CN117520350A - Big data platform construction method combining digital twin and space-time technology - Google Patents

Abstract

The application provides a big data platform construction method combining digital twin and space-time technology, belonging to the big data technical field. The platform constructed by the method is used for carrying out dimension and index adaptation and enhancement on the basis of a traditional two-dimensional chart, and can realize multi-level expansion of the multi-dimensional tension space of data, expansion of the expressive force of time dimension, and real-time driving and tracing of the change of the data by combining a map and a digital twin technology. The method comprises the following steps: environmental deployment, data initialization, application development, service release, deployment of Web applications, multi-data source configuration based on business topics and the like.

Description

Big data platform construction method combining digital twin and space-time technology

Technical Field

The application relates to the technical field of big data, in particular to a big data platform construction method combining digital twin and space-time technology.

Background

In the information society, how to intuitively analyze, display, track and compare massive data is a difficult problem faced in the field of big data, and the difficult problems are specifically expressed in the following aspects:

1. a traditional two-dimensional chart has dimensions and indexes which are fixed and unchangeable: when the data panel is analyzed, if several dimensions are to be added or removed or several indexes are to be temporarily added, the code is required to be modified and reissued because the code is solidified and the traditional two-dimensional chart cannot be done.

2. Traditional two-dimensional charts, whose dimension levels are fixed, cannot be drilled or aggregated: in the data table, the index values recorded in each row are grouped and counted according to each dimension, and the effect of data exertion is greatly reduced because the index values cannot be drilled downwards or aggregated upwards under the condition that a certain dimension has a plurality of layers.

3. The three-dimensional real scenes in the real world cannot be fused, and the image perception is difficult: traditional data display has no capability to incorporate digital twinning technology, and 3D models of roads, buildings, villages, mountain forests and the like are introduced. For data depending on the surrounding environment, such as hydraulic pipe network, gas pipe network, crop planting and the like, planning and data statistics of the data cannot be intuitively analyzed by combining with the field scene.

4. The spatial data is dimension reduced, and the distribution of the spatial data cannot be intuitively perceived: traditional data display is not combined with a GIS technology, and space vector data is not displayed in a good mode, so that the space dimension of the data is lost, and the difficulty of understanding the data is increased.

5. The time dimension is tapped and the change of the data cannot be perceived visually: traditional data presentation treats the time dimension together with the normal business dimension, sometimes even discarded, resulting in serious underestimation of the effect thereof, ignoring the continuous change of time fluidity to the data.

Disclosure of Invention

In order to solve at least one technical problem in the background art, the embodiment of the application provides a large data platform construction method combining digital twinning and space-time technology. Performing dimension and index adaptation and enhancement on the basis of a traditional two-dimensional chart; and combining a map and a digital twin technology, expanding multidimensional tension space of data in a multi-level manner, expanding expressive force of time dimension, and driving and tracing the change of the data in real time. The method can be effectively applied to various industries such as smart cities, business intelligence, finance, electronic government affairs, geographic information and the like.

The big data platform construction method combining digital twin and space-time technology provided by the embodiment of the application comprises the following steps:

first step, environment deployment:

preparing a client machine;

constructing a space database for storing space data;

building a relational database for storing relational data;

constructing a file server for storing 3D model data;

building a map server, wherein the map server is used for publishing WMS service, WMTS service and TMS service;

building a Web server, wherein the Web server is used for publishing 3D model data, web application and providing http service and https service;

setting up an application server, wherein the application server is a micro-service cluster and is used for developing a configuration center and providing an API (application program interface) comprising query services, newly added services, deleted services, modified services and release services of each theme;

second, initializing data:

preparing management subject related data including spatial data, 3D model data and relationship data;

thirdly, application development:

the configuration center develops a back-end application program by adopting a cloud native and micro-service architecture;

developing a visualization center, developing a front-end application program, adopting a vue or reaction frame, and integrating a Web map;

fourth step, service release:

releasing WMS/WMTS service, entering a map server, and releasing various topics into WMS or WMTS;

issuing an http service, entering a Web server, and issuing a catalog in which the 3D model is located into the http service according to a project area;

issuing a micro service: the configuration center develops, packages and uploads the test completion to the micro service cluster, registers the service to the registration center, and provides API call to the outside through the gateway;

fifth, deploying Web application:

after the development and the test of the visual center are completed, packaging and uploading the visual center to a Web service cluster environment, configuring load balancing, providing a unified Web address, and accessing the visual center through a browser;

sixth, multiple data sources based on business theme are configured: aiming at each service theme, the data sources of all sources are dynamically configured in three panels of a layer, a theme and customization, each panel is organized in a tree form, and the data are finally integrated in a visual center area for centralized display.

