Computational model fast integration and automatic ball-up visualization processing method and device

Abstract

This invention provides a method and apparatus for rapid integration and automatic visualization of computational models, relating to the field of artificial intelligence technology, specifically the application of computational models in the field of geographic information. It aims to solve the technical problems of low integration efficiency and poor scalability caused by the lack of a unified model access mechanism and a universal visualization framework in existing technologies, which require customized development of front-end interfaces and service interfaces for each model. This method uses standardized metadata description and an automation engine to solve the problems of automatic integration of third-party computational models and automatic generation of interactive interfaces. Model developers only need to follow a unified metadata specification and package the model into a standard service; the model management framework will automatically parse the metadata and generate standardized output and output interfaces. This can greatly improve model integration efficiency (from monthly / weekly to daily / hourly) and significantly enhance the platform's openness and scalability.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, specifically to the application of computational models in the field of geographic information, and more specifically, to a method and apparatus for rapid integration of computational models and automatic visualization processing. Background Technology

[0002] With the deep integration of Geographic Information System (GIS) technology and the concept of Digital Earth, and their explosive penetration across various industries, spatial information platforms based on a three-dimensional Earth are increasingly becoming core infrastructures in many key areas such as smart cities, environmental monitoring, emergency management, energy planning, and even smart agriculture. The powerful spatial data management, integration, and dynamic visualization capabilities of these platforms naturally make them an ideal "foundation" for supporting various spatial analysis and simulation models.

[0003] In current practice, a large number of third-party professional models play a crucial role. These models cover a wide range of professional application dimensions. Therefore, seamlessly integrating these models into the Digital Earth platform and fully utilizing its powerful spatial context for driving and displaying results is an urgent need and a key breakthrough for unleashing the potential of models, enhancing the platform's comprehensive analytical capabilities, and achieving intelligent decision support in the future.

[0004] However, in existing technologies, when third-party developed professional models are integrated into the Digital Earth platform, the lack of a unified model integration mechanism and a universal visualization framework typically requires customized development of front-end interfaces and service interfaces for each model, resulting in low integration efficiency and poor scalability. Therefore, there is an urgent need for a universal method and system that supports standardized integration of third-party models and can automatically generate input interaction interfaces and output display interfaces to improve model integration efficiency and platform scalability. Summary of the Invention

[0005] In view of this, the present invention provides a method and apparatus for rapid integration of computational models and automatic ball loading visualization, aiming to solve the technical problems of low integration efficiency and poor scalability in the prior art due to the lack of a unified model access mechanism and a general visualization framework, which requires customized development of front-end interfaces and service interfaces for models.

[0006] One aspect of the present invention provides a method for rapid integration and automatic visualization of computational models, applied to a model management framework, comprising: receiving an interface description file from a computational model, parsing the interface description file to generate model metadata, wherein the interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computational model; generating input interface configuration information and output parsing rules for the computational model based on the model metadata, and sending the input interface configuration information to a digital earth platform so that the digital earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the user-configured input parameters; receiving... The system receives model execution requests from the Digital Earth platform and validates the input parameters in these requests. Upon successful validation, it sends the execution request to the computational model to perform the computational task. It also receives the raw computation results returned by the computational model and parses them based on output parsing rules to generate structured computational result descriptions. Based on these descriptions, it constructs a result directory for each model execution task, generating corresponding spatial layer data for the spatial data results within the directory. Finally, it sends the generated spatial layer data to the Digital Earth platform, enabling it to load and visualize the data.

[0007] According to an embodiment of the present invention, the input interface specification includes parameter name, parameter identifier, parameter type, default value, parameter constraint, parameter description information, data format, and input component type; the output interface specification includes output item name, output identifier, output type, output description information, and output data format description.

[0008] According to an embodiment of the present invention, generating input interface configuration information and output parsing rules for a computational model based on model metadata includes: generating input interface configuration information for a computational model based on model metadata using predefined parameter-interaction component mapping rules; and generating output parsing rules for parsing model output results based on model metadata using predefined output interface specifications.

