display size adjustment of the map basic component and/or the table component by the user; and/or, receiving a sixth operation of the user for adjusting the display parameter setting of the map basic component and/or the table component; and/or receiving a seventh operation of the user on the setting of the publishing attribute of the map basic component and/or the table component; and/or receiving an eighth operation of setting the subscription attribute of the map basic component and/or the table component by the user;
receiving the storage operation of a user, storing and releasing a configuration operation interface set by the user;
wherein the first operation comprises: selecting and/or dragging;
the second operation includes: selecting and/or dragging;
the third operation includes: selecting and dragging, or selecting and inputting;
the fourth operation includes: sequentially selecting;
the fifth operation includes: selecting and dragging, or selecting and inputting;
the sixth operation includes: selecting and inputting;
the seventh operation includes: selecting;
the eighth operation includes: and (4) selecting.
The working principle and the beneficial effects of the technical scheme are as follows:
during specific configuration, a preset configuration operation interface is divided into three parts, namely an effect display area positioned in the middle, visual configuration component display areas positioned on the left side and the right side of the effect display area and a parameter display area; the visual configuration components are displayed in a visual configuration component display area in a classified mode, the map basic components are displayed through first icons, and the table components are displayed through second icons; the first operation is selection and/or dragging, specifically, a first icon in a visual configuration component display area is selected in a clicking mode, a map basic component corresponding to the first icon is displayed at a preset position of an effect display area, dragging is a clicking mode and moves to the effect display area, and the map basic component corresponding to the first icon is displayed at the tail end of dragging; performing a third operation of adjusting the position of the map basic component and/or the table component on the configuration operation interface, specifically, clicking to select and drag the map basic component and/or the table component, or clicking to select and input a target coordinate value on the effect display area by a keyboard; the relative positions of the map basic component and the table component are mainly that the map basic component is arranged above the table component or the map basic component is displayed below the table component; a seventh operation of publishing the setting of the property for the map base component and/or the form component, and an eighth operation of subscribing to the setting of the property for the map base component and/or the form component; the components displayed in the effect display area are selected first, and then preset selectable items are selected in the parameter display area. The editing of the visual interface is realized through simple selection and dragging, and the editing efficiency is improved.
In one embodiment, before receiving a second operation of the user on a corresponding second icon of the form component, the method further comprises:
acquiring a first identification vector of a map basic component displayed to a configuration operation interface;
acquiring second identification vectors of all table components in the component database;
and calculating the association degree of the first identification vector and the second identification vector, wherein the calculation formula is as follows:
g is the association degree of the first identification vector and the second identification vector; a. theiA value of the ith data of the first identification vector; a. thejIs the value of the jth data of the first identification vector; b isiIs the value of the ith data of the second identification vector; b isjIs the value of the jth data of the second identification vector; n is the total number of data of the first identification vector or the second identification vector;
acquiring a second icon corresponding to the table component with the association degree larger than a preset association degree threshold;
constructing a selection list based on the second icon;
the selection list is delivered to the user.
The working principle and the beneficial effects of the technical scheme are as follows:
and after the user selects the map basic component, outputting a selection list of the associated icon components, and quickly selecting in the selection list by the user so as to improve the editing speed of the user on the visual interface. Calculating the degree of association through a preset first identification vector corresponding to the map basic component and a preset second identification vector corresponding to the table component, wherein the first identification vector can comprise time data, space data, item data set by a user and the like; the second identification vector may also include temporal data, spatial data, and user-set transaction data, among others.
In one embodiment, the third-party data processing platform processes published spatiotemporal big data, comprising:
acquiring a preset standard word bank;
identifying the space-time big data based on a preset standard word bank;
when the space-time big data has unidentified data; calculating the similarity between the data and each standard word in the standard word bank, and extracting the standard words with the similarity larger than a preset similarity threshold; constructing a suspected list;
outputting the suspected list to a user for selection;
and/or the presence of a gas in the gas,
publishing the suspected list on a third-party data processing platform, and receiving joint decisions of a plurality of users on the third-party data processing platform;
and/or the presence of a gas in the gas,
and screening the standard words in the suspected list based on the historical selection records of the user, and determining the standard words corresponding to the data.
The working principle and the beneficial effects of the technical scheme are as follows:
when the third-party data processing platform processes space-time big data and encounters data which cannot be identified, the suspected corresponding standard words can be determined firstly, and all the suspected standard words are placed in a suspected list to be identified through at least three ways; the first method is to send the suspected list and the corresponding data to the user, and the selection of the user is taken as the standard; the second method is that the suspected list and the corresponding data are published on a platform, and the joint decision of the user on the platform is received; and thirdly, screening is carried out according to historical selection records generated when the user adopts the first mode, and the accuracy of the third-party data processing platform in processing data is improved by coping with abnormal data during identification of the third-party data processing platform.