In one possible implementation manner, in the sixth step, the configuration of the multiple data sources includes a spatial data configuration, and the steps of the spatial data configuration are as follows:

preparing space data and storing the space data into a space database;

building a map server environment;

publishing a WMS or WMTS map service in a map server;

and entering a layer panel of the visualization center, and configuring a corresponding layer for the service.

In one possible implementation manner, the layer configured by the big data platform construction method combining digital twin and space-time technology provided by the embodiment of the application includes layer name, layer link, longitude, latitude, altitude and service type.

In one possible implementation manner, in the method for constructing a large data platform combining digital twin and space-time technology provided in the embodiment of the present application, in the sixth step, the configuration of multiple data sources includes 3D model data configuration, and the steps of the 3D model data configuration are as follows:

3D modeling is carried out through AutoCAD or unmanned aerial vehicle oblique photography, and the model is stored in a file server;

building a Web server environment;

publishing the 3D model as an http service;

and entering a layer panel of the visualization center, and configuring a corresponding layer for the service.

In one possible implementation manner, in the sixth step, the multi-data source configuration includes a relationship data configuration, and the steps of the relationship data configuration are as follows:

preparing relation data, and extracting service data to a plurality of bins through an ETL tool;

and entering a theme panel of the visualization center to perform theme configuration.

In one possible implementation manner, the big data platform construction method combining digital twin and space-time technology provided by the embodiment of the application, the subject to be configured includes a data source, a table, a field, a display name, a formatting definition, a picture, a dimension definition, an index definition and a space marker of the query.

In one possible implementation manner, in the sixth step, the method for constructing a large data platform combining digital twin and space-time technology provided in the embodiment of the present application, the multiple data source configuration includes a custom data configuration, and the steps of the custom data configuration are as follows:

developing a personalized interface aiming at the data which cannot be dynamically configured for display;

and entering a customization panel of the visualization center, and performing theme configuration, wherein the theme to be configured comprises names and url.

The invention has the beneficial effects that:

according to the invention, different data are respectively issued into corresponding services through integrating data sources, and then are integrated in the data panel and the map through the visual center for simultaneous presentation, so that the traditional big data thinking limitation is eliminated, and the advantages are shown in:

1. visual and clear: the map can display space data in a visual mode, so that people can intuitively know information such as geographic positions, distances, distribution and the like, and the data can be understood and analyzed more easily.

2. True and accurate: the 3D model can present data in a real and stereoscopic mode, and can better restore objects or scenes represented by the data, so that an observer can more accurately perceive and understand the data. Through the 3D model, the viewing angle and the angle of observation can be freely selected, data can be observed from different angles, and more information and details can be obtained. Meanwhile, through interactive operation, the observer can also change the view angle, zoom, roaming and the like of the model, interact with the data, and explore and analyze the data more deeply.

3. Flexible and fine: by drilling dimensions, more flexible and fine data analysis can be performed, details of the data can be penetrated layer by layer, hidden modes and trends can be found, and more accurate analysis and decision making can be performed based on the subdivided data.

4. Retrospective change: by adjusting the change of the time dimension, the change trend and the dynamic condition of the data can be monitored and fed back in real time, and the time correlation mode and the trend in the data are revealed. Historical data can be traced back and past trends and associations and causes and results of the results analyzed.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

FIG. 1 is a technical flow implementation diagram of a large data platform construction method combining digital twinning and space-time techniques according to an embodiment of the present application;

FIG. 2 is a schematic diagram of an environmental deployment architecture of a large data platform construction method combining digital twinning and spatio-temporal techniques according to an embodiment of the present application;

FIG. 3 is a schematic diagram of entity-relationship (E-R) related to a business entity in a large data platform construction method combining digital twinning and space-time technology according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a multi-dimensional analysis query main interface design of a visualization center in a large data platform construction method combining digital twinning and space-time technology according to an embodiment of the present application;

fig. 5 is a schematic diagram of an effect of a layer tree configuration in a method for constructing a big data platform combining digital twin and space-time technology according to an embodiment of the present application.

Detailed Description

In big data technology and application, how to restore real time and space dimensions of data, and to construct a data analysis and display platform obtained immediately after finding is always in active exploration and continuous improvement. With the development of GIS, various open sources, commercial products are continuously emerging, and the desktop GIS era is gradually transited to the Web GIS. The continual advances in high performance computing and simulation techniques have enabled digital twinning techniques to accurately simulate and simulate physical systems.