[0009] According to an embodiment of the present invention, the model execution request includes model identification information for identifying the target model, and input parameter values ​​for characterizing the model execution parameters.

[0010] According to an embodiment of the present invention, validating the input parameters in a model execution request includes: validating the parameter type, parameter range, and required parameters of the input parameters in the model execution request, and performing adaptation and conversion processing on the parameter data format of the input parameters in the model execution request when preset conditions are met.

[0011] According to an embodiment of the present invention, a result directory information is constructed based on the calculation result description information, with the model execution task as the unit. This includes: creating a parent result node in the result management interface of the digital earth platform, with the model execution task as the unit; and generating child nodes corresponding to the model output results under the parent result node according to the output result type. The child nodes include at least one of spatial layer nodes, statistical chart nodes, and file resource nodes.

[0012] According to an embodiment of the present invention, an application programming interface (API) service gateway is provided between the model management framework and the digital earth platform; wherein, the API service gateway serves as a unified access point between the model management framework and the digital earth platform, and is used to provide model list query, model parameter configuration acquisition, model execution request submission, and model execution status and result query, and supports a unified interface authentication and access control mechanism.

[0013] According to an embodiment of the present invention, the method further includes: real-time monitoring of the status of computing resources used by the system during operation and the generation status of model metadata; and scheduling and controlling the model execution tasks based on the monitoring results.

[0014] According to an embodiment of the present invention, the method further includes: configuring visualization theme parameters for spatial layer data based on theme management rules, wherein the theme parameters include at least one of color, symbol, transparency, and annotation fields.

[0015] Another aspect of the present invention provides a computational model rapid integration and automatic ball-layout visualization processing device, applied to a model management framework, comprising: a model registration module, used to receive an interface description file from a computational model, parse the interface description file, and generate model metadata, wherein the interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computational model; a model configuration management module, used to generate input interface configuration information and output parsing rules of the computational model according to the model metadata, and send the input interface configuration information to the digital earth platform, so that the digital earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the user-configured input parameters; and execution scheduling. The engine module receives model execution requests from the Digital Earth platform, validates the input parameters in the requests, and sends the requests to the computational model to perform the computational tasks upon successful validation. The computation result management module receives raw computation results from the computational model, parses them based on output parsing rules, and generates structured computation result descriptions. Based on these descriptions, it constructs a result directory for each model execution task, generating corresponding spatial layer data for the spatial data results within the directory. Finally, it sends the generated spatial layer data to the Digital Earth platform, enabling the platform to load and visualize the data.

[0016] Another aspect of the present invention provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method described above.

[0017] Another aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the method described above.

[0018] Another aspect of the present invention provides a computer program product including computer-executable instructions that, when executed, are used to implement the method described above.

[0019] Compared with the prior art, the computational model rapid integration and automatic ball placement visualization processing method and apparatus provided in this embodiment of the invention have at least the following beneficial effects:

[0020] (1) The computational model rapid integration and automatic ball visualization processing method and device provided in the embodiments of the present invention adopts standardized metadata description + automation engine to solve the problem of automatic access of third-party computational models and automatic generation of interactive interfaces. Model developers only need to follow the unified metadata specifications and package the model into a standard service. The model management framework will automatically parse the metadata and generate standardized output and output interface. This can greatly improve the efficiency of model access (from monthly / weekly level to daily / hourly level), significantly enhance the openness and scalability of the platform (quickly incorporate new models in the ecosystem), and strongly promote the accumulation and reuse of model assets (models become pluggable "microservices"). Model providers only need to focus on the design and development of the model computation function itself and encapsulate and register it according to the specifications to quickly realize ball visualization, thereby significantly improving user interaction experience and analysis efficiency.