In one embodiment, the suspected list is published on a third-party data processing platform, and joint decisions of a plurality of users on the third-party data processing platform are received; the method comprises the following steps:
acquiring a support value of a support user corresponding to each standard word on the suspected list and a weight value of a corresponding user;
and determining a decision value whether each standard word is matched with the data or not based on the support value and the weight value, wherein a calculation formula of the decision value is as follows:
wherein J is a decision value; beta is aσThe weight value of the sigma-th user; dσA support value for the σ -th user; m is the total number of users supported by the standard words;
and comparing the decision value of each standard word in the suspected list, and acquiring the standard word with the maximum decision value as the standard word corresponding to the data.
The working principle and the beneficial effects of the technical scheme are as follows:
the user participates in the decision of the suspected list issued by the third-party data processing platform through the support value and the weight value; by adopting the principle of taking the cognition of most people as a benchmark; and providing support for the processing of the third-party data processing platform. The support value is configured by the third-party data processing platform according to the use condition of the user; and the weight value is configured according to the authority of the user on the third-party data processing platform.
In one embodiment, the component-based spatiotemporal big data visualization configuration system further comprises:
an adjustment module that performs the following operations:
when the data determined by the joint decision of the plurality of users and the standard words are accurate in corresponding relation, carrying out up-regulation operation on the support values and/or weight values of the users supported by the standard words; the support value and/or the weight value of the user supported by other standard words in the suspected list are/is adjusted downwards;
wherein, the support value or weight value after the up-regulation operation is determined by the following formula:
in the formula, K' is a support value or a weight value adjusted by an up-regulation operation; k is a support value or a weight value before the adjustment of the up-regulation operation; theta is a preset adjusting amplitude value; theta0Supplementing value for the preset amplitude;
the support value or weight value after the down-regulation operation is determined by the following formula:
in the formula, k' is a support value or a weight value after being adjusted by down-regulation operation; k is a support value or a weight value before down-regulation operation adjustment; and when the support value or the weight value which is calculated by the formula and adjusted by the down-regulation operation is smaller than a preset lower limit value, the lower limit value is the support value or the weight value which is adjusted by the down-regulation operation.
The working principle and the beneficial effects of the technical scheme are as follows:
usage based on the decided result, for example: when the user uses the visual configuration component processed according to the decision, namely the visual configuration component is good, namely no abnormity occurs, the decision is correct, the support value or the weight value of the user participating in the decision is adjusted, and the accuracy of the next joint decision of the next third-party data processing platform is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A visual configuration method of space-time big data based on components is characterized by comprising the following steps:
acquiring space-time big data to be processed;
analyzing the space-time big data and determining the data type;
based on the data type, calling corresponding publishing service to publish the space-time big data;
receiving a visual configuration component which is processed by a third-party data processing platform on the issued space-time big data;
receiving configuration operation of a user on the visual configuration component to form a visual interface;
the third-party data processing platform processes the issued space-time big data, and the processing method comprises the following steps:
acquiring a preset standard word bank;
identifying the space-time big data based on a preset standard word bank;
when the large spatio-temporal data has unidentified data; calculating the similarity between the data and each standard word in the standard word bank, and extracting the standard words with the similarity larger than a preset similarity threshold; constructing a suspected list;
outputting the suspected list to a user for selection;
and/or the presence of a gas in the gas,
publishing the suspected list to the third-party data processing platform, and receiving joint decisions of a plurality of users on the third-party data processing platform;
and/or the presence of a gas in the gas,
and screening the standard words in the suspected list based on the historical selection records of the user, and determining the standard words corresponding to the data.
2. The component-based spatiotemporal big data visualization configuration method of claim 1, wherein the data types comprise: one or more of raster data, image data, vector data, and structured data.
3. The component-based spatio-temporal big data visualization configuration method according to claim 2, wherein the invoking of the corresponding publishing service based on the data type publishes the spatio-temporal big data comprising;
when the data type is the raster data or the image data or the vector data, the data is issued to be a standard map service through an arcgis or hypergraph service;
and/or the presence of a gas in the gas,
and when the data type is structured data, issuing the data through a rest service.
4. The component-based spatiotemporal big data visualization configuration method of claim 1, wherein the visualization configuration component comprises: one or more of a map base component, a table component, a statistical map component and a button component.