How to intuitively analyze, display, track and compare massive data is a difficult problem faced in the field of big data, and the difficult problems are specifically expressed in the following aspects:

1. a traditional two-dimensional chart has dimensions and indexes which are fixed and unchangeable: when the data panel is analyzed, if several dimensions are to be added or removed or several indexes are to be temporarily added, the code is required to be modified and reissued because the code is solidified and the traditional two-dimensional chart cannot be done.

2. Traditional two-dimensional charts, whose dimension levels are fixed, cannot be drilled or aggregated: in the data table, the index values recorded in each row are grouped and counted according to each dimension, and the effect of data exertion is greatly reduced because the index values cannot be drilled downwards or aggregated upwards under the condition that a certain dimension has a plurality of layers.

3. The three-dimensional real scenes in the real world cannot be fused, and the image perception is difficult: traditional data display has no capability to incorporate digital twinning technology, and 3D models of roads, buildings, villages, mountain forests and the like are introduced. For data depending on the surrounding environment, such as hydraulic pipe network, gas pipe network, crop planting and the like, planning and data statistics of the data cannot be intuitively analyzed by combining with the field scene.

4. The spatial data is dimension reduced, and the distribution of the spatial data cannot be intuitively perceived: traditional data display is not combined with a GIS technology, and space vector data is not displayed in a good mode, so that the space dimension of the data is lost, and the difficulty of understanding the data is increased.

5. The time dimension is tapped and the change of the data cannot be perceived visually: traditional data presentation treats the time dimension together with the normal business dimension, sometimes even discarded, resulting in serious underestimation of the effect thereof, ignoring the continuous change of time fluidity to the data.

Based on the above, the embodiment of the application provides a large data platform construction method combining digital twin and space-time technology, the platform constructed by the method is used for carrying out dimension and index adaptation and enhancement on the basis of a traditional two-dimensional chart, and the multi-dimensional tension space of multi-level expansion data, the expressive force of time dimension and real-time driving and tracing of data change can be realized by combining a map and the digital twin technology.

The implementation of the examples of the present application will be described in detail below with reference to the accompanying drawings.

The embodiment of the application provides a big data platform construction method combining digital twin and space-time technology, which is characterized by comprising the following steps:

first step, environment deployment:

preparing a client machine;

constructing a space database for storing space data;

building a relational database for storing relational data;

constructing a file server for storing 3D model data;

building a map server, wherein the map server is used for publishing WMS service, WMTS service and TMS service;

building a Web server, wherein the Web server is used for publishing 3D model data, web application, providing http service and https service;

setting up an application server, wherein the application server is a micro-service cluster and is used for developing a configuration center and providing an API (application program interface) comprising query services, newly added services, deleted services, modified services and release services of each theme;

second, initializing data:

preparing management subject related data including spatial data, 3D model data and relationship data;

thirdly, application development:

the configuration center develops a back-end application program by adopting a cloud native and micro-service architecture;

the visual center develops, develops a front-end application program, adopts a vue or reaction frame, and integrates a Web map;

fourth step, service release:

releasing WMS/WMTS service, entering a map server, and releasing various topics into WMS or WMTS;

issuing an http service, entering a Web server, and issuing a catalog in which the 3D model is located into the http service according to a project area;

issuing a micro service: the configuration center develops, packages and uploads the test completion to the micro service cluster, registers the service to the registration center, and provides API call to the outside through the gateway;

fifth, deploying Web application:

after the development and the test of the visual center are completed, packaging and uploading the visual center to a Web service cluster environment, configuring load balancing, providing a unified Web address, and accessing the visual center through a browser;

sixth, multiple data sources based on business theme are configured: aiming at each service theme, the data sources of all sources are dynamically configured in three panels of a layer, a theme and customization, each panel is organized in a tree form, and the data are finally integrated in a visual center area for centralized display.

Wherein the multiple data source configuration comprises a spatial data configuration, the steps of the spatial data configuration are as follows:

preparing space data and storing the space data into a space database;

building a map server environment;

publishing a WMS or WMTS map service in a map server;

and a layer panel entering the visualization center configures a corresponding layer for the service, wherein the layer to be configured comprises a layer name, a layer link, longitude, latitude, altitude and service type.

Wherein the multiple data source configuration comprises a 3D model data configuration, the steps of the 3D model data configuration are as follows:

3D modeling is carried out through AutoCAD or unmanned aerial vehicle oblique photography, and the model is stored in a file server;

building a Web server environment;

publishing the 3D model as an http service;

and entering a layer panel of the visualization center, and configuring a corresponding layer for the service.