[0021] (2) The computational model rapid integration and automatic visualization processing method and apparatus provided in this embodiment of the invention adopts a model access and registration mechanism based on unified metadata description to realize the self-descriptive access of third-party computational models. When registering a computational model, the model provider needs to submit the corresponding interface description file to the model management framework. This interface description file adopts a unified data description specification to structurally define the input and output interfaces of the model. The interface description file includes at least the parameter name, parameter identifier, parameter data type, parameter constraint condition, spatial data type identifier, and prompt information related to visualization interaction of the model input parameters, as well as the output type, data structure description, and visualization-related description information of the model output results. The model management framework automatically completes the identification and understanding of the capabilities of the computational model by parsing the interface description file, and stores the parsed model metadata information in the model registration center, thereby completing the registration process of the computational model. Through this unified metadata description method, the computational model has self-descriptive capabilities, providing a unified data foundation for subsequent model configuration, execution scheduling, and result parsing.

[0022] (3) The computational model rapid integration and automatic ball loading visualization processing method and apparatus provided in this embodiment of the invention adopts a dynamic generation method for model input configuration interface. After the model registration is completed, the model management framework performs dynamic generation of the model input configuration interface based on the model input interface metadata information, dynamically adapting or mapping it to a predefined interactive component library. This achieves the goal of eliminating the need to develop a separate front-end interface for each model, allowing users to configure parameters on the platform in a "what you see is what you get" manner. Through this metadata-based parameter-component automatic mapping mechanism, zero-code generation of the model input interface can be achieved, improving model access efficiency and reducing front-end development costs.

[0023] (4) The computational model rapid integration and automatic visualization processing method and apparatus provided in this embodiment of the invention adopts an automated parsing and visualization organization method for model output results. Based on the parsing results, a structured result directory view is automatically constructed. In the result management interface of the digital earth platform, parent nodes are created with model execution tasks as the unit, and child nodes corresponding to the output results are automatically generated under them, including spatial layer nodes, statistical chart nodes, or file resource nodes. For spatial layer nodes, the system can automatically configure the initial visualization style based on the visualization prompts provided in the output metadata. By intelligently identifying, parsing, and structurally organizing visualization elements (layers / charts) in the output description, the efficiency of result display can be significantly improved.

[0024] (5) The computational model rapid integration and automatic sphere visualization processing method and apparatus provided in this embodiment of the invention adopts a core architecture design of a model management module, that is, a middleware framework design for connecting the computational model layer and the digital earth platform. The core module, the model registration center, is responsible for storing and managing model metadata. The model configuration management module is responsible for parsing the input metadata to generate interface configuration, parsing the output metadata to generate result parsing rules, and the execution scheduling engine module to schedule model execution (synchronous / asynchronous), handle parameter verification, service calls, and task status management. The computational result management module parses the raw result data according to rules and constructs a structured result directory and visualization context. This architecture and the collaborative workflow of its components serve as the core carrier for realizing the entire automated pipeline, achieving decoupled integration between third-party computational models and the digital earth platform. This enables computational models from different sources and with different implementation methods to complete rapid access, parameter configuration, and result visualization without modifying the front-end code, thereby improving the system's scalability and model integration efficiency. Attached Figure Description

[0025] The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0026] Figure 1 A flowchart illustrating a method for rapid integration of computational models and automatic ball loading visualization processing according to an embodiment of the present invention is shown.

[0027] Figure 2 This diagram schematically illustrates the link between the model management framework, the computational model, and the digital earth platform according to an embodiment of the present invention.

[0028] Figure 3 This schematic diagram illustrates the structural block diagram of a computational model rapid integration and automatic ball loading visualization processing device according to an embodiment of the present invention;

[0029] Figure 4The diagram illustrates the structure of an electronic device suitable for implementing a method for rapid integration of computational models and automatic ball loading visualization processing according to an embodiment of the present invention. Detailed Implementation

[0030] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0031] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0032] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0033] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0034] In the embodiments of this invention, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to maintain the security of user personal information and network security.