5. The component-based spatiotemporal big data visualization configuration method according to claim 4, wherein the receiving of the configuration operation of the visualization configuration component by the user forms a visualization interface, comprising:
acquiring a preset configuration operation interface;
receiving a first operation of a user on a corresponding first icon of the map basic component, and displaying the map basic component corresponding to the first icon to the configuration operation interface;
receiving a second operation of a user on a corresponding second icon of the table component, and displaying the table component corresponding to the second icon to the configuration operation interface;
receiving a third operation of position adjustment of the map basic component and/or the table component on the configuration operation interface by a user; and/or receiving a fourth operation of adjusting the relative position of the map base component and the table component by the user; and/or receiving a fifth operation of display size adjustment of the map basic component and/or the table component by a user; and/or, receiving a sixth operation of the user for adjusting the display parameter setting of the map basic component and/or the table component; and/or receiving a seventh operation of a user on the setting of the publishing attribute of the map base component and/or the table component; and/or receiving an eighth operation of setting the subscription attribute of the map basic component and/or the table component by the user;
receiving the storage operation of a user, storing and releasing a configuration operation interface set by the user;
wherein the first operation comprises: selecting and/or dragging;
the second operation includes: selecting and/or dragging;
the third operation includes: selecting and dragging, or selecting and inputting;
the fourth operation includes: sequentially selecting;
the fifth operation includes: selecting and dragging, or selecting and inputting;
the sixth operation includes: selecting and inputting;
the seventh operation includes: selecting;
the eighth operation includes: and (4) selecting.
6. The component-based spatiotemporal big data visualization configuration method of claim 5, further comprising, prior to receiving a second operation by a user on a corresponding second icon of the form component:
acquiring a first identification vector of the map basic component displayed to the configuration operation interface;
acquiring second identification vectors of all table components in a component database;
calculating the association degree of the first identification vector and the second identification vector, wherein the calculation formula is as follows:
wherein G is the association degree of the first identification vector and the second identification vector; a. theiIs the value of the ith data of the first identification vector; a. thejIs the value of the jth data of the first identification vector; b isiIs the value of the ith data of the second identification vector; b isjIs the value of the jth data of the second identification vector; n is the total number of data of the first identification vector or the second identification vector;
acquiring a second icon corresponding to the table component with the association degree larger than a preset association degree threshold;
building a selection list based on the second icon;
and transmitting the selection list to a user.
7. The component-based spatiotemporal big data visualization configuration method according to claim 1, characterized in that the suspected list is published on the third-party data processing platform, and joint decisions of a plurality of users on the third-party data processing platform are received; the method comprises the following steps:
acquiring a support value of a support user corresponding to each standard word on the suspected list and a weight value of a corresponding user;
determining a decision value whether each standard word is matched with the data or not based on the support value and the weight value, wherein the calculation formula of the decision value is as follows:
wherein J is the decision value; beta is aσThe weight value of the sigma-th user; dσA support value for the σ -th user; m is the total number of users supported by the standard words;
and comparing the decision values of all the standard words in the suspected list, and acquiring the standard word with the maximum decision value as the standard word corresponding to the data.
8. The component-based spatiotemporal big data visualization configuration method of claim 7, further comprising:
when the data determined by the joint decision of the plurality of users and the corresponding relation of the standard words are accurate, carrying out up-regulation operation on the support value and/or the weight value of the user supported by the standard words; performing down-regulation operation on the support value and/or weight value of the user supported by other standard words in the suspected list;
wherein the support value or the weight value after the up-regulation operation is determined by the following formula:
in the formula, K' is the support value or weight value adjusted by the up-regulation operation; k is the support value or the weight value before the adjustment of the up-regulation operation; theta is a preset adjusting amplitude value; theta0Supplementing value for the preset amplitude;
q is the sum of the support values or the sum of the weight values of all users participating in the decision; when the support value or the weight value which is calculated by a formula and adjusted by the up-regulation operation is larger than a preset upper limit value, taking the upper limit value as the support value or the weight value which is adjusted by the up-regulation operation;
the support or weight value after the down-regulation operation is determined by the following formula:
wherein k' is the support value or the weight value after being adjusted by the down-regulation operation; k is the support value or the weight value before the down-regulation operation is adjusted; and when the support value or the weight value which is calculated by a formula and adjusted by the down-regulation operation is smaller than a preset lower limit value, taking the lower limit value as the support value or the weight value which is adjusted by the down-regulation operation.
9. A component-based spatiotemporal big data visualization configuration system, comprising:
the acquisition module is used for acquiring space-time big data to be processed;
the analysis module is used for analyzing the space-time big data and determining the data type;
the publishing module is used for calling corresponding publishing services to publish the space-time big data based on the data type;
the receiving module is used for receiving a visual configuration component which is processed by the third-party data processing platform on the issued space-time big data;
the configuration module is used for receiving the configuration operation of the visualization configuration component by a user to form a visualization interface;
the third-party data processing platform processes the issued space-time big data, and the processing method comprises the following steps:
acquiring a preset standard word bank;
identifying the space-time big data based on a preset standard word bank;
when the large spatio-temporal data has unidentified data; calculating the similarity between the data and each standard word in the standard word bank, and extracting the standard words with the similarity larger than a preset similarity threshold; constructing a suspected list;
outputting the suspected list to a user for selection;
and/or the presence of a gas in the gas,
publishing the suspected list to the third-party data processing platform, and receiving joint decisions of a plurality of users on the third-party data processing platform;
and/or the presence of a gas in the gas,
and screening the standard words in the suspected list based on the historical selection records of the user, and determining the standard words corresponding to the data.
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