Wherein the multiple data source configuration comprises a relationship data configuration, the relationship data configuration comprising the steps of:

preparing relation data, and extracting service data to a plurality of bins through an ETL tool;

and entering a theme panel of the visualization center to perform theme configuration. The topics that are configured include the data sources, tables, fields, display names, formatting definitions, pictures, dimension definitions, index definitions, and spatial labels of the query.

Wherein the multiple data source configuration comprises a custom data configuration, the steps of the custom data configuration being as follows:

developing a personalized interface aiming at the data which cannot be dynamically configured for display;

and entering a customization panel of the visualization center, and performing theme configuration, wherein the theme to be configured comprises names and url.

In the technical scheme, the object to be analyzed and displayed for big data defines the granularity of the business theme in the industries of smart cities, business intelligence, finance and the like. Business topics, abbreviated as topics, refer to a class of business requirements defined and constructed to achieve a particular business objective and solve business problems, and are typically spread around a particular business domain.

The map layer refers to spatial data and 3D model data related to a theme, and after being released through a related Service such as WMS, WMTS, HTTP Service, etc., the theme data of the map can be loaded, scaled, rotated, and manipulated.

Spatial data, 3D model data, relational data, and these three types of data cover almost all data sources to which the subject is exposed.

The spatial data is the spatial geographic position distribution of the subject, is vector data such as points, lines or planes, and contains longitude, latitude, altitude, a coordinate system and other information.

The 3D model data is the surrounding environment information to be displayed by the theme, is used for modeling the 3D digital of the real world, and has huge information quantity.

The relation data is the business data of the theme and is the core data of the display and analysis.

After extraction, conversion and cleaning, the three types of data are released into corresponding services through different servers, and finally are displayed in a centralized manner in the same Web application, namely a visual center for analysis and decision. Referring to fig. 1, the "technical flowchart implementation" describes the series of procedures, and is described as follows:

1. software environment:

(1) database server:

spatial databases, such as open source PostgreSQL, for storing spatial data;

relational databases, such as Mysql, for storing relational data;

file servers, such as ftp, ssh, etc., are used to store 3D model data.

(2) The application server:

map servers, such as GeoServer, mapServer, arcgisServer, for publishing WMSs (web map services), or WMTS (web map tile services), TMS (tile map services), etc.;

a Web server, such as nginx, for publishing 3D model data, a Web application (a visualization center), and providing http, https, and other services;

(3) visualization center:

one Web application cluster needs to integrate a three-dimensional map frame and can select CesiumJS;

various base maps such as a sky map, a high-altitude map, a hundred-degree map, a Tencel map and the like can be supported;

providing a layer, a theme, a customized three-large configuration panel and a map, and displaying two data panels;

the method can perform the functions of measurement, space analysis, pattern spot inquiry, data change driven by time, dimension drill-down and aggregation, dynamic increase and decrease of dimensions and indexes, dynamic transformation of diagrams and the like.

(4) Configuration center: and a micro service cluster for providing APIs of inquiring, adding, deleting, modifying, releasing and the like of each theme.

2. Multi-data source configuration based on business topic

For any business theme, the data sources of all sources can be dynamically configured in three panels of a layer, a theme and customization, each panel is organized in a tree form, and the data is finally integrated in a visual center area for centralized display.

2.1 spatial data:

(1) preparing space data and storing the space data into a space database;

(2) building a map server environment;

(3) map services such as WMS or WMTS are released in a map server;

(4) and entering a visual center-layer panel, configuring corresponding layers for the Service released above, wherein the layers comprise layer names, layer links, longitudes, latitudes, altitudes, service types (WMS/WMTS/3 DTiles services) and the like, and modifying, deleting, dragging and sorting the configured layers and setting transparency.

(5) Clicking the layer node on the tree can be seen in the map display area of the visual center, and a plurality of layers can be displayed in a superposition mode.

2.2 3D model data configuration:

(1) 3D modeling is carried out through AutoCAD or unmanned aerial vehicle oblique photography, and the model is stored in a file server;

(2) building a Web server environment;

(3) publishing the 3D model as an http service;

(4) entering a visual center-layer panel, and configuring a corresponding layer for service;

(5) clicking the layer node on the tree can be seen in the map display area of the visual center, and a plurality of layers can be displayed in a superposition mode.