[0035] With the deep integration of Geographic Information System (GIS) technology and the concept of Digital Earth, and their explosive penetration across various industries, spatial information platforms based on a three-dimensional Earth are increasingly becoming core infrastructures in many key areas such as smart cities, environmental monitoring, emergency management, energy planning, and even smart agriculture. The powerful spatial data management, integration, and dynamic visualization capabilities of these platforms naturally make them an ideal "foundation" for supporting various spatial analysis and simulation models.

[0036] In current practice, numerous third-party professional models play a crucial role. These models cover a wide range of professional applications, such as: accurate terrain complexity calculation (for analyzing regional accessibility or suitability for construction), refined accessibility performance assessment (simulating the mobility of transportation, logistics, or military equipment on different terrain surfaces), complex hydrological and hydrodynamic simulations (predicting flood evolution), accurate meteorological pollutant diffusion simulations, in-depth ecological carrying capacity assessments, and urban development simulations under multiple scenarios. The scientific rigor and professionalism of these models are the core of their value.

[0037] Therefore, seamlessly integrating these models into the Digital Earth platform and fully utilizing its powerful spatial context for driving and displaying results is an urgent need and a key breakthrough for unleashing the potential of models, enhancing the platform's comprehensive analytical capabilities, and achieving intelligent decision support in the future.

[0038] However, in existing technologies, third-party developed professional models still face the following shortcomings when integrated into the Digital Earth platform, for example:

[0039] (1) Lack of a unified model access mechanism: Current mainstream digital earth platforms differ greatly in their underlying architecture, data specifications, and service application programming interfaces (APIs). Furthermore, they lack a widely accepted standard protocol that describes the model's functionality, input and output parameter specifications (name, type, value range, unit, data format, etc.), and execution methods (local / cloud, synchronous / asynchronous). Models are like plugs of various shapes, while the sockets provided by the platforms are inconsistent and incompatible.

[0040] (2) Lack of a universal model visualization framework: The spatial representation requirements of model calculation results are complex and diverse, such as point results (e.g., monitoring stations), linear results (e.g., trajectories, paths), area results (e.g., pollution range, heat maps), dynamic field data (e.g., wind fields, flow fields), and three-dimensional volume data (e.g., geological bodies, buildings), each requiring specific visualization rendering techniques. Currently, various digital earth platforms typically lack a universal framework that can automatically adapt and generate corresponding interactive interfaces (model parameter input interface and calculation result visualization interface) based on model output metadata. This forces integrators to manually write a large amount of visualization code, which is difficult and lacks flexibility.

[0041] The direct consequence of these problems is a high degree of customization and repetitive work in model development and integration. Currently, the mainstream approach to integrating third-party models into the Digital Earth platform almost inevitably requires extensive customization of input and output interfaces. Model developers or platform integrators need to manually tailor a dedicated front-end interface (for parameter input and model startup control) and back-end service interface (for receiving requests, calling models, and transmitting data) for each model. This means that even if two models have similar functions, the integration process requires almost "starting from scratch," resulting in extremely low R&D efficiency. It also makes cross-platform model reuse, rapid deployment of different models within the same platform, and even model chaining between models from different disciplines exceptionally difficult.

[0042] In summary, current technologies for integrating third-party developed professional models into digital earth platforms suffer from low efficiency and poor scalability due to the lack of a unified model integration mechanism and a universal visualization framework. This typically requires customized development of front-end interfaces and service interfaces for each model. Therefore, there is an urgent need for a universal method and system that supports standardized integration of third-party models and can automatically generate input and output display interfaces, thereby improving model integration efficiency and platform scalability.

[0043] Based on this, embodiments of the present invention provide a method and apparatus for rapid integration of computational models and automatic ball loading visualization, aiming to solve the technical problems of low integration efficiency and poor scalability in the prior art due to the lack of a unified model access mechanism and a general visualization framework, which requires customized development of front-end interfaces and service interfaces for models.

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0045] Figure 1The flowchart illustrates a method for rapid integration of computational models and automatic ball placement visualization processing according to an embodiment of the present invention.

[0046] like Figure 1 As shown, the computational model rapid integration and automatic ball placement visualization processing method of this embodiment may include, for example, operations S1 to S6.

[0047] In this embodiment, the rapid integration of the computational model and the automatic ball-loading visualization processing method can be executed, for example, by a model management framework.

[0048] In operation S1, the interface description file from the computational model is received and parsed to generate model metadata. The interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computational model.

[0049] In operation S2, based on the model metadata, the input interface configuration information and output parsing rules of the computation model are generated, and the input interface configuration information is sent to the Digital Earth platform so that the Digital Earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the input parameters configured by the user.

[0050] In operation S3, a model execution request is received from the Digital Earth platform, and the input parameters in the model execution request are validated. In response to the validation being successful, the model execution request is sent to the computation model to execute the computation task.

[0051] In operation S4, the raw calculation results returned by the calculation model are received, and the raw calculation results are parsed based on the output parsing rules to generate structured calculation result description information.

[0052] In operation S5, based on the description information of the calculation results, a result directory information is constructed with the model execution task as the unit. Among them, for the spatial data results in the result directory information, the corresponding spatial layer data is generated.

[0053] During operation S6, the generated spatial layer data is sent to the Digital Earth platform so that the Digital Earth platform can load the spatial layer data and visualize it.

[0054] This method provides a unified standard specification for model input / output interfaces and a model visualization management framework, supporting standardized and declarative access to third-party professional models. Model providers only need to describe their metadata (such as functionality, input parameter constraints, and output data structure) according to the unified specification, encapsulate the interface, and register it with the model visualization management framework according to the specification.

[0055] Automatically generate input interaction interfaces: Based on parameter descriptions, intelligently generate intuitive and user-friendly front-end parameter configuration forms (such as sliders, drop-down selections, file upload components, and map interactive point selection), greatly reducing the workload of building user interfaces.

[0056] Automatically adapts to the output visualization: Based on the type of model output data (such as points / lines / surfaces / raster / vectors / 3D volumes), structure (such as scalars / vectors / tensors), and semantic information (such as temperature values, height, pollutant concentrations), it automatically selects and configures the best rendering scheme (such as heat maps, isosurfaces, dynamic particles, 3D flow field arrows, and linked charts), and intuitively integrates and displays the results in a 3D Earth scene.

[0057] Provide standard execution interfaces: Define clear and loosely coupled service call contracts between the model and the platform (such as Web service interfaces (Representational State Transfer API) built on REST principles, service forms or message queues of high-performance remote procedure call framework protocols), and shield the heterogeneity of underlying technologies.

[0058] The computational model rapid integration and automatic visualization processing method provided in this invention adopts a model access and registration mechanism based on unified metadata description. This mechanism enables self-descriptive access of third-party computational models. When registering a computational model, the model provider must submit a corresponding interface description file to the model management framework. This interface description file uses a unified data description specification to structurally define the model's input and output interfaces. The interface description file includes at least the parameter names, parameter identifiers, parameter data types, parameter constraints, spatial data type identifiers, and visual interaction-related prompts for the model input parameters, as well as the output type, data structure description, and visualization-related descriptive information for the model output results. The model management framework automatically identifies and understands the capabilities of the computational model by parsing this interface description file and stores the parsed model metadata information in the model registration center, thus completing the computational model registration process. This unified metadata description method enables the computational model to have self-descriptive capabilities, providing a unified data foundation for subsequent model configuration, execution scheduling, and result parsing.

[0059] In this embodiment, a model management framework is designed to connect the computational model and the digital earth platform, as detailed below. Figure 2 As shown.

[0060] Figure 2 The diagram illustrates the link between the model management framework, the computational model, and the digital earth platform according to an embodiment of the present invention.