2.3 configuration of relational data:

(1) preparing relation data, and extracting service data to a plurality of bins through an ETL tool;

(2) entering a visual center-theme panel to perform theme configuration, wherein the theme configuration comprises a data source, a table, a field, a display name, a formatting definition, a picture, a dimension definition, an index definition, a space mark and the like of a query;

(3) clicking on the subject node on the tree may display a two-dimensional chart in the data panel of the visualization center.

2.4 custom data configuration:

(1) for special data, the display cannot be dynamically configured, and a personalized interface is developed;

(2) entering a visual center-custom panel for subject configuration including names, url and the like;

(3) clicking the custom node on the tree can be seen in the map display area of the visualization center, and multiple layers can be displayed in a superposition mode.

3. Spatiotemporal analysis based on business topics

For any business theme, all data sources under the theme can be displayed in the map and data panel area of the visual center. The map panel can display two-dimensional and three-dimensional space data and time data, and the data panel displays two-dimensional tables and statistical figures.

3.1 spatial data analysis

(1) All thematic layers of the service theme are displayed in a superposition mode on a map panel of the visual center;

(2) when clicking or framing a certain map spot, the attribute information of a plurality of map layers of the area can be displayed simultaneously; at the same time, the position of the three-dimensional layer window is refreshed; the chart of the data panel will also change accordingly;

(3) clicking the toolbar to measure, including length, area and elevation;

(4) the space analysis can be carried out to carry out the containing and intersecting inquiry and count the number and the area of the complete pattern spots in the area;

(5) clicking play in the time column can check the change condition of data in a certain period of time, and the play speed can be adjusted.

3.2 3D model analysis:

(1) superposing and displaying all thematic layers and 3D model data under the service theme on a map panel of a visual center;

(2) the method can scale, balance, rotate and 3D roam, click on a certain object of the model, and display the attribute of the object;

(3) two-dimensional and three-dimensional linkage analysis can be performed through multiple windows;

(4) the WebXR is turned on and a 3D immersive experience is possible.

3.3 analysis of relational data:

(1) displaying a two-dimensional table and a statistical graph of the service theme on a data panel of the visual center;

(2) clicking a record to synchronously locate two-dimensional and three-dimensional data in the map panel;

(3) the dimension drilling and shrinking operation can be carried out on the two-dimensional table;

(4) dimension replacement, index replacement, paging inquiry and sequencing operations can be performed;

(5) the graph can be switched into a plurality of forms such as a pie chart, a column, a broken line, 3D and the like;

(6) clicking play in the time column can check the change condition of data in a certain period of time, and the play speed can be adjusted.

The technical scheme combines GIS, MDX and digital twin technology, can be a multi-dimensional and 3D three-dimensional data display solution, and is mainly characterized in that:

1. chart drilling and replacing: by means of MDX technology, based on the traditional two-dimensional table and two-dimensional graph, the dynamic configuration of data dimension and data index can be carried out, and the functions of dynamic addition, deletion, condition filtering, dimension drilling, position transformation, graph transformation and the like are realized.

2. 3D model assistance: 3D modeling is carried out on the real ground object environment by means of a digital twin technology, and accurate positioning and digital reproduction are carried out on a map; the method and the system realize real-time interaction with the real-world data source, dynamically adjust the data display mode and the view angle according to personal requirements, and further help users to conduct multi-view data analysis.

3. Web map marking: introducing a map technology, and taking the spatial position and shape of the data as a layer to be displayed in a superposition way; the data may be subjected to geographic visualization, spatial analysis, location clustering, and the like. The spatial dimension may also help the user find geographically relevant trends and patterns, such as differences between regions, hot spot areas, etc.

Referring to fig. 2, the following describes the implementation process by taking the subject of "business body" as an example. The management subject refers to a professional large household, a family farm, a peasant cooperation agency, a related farming enterprise and the like in rural economic organizations. The main attributes include social credit code, organization name, legal representative, registered capital, region, land number, project area, land border, planting area, agricultural product classification, planting variety, land use type, reporting time, remarks, etc.

The first step: environmental deployment (deployment architecture diagram see fig. 2).

Preparing a client machine;

building a map server, a Web server and an application server;

and constructing a space database, a file server and a relational database.

And a second step of: and initializing data.

Data relating to the business entity is prepared, which includes three main categories:

1. spatial data: the management subject related thematic layer data, such as land block themes, contracture themes, homeland themes and rice themes, are prepared in a shape format, and then imported into a spatial database.

2. 3D model data: the unmanned aerial vehicle is used for oblique photography, high-precision pictures of the geographical environment of a designated county and a project area are flown out, a 3D files format file is formed through 3D modeling, and the files are uploaded to a file server, in this example, the project area.