[0061] like Figure 2As shown in this embodiment, the model management framework, the computational model, and the digital earth platform can be integrated into a single system. The computational model is located at the bottom layer of the system, and the digital earth platform is located at the top layer of the system. The two are connected and interact through the model management framework.

[0062] The model management framework, serving as the core middleware layer of the system, enables unified access, configuration management, execution scheduling, and result parsing and visualization adaptation of computational models. Third-party computational models are encapsulated as standardized services conforming to preset interface specifications. These standardized services include, but are not limited to, web service interfaces built on REST principles or high-performance remote procedure call framework protocols.

[0063] The model management framework provides a model registration interface for standardized services. This interface receives and parses model interface description files and registers the model's related metadata. After completing the development of the core model algorithm and the standardized encapsulation of the interface, model developers enter the model's metadata information, thereby completing the model registration and its visualization configuration on the Digital Earth platform.

[0064] Regarding model input, the model management framework provides input configuration functionality based on model metadata. The computational model designs its input interface according to actual computational needs and describes the input parameters in the interface description file. Based on the parameter types, constraints, and input component identification information defined in the interface description file, the model management framework performs rule parsing and mapping of the model input parameters, automatically generating a configuration scheme for the model input interface. The digital earth platform front-end then automatically generates the corresponding model input interface based on this configuration scheme.

[0065] Regarding model output, the computational model organizes the output results according to a pre-defined standardized interface specification. The model management framework automatically parses the output results and generates structured output description information based on the parsing results. The digital earth platform front-end then generates the corresponding result layer directory and performs visualization rendering on each output result.

[0066] The above structure enables decoupled integration between third-party computing models and the digital earth platform, allowing computing models from different sources and with different implementation methods to be quickly connected, configured with parameters, and visualized with results without modifying the front-end code, thereby improving the system's scalability and model integration efficiency.

[0067] To make the rapid integration of the computational model and the automatic ball loading visualization processing method provided in the embodiments of the present invention clearer, the workflow of the model management framework will be described in more detail below.

[0068] The workflow of this model management framework specifically involves the following aspects:

[0069] 1. Model Registration:

[0070] First, the model management framework receives model services and their interface description files provided by third-party computing models. These interface description files are used to provide a structured description of the input and output interface specifications of the computing models.

[0071] According to embodiments of the present invention, the input interface specification may specifically include: parameter name, parameter identifier, parameter type, default value, parameter constraints, parameter description information, data format, and input component type. The output interface specification may specifically include output item name, output identifier, output type, output description information, and output data format description.

[0072] Then, the interface description file is parsed to generate the corresponding model metadata information, and the model metadata information is stored to complete the registration of the computing model.

[0073] The computational model rapid integration and automatic visualization processing method provided in this invention adopts a model access and registration mechanism based on unified metadata description. This mechanism enables self-descriptive access of third-party computational models. When registering a computational model, the model provider must submit a corresponding interface description file to the model management framework. This interface description file uses a unified data description specification to structurally define the model's input and output interfaces. The interface description file includes at least the parameter names, parameter identifiers, parameter data types, parameter constraints, spatial data type identifiers, and visual interaction-related prompts for the model input parameters, as well as the output type, data structure description, and visualization-related descriptive information for the model output results. The model management framework automatically identifies and understands the capabilities of the computational model by parsing this interface description file and stores the parsed model metadata information in the model registration center, thus completing the computational model registration process. This unified metadata description method enables the computational model to have self-descriptive capabilities, providing a unified data foundation for subsequent model configuration, execution scheduling, and result parsing.

[0074] II. Model Configuration Generation:

[0075] The model management framework generates input interface configuration information and output parsing rules for the computational model based on the model metadata, and sends the input interface configuration information to the Digital Earth platform.

[0076] After receiving the input interface configuration information, the Digital Earth platform will generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the user's configured input parameters.