3. Relationship data: and after the source layer data are processed through the dimension layer and the detail layer, summarizing the processed source layer data into an application layer data bin. The entity-relationship (E-R) related to the management entity is shown in FIG. 3:

and a third step of: and (5) application development.

1. Configuration center development:

the back-end application program adopts cloud native and micro-service architecture, and the functions comprise:

the business theme service API comprises creation, inquiry, modification and deletion of a theme;

the theme view service API comprises creation, modification, deletion and loading of views;

a theme dimension services API;

a subject index service API;

a theme mark service API;

a layer service API;

2. visualization center development:

the front-end application adopts vue or react frames to integrate the Web map, and the main interface is shown in the multi-dimensional analysis query main interface design diagram of figure 4.

Fourth step: and (5) service release.

1. Publishing WMS/WMTS services: entering a map server GeoServer, and publishing the land block themes and the contractual land themes into WMSs; and publishing the homeland themes and the rice themes into WMTS.

2. Publishing http service: entering a Web server nginx, and publishing the catalogue where the 3Dtiles model is located into an http service according to the project area.

3. Issuing a micro service: after the development and test of the configuration center are completed, packaging and uploading the configuration center to a micro service cluster environment, registering the service to a registration center, and uniformly providing API call to the outside through a gateway.

Fifth step: the Web application is deployed.

After the development and testing of the visual center are completed, the visual center is packaged and uploaded to a Web service cluster environment, load balancing is configured, unified Web addresses are provided, and access is performed through a browser.

Sixth step: layer and theme configuration.

1. Layer configuration:

adding a layer: including layer name, layer link, default exposed longitude, latitude, altitude, service type (WMS/WMTS/3 DTiles Service), attribute description, picture field, picture Service address, upper layer. The saved tree structure can be displayed according to the hierarchical directory.

Layer attribute modification: the value of any layer attribute may be modified;

layer deletion: deleting the designated nodes on the layer tree;

layer movement: dragging the tree node, and changing the position of the tree node;

layer tree view preservation: some nodes in the layer tree can be stored as a new tree, which is convenient for the tree node to check.

Layer tree view loading: the saved tree view may be selected by a drop down, some selected, and all nodes of the view tree loaded.

Layer configured effects see fig. 5:

2. theme configuration:

adding a theme: including the name of the topic, the data source, the table name, and the superior topic. The saved tree structure can be displayed according to the hierarchical directory.

Theme attribute modification: the value of any subject property may be modified;

theme deletion: deleting the designated nodes on the theme tree;

theme movement: dragging the tree node, and changing the position of the tree node;

theme tree view preservation: some nodes in the subject tree can be stored as a new tree, which is convenient for the tree nodes to check.

Theme tree view loading: the saved tree view may be selected by a drop down, some selected, and all nodes of the view tree loaded.

Maintenance of theme dimension:

the functions include dimension addition, deletion and modification.

The dimension attributes are: name, field name.

The present example configures three dimensions for the business entity: variety, region and period correspond to e-r attribute planting variety, region and reporting time in the third step.

Maintaining the theme indexes:

the functions include index addition, deletion and modification.

The index attributes are: name, field name.

The present example configures three indicators for the business entity: the land quantity, the area and the main body quantity correspond to the e-r attribute land blocks (numbers and areas) and the involved agriculture enterprises (total amount of assembly) in the step 3.

Topic marking maintenance:

the functions include tag addition, deletion, modification.

The marking attributes are: name, type (point, line, face), field name.

The present example provides a business entity with a tag: and (3) the block boundary corresponds to the e-r attribute block boundary in the step 3.

The effect of the subject after configuration is shown in the multi-dimensional analysis query main interface design diagram in fig. 4.

Seventh step: and (5) query analysis.

1. Two-dimensional chart:

clicking the management topic node on the topic tree, and displaying the two-dimensional data summarization table and graph of the topic on the right data panel.

Front end API

/>

2. Dimension drilling:

in the two-dimensional table, the first row defaults to display all varieties, all areas, all periods, the number of summarized land areas, the summarized area and the number of summarized main bodies.

Clicking the "+" sign before all varieties can expand all sub varieties below the "+" sign, and can be sequentially expanded according to the hierarchy; after expansion, an MDX (multi-dimensional query) statement is generated, and the results of the indexes in the list are updated after the MDX statement is executed through the API. The MDX statement is as follows:

/>

clicking the "+" sign before all areas can be sequentially unfolded according to administrative division levels;

clicking the "+" sign before all cycles can be expanded according to the date;

3. dimension substitution:

clicking the right drop-down arrow of the gauge head variety can select deletion and addition.

Deleting the dimension of the variety;

the addition then selects, from among the three dimensions defined by the business body theme, only those dimensions that are not present in the header, of course.

Operating the same variety in regional and periodic dimensions;

4. index replacement:

clicking the pull-down arrow on the right side of the header block can select deletion and addition.

Deleting the land block indexes when deleting;

the addition is then optionally one of the three indices defined by the subject matter of the business, of course only the index that is not present in the header can be selected.

The operation of the area and the main body is same as that of a land block;

5. dimension and index exchange:

pressing the left button of the mouse can drag and drop any dimension to the left or right of other dimensions, and the gauge head position of the dimension is changed;

index operation is in the same dimension;

6. graph replacement: the 'switch' button at the upper right corner of the graphic column is selected, and different graphics can be selected by pulling down, so that the data of the current two-dimensional table can be represented by the graphics such as a line break, a column, a scattered point and the like.

7. Map marking:

selecting management subject nodes of a subject tree, and displaying the plot boundary map spots of each subject in a map by default;

switching to the layer page at the left side panel, selecting the nodes on the corresponding layer tree, such as homestead themes, superposing the themes on a map for display, and comparing the areas and the quantity of land blocks and homesteads;

selecting project area nodes on the layer tree, and loading a digital twin 3D image map on the map;

8. time driving:

setting a time range on a time axis according to the minimum value and the maximum value of the period;

clicking the play button, starting from the minimum period by default, periodically sending an inquiry request API to the back-end micro-service, updating the map mark according to the response result, and seeing the real-time change of the data.

Clicking the back button, starting from the maximum period by default, periodically sending an inquiry request API to the back-end micro-service, updating the map mark according to the response result, and tracing the historical change rule of the data.

The time-driven code logic is as follows:

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9. map spot query:

clicking a certain map spot on the map, and popping up the map spot from the left column to obtain detailed information;

if the image spot is overlapped with a plurality of image layers, displaying information of the image spot in all the image layers in a tab page mode;

10. map measurement:

the areas of the length, the height, the triangle, the quadrangle and the polygon can be measured on the map;

marking the longitude, latitude and altitude of the point;

11. spatial analysis:

selecting a certain area on the map, and counting the number and the area of the complete map spots in the area;

counting the number and the area of the pattern spots intersected with the pattern spots in the area;

counting the number and the area of the pattern spots in the appointed distance around the area, such as 1 km, 5 km and the like;

and counting the areas of the debt base, cultivated land and rice in the appointed distance around the area.

Specifically, the big data visualization center takes the theme as an analysis object, selects a certain theme under the service classification, can display a two-dimensional chart of the theme in the data panel, marks the spatial distribution of the theme in the map, and superimposes the corresponding two-dimensional or three-dimensional chart layer. The main interface design is shown in the multi-dimensional analysis query main interface design diagram of fig. 4, and the functions of each part are described as follows:

1. the theme and the layer panel are respectively from top to bottom:

(1) folding button: clicking on the drop down button on the left side of the search box can hide the underlying theme and layer panel.

(2) Search box: the data record under the current theme can be searched, and fuzzy searching and instant searching are supported. The search listing paginates that each record may be located on the current map.

(3) Subject matter: and displaying each service theme in a tree-shaped hierarchical structure according to the service major class. Supporting the operations of adding, modifying and deleting themes and supporting the drag-and-drop operation of each node in the tree. The topic tree views of different nodes can be defined and saved in the form of schemes for later selection and loading.

(4) Layer (c): and displaying each thematic layer in a tree-shaped hierarchical structure according to the service category.

2. The data panel is from top to bottom:

(1) title: displaying the topic name of the analysis;

(2) summarizing index values: summarizing values in all dimensions according to the index selected by the theme;

(3) data table: the selected dimensions and indices of the theme are displayed. Clicking the drop-down button of each header can delete and add columns. Support drag left and right for each column. The dimensions below the header may be drilled down, or aggregated, by their hierarchy. Paging operations are supported.

(4) Image: according to the data table, all index diagrams of all dimensions below the data table are correspondingly displayed, and a histogram, a line diagram, a pie chart, a scatter diagram and the like can be selected for replacement

3. Tool bar:

(1) hiding: clicking the main title and the layer panel and the data panel which can display/hide the left and right sides;

(2) and (3) switching: a click switch defaults to an off state, and clicks to drag and drop the movable map; in the open state, a single click reveals the spot details of all superimposed layers there.