[0077] According to an embodiment of the present invention, input interface configuration information and output parsing rules for a computational model are generated based on model metadata, which may specifically include:

[0078] Based on model metadata, the input interface configuration information of the computational model is generated using predefined parameter-interaction component mapping rules; based on model metadata, the output parsing rules for parsing model output results are generated using predefined output interface specifications.

[0079] For example, the model management framework can parse the input parameters of the computational model based on model metadata information and automatically generate a configuration scheme for the model input interface according to predefined parameter-interaction component mapping rules. These interaction component types can include, for example, input boxes, drop-down selection boxes, sliders, and spatial location selection components. Simultaneously, the model management framework can generate output parsing rules for parsing model output results based on the output interface specifications defined in the model metadata information.

[0080] The computational model rapid integration and automatic ball-loading visualization processing method provided in this embodiment of the invention adopts a dynamic generation method for the model input configuration interface. After the model registration is completed, the model management framework dynamically generates the model input configuration interface based on the model input interface metadata information, dynamically adapting or mapping it to a predefined interactive component library. This eliminates the need to develop a separate front-end interface for each model, allowing users to configure parameters in a WYSIWYG manner on the platform. Through this metadata-based parameter-component automatic mapping mechanism, zero-code generation of the model input interface can be achieved, improving model access efficiency and reducing front-end development costs.

[0081] Third, model execution scheduling:

[0082] The model management framework receives model execution requests from the Digital Earth platform, performs automated validity checks on the input parameters, and, after successful validation, invokes the corresponding computational model service to execute the computation task based on the model registration information.

[0083] For example, based on the service access address and communication protocol type recorded in the model registration information, the processed parameter request can be sent to the corresponding computing model service. It can adopt synchronous or asynchronous execution mode and manage the status of the model execution task.

[0084] In addition, it can handle abnormal situations during model execution and record model execution log information.

[0085] According to an embodiment of the present invention, the model execution request specifically includes model identification information for identifying the target model, and input parameter values ​​for characterizing the model execution parameters.

[0086] According to an embodiment of the present invention, validating the input parameters in the model execution request may specifically include:

[0087] The system validates the parameter types, parameter ranges, and required parameters of the input parameters in the model execution request, and performs adaptation and conversion processing on the parameter data format of the input parameters in the model execution request when the preset conditions are met.

[0088] For example, when performing validity verification, the model management framework mainly verifies the parameter type, parameter range, and required parameters of the input parameters in the model execution request, and performs adaptation and conversion processing on the parameter data format of the input parameters in the model execution request when necessary.

[0089] IV. Analysis of Calculation Results:

[0090] The model management framework receives the raw computation results returned by the computation model, and based on the output parsing rules, parses the raw computation results, identifies the data type and data structure of the output results, and generates structured computation result description information.

[0091] During the parsing process, the model management framework will construct a result directory based on the computation result description information, with each model execution task as the unit.

[0092] According to an embodiment of the present invention, based on the description information of the calculation results, result catalog information is constructed on a unit basis according to the model execution task, which may specifically include:

[0093] In the results management interface of the Digital Earth platform, parent result nodes are created on a per-model-execution-task basis. Under the parent result node, child nodes corresponding to the model output results are generated according to the output result type. Among them, child nodes include at least one of spatial layer nodes, statistical chart nodes, and file resource nodes.

[0094] The computational model rapid integration and automatic visualization processing method provided in this invention adopts an automated parsing and visualization organization method for model output results. Based on the parsing results, a structured result directory view is automatically constructed. In the result management interface of the digital earth platform, parent nodes are created based on model execution tasks, and child nodes corresponding to the output results are automatically generated under them, including spatial layer nodes, statistical chart nodes, or file resource nodes. For spatial layer nodes, the system can automatically configure the initial visualization style based on the visualization prompts provided in the output metadata. By intelligently identifying, parsing, and structurally organizing visualization elements (layers / charts) in the output description, the efficiency of result display can be significantly improved.

[0095] V. Interface Authentication and Access Control:

[0096] According to an embodiment of the present invention, an application programming interface (API) service gateway is provided between the model management framework and the digital earth platform.