(3) Analysis: and (3) carrying out space analysis, and calculating the number and the area of the pattern spots under the intersection, inner and outer boundaries of the pattern layers in the frame selection range.

(4) Setting: the transparency, the superposition sequence and the coordinate system of the layers can be set, and different base maps, two-dimensional or three-dimensional and the like can be selected.

4. A central region:

(1) and the map display area is used for loading the data space distribution under the theme by default and can also cancel the display.

(2) When the left panel is switched to the map layer page, different map layers are selected, and the map layers can be displayed in a superimposed mode.

5. The time panel is from left to right:

(1) circular operation panel: playable, pause, rewind, speed-adjustable (by default in seconds).

(2) Long time axis: displaying a time range set by a theme;

(3) driving time dimension: clicking the play button can send a data query API request to the configuration center within the time range set by the theme, and the queried spatial data result is displayed on the map. As a result, the data space distribution map on the center area map dynamically changes with the lapse of time. Reverse play is supported.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims (7)

1. The method for constructing the big data platform by combining the digital twin and space-time technology is characterized by comprising the following steps of:

first step, environment deployment:

preparing a client machine;

constructing a space database for storing space data;

building a relational database for storing relational data;

constructing a file server for storing 3D model data;

building a map server, wherein the map server is used for publishing WMS service, WMTS service and TMS service;

building a Web server, wherein the Web server is used for publishing 3D model data, web application and providing http service and https service;

setting up an application server, wherein the application server is a micro-service cluster and is used for developing a configuration center and providing an API (application program interface) comprising query services, newly added services, deleted services, modified services and release services of each theme;

second, initializing data:

preparing management subject related data including spatial data, 3D model data and relationship data;

thirdly, application development:

the configuration center develops a back-end application program by adopting a cloud native and micro-service architecture;

developing a visualization center, developing a front-end application program, adopting a vue or reaction frame, and integrating a Web map;

fourth step, service release:

releasing WMS/WMTS service, entering a map server, and releasing various topics into WMS or WMTS;

issuing an http service, entering a Web server, and issuing a catalog in which the 3D model is located into the http service according to a project area;

issuing a micro service: the configuration center develops, packages and uploads the test completion to the micro service cluster, registers the service to the registration center, and provides API call to the outside through the gateway;

fifth, deploying Web application:

after the development and the test of the visual center are completed, packaging and uploading the visual center to a Web service cluster environment, configuring load balancing, providing a unified Web address, and accessing the visual center through a browser;

sixth, multiple data sources based on business theme are configured: aiming at each service theme, the data sources of all sources are dynamically configured in three panels of a layer, a theme and customization, each panel is organized in a tree form, and the data are finally integrated in a visual center area for centralized display.

2. The method for constructing a large data platform combining digital twin and spatio-temporal techniques according to claim 1, wherein in the sixth step, the multiple data source configuration includes a spatial data configuration, and the step of the spatial data configuration is as follows:

preparing space data and storing the space data into a space database;

building a map server environment;

publishing a WMS or WMTS map service in a map server;

and entering a layer panel of the visualization center, and configuring a corresponding layer for the service.

3. The method of claim 2, wherein the layers configured include layer names, layer links, longitudes, latitudes, altitudes, and service types.

4. The method for constructing a large data platform combining digital twin and spatio-temporal techniques according to claim 1, wherein in the sixth step, the multiple data source configuration includes a 3D model data configuration, and the step of the 3D model data configuration is as follows:

3D modeling is carried out through AutoCAD or unmanned aerial vehicle oblique photography, and the model is stored in a file server;

building a Web server environment;

publishing the 3D model as an http service;

and entering a layer panel of the visualization center, and configuring a corresponding layer for the service.

5. The method for constructing a large data platform combining digital twin and space-time technology according to claim 1, wherein in the sixth step, the multiple data source configuration includes a relational data configuration, and the steps of the relational data configuration are as follows:

preparing relation data, and extracting service data to a plurality of bins through an ETL tool;

and entering a theme panel of the visualization center to perform theme configuration.

6. The method of claim 5, wherein the configured topics include data sources, tables, fields, display names, formatting definitions, pictures, dimension definitions, index definitions, and spatial labels of the query.

7. The method for constructing a large data platform combining digital twin and spatio-temporal techniques according to claim 1, wherein in the sixth step, the multiple data source configuration includes a custom data configuration, and the step of the custom data configuration is as follows:

developing a personalized interface aiming at the data which cannot be dynamically configured for display;

and entering a customization panel of the visualization center, and performing theme configuration, wherein the theme to be configured comprises names and url.