[0097] Among them, the application interface service gateway serves as a unified access point between the model management framework and the digital earth platform. It provides services such as model list query, model parameter configuration acquisition, model execution request submission, and model execution status and result query, and supports a unified interface authentication and access control mechanism.

[0098] VI. Resource Monitoring and Management:

[0099] According to embodiments of the present invention, the method may further include, for example,: real-time monitoring of the status of computing resources used by the system during operation and the generation status of model metadata; and scheduling and controlling the model execution tasks based on the monitoring results.

[0100] VII. Topic Management:

[0101] According to an embodiment of the present invention, the method may further include, for example, configuring visualization theme parameters for spatial layer data based on theme management rules, wherein the theme parameters include at least one of color, symbol, transparency, and annotation fields.

[0102] Figure 3 The diagram illustrates the structural block diagram of a computational model rapid integration and automatic ball loading visualization processing device according to an embodiment of the present invention.

[0103] like Figure 3 As shown, the computational model rapid integration and automatic ball loading visualization processing device 300 of this embodiment includes: a model registration module 310, a model configuration management module 320, an execution scheduling engine module 330, and a computation result management module 340.

[0104] The model registration module 310 is used to receive the interface description file from the computing model, parse the interface description file, and generate model metadata. The interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computing model.

[0105] For example, in this embodiment, the model registration module 310 mainly provides a standardized model registration interface for model developers or system administrators. This model registration interface can take the form of a REST API, utility program, etc., to receive pre-packaged computational model services. Specifically:

[0106] The model registration module 310 parses and stores the interface description file provided by the computational model. The interface description file contains the model's input interface specifications and output interface specifications. The input interface specifications include at least parameter names, parameter identifiers, parameter types, default values, parameter constraints, parameter description information, data formats, and input component types. The output interface specifications include at least output item names, output identifiers, output types, output description information, and output data format specifications.

[0107] The parsed interface description information is stored uniformly as part of the model metadata and is called by the model configuration management module 320, the execution scheduling engine module 330, and the calculation result management module 340.

[0108] The model configuration management module 320 is used to generate input interface configuration information and output parsing rules for the computational model based on the model metadata, and send the input interface configuration information to the digital earth platform so that the digital earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the input parameters configured by the user.

[0109] For example, in this embodiment, the model configuration management module 320 is mainly used to read, parse, cache and manage the metadata information of registered models, providing basic data support for the generation of model input interfaces and model execution scheduling.

[0110] The input interface configuration function of the model configuration management module 320 automatically generates a parameter configuration scheme for the model based on the input parameter types, parameter constraints, and input component prompts defined in the model metadata, using predefined parameter-component mapping rules. This parameter configuration scheme describes the types of input controls and their attribute parameters that need to be rendered on the front end of the digital earth platform, and can be output in the form of a structured configuration description object for direct use by the front-end user interface framework.

[0111] The model configuration management module 320 also includes an output parsing configuration function, which pre-generates corresponding output parsing rules based on the output interface specifications defined in the model metadata, and instructs the calculation result management module to parse and process the model output results.

[0112] The execution scheduling engine module 330 is used to receive model execution requests from the digital earth platform, and to validate the input parameters in the model execution request. In response to the validation passing, the model execution request is sent to the computing model to execute the computing task.

[0113] For example, in this embodiment, the execution scheduling engine module 330 is used to receive a model execution request from the front end of the digital earth platform. The model execution request includes at least model identification information and user-configured input parameter values.

[0114] The execution scheduling engine module 330 performs automated validity checks on the received input parameters based on the input parameter specifications defined in the model metadata, including parameter type checks, parameter range checks, and mandatory parameter checks, and automatically adapts and converts the parameter data format when necessary.

[0115] After verification and adaptation are completed, the execution scheduling engine module 330 sends the processed parameter request to the corresponding computing model service based on the service access address and communication protocol type recorded in the model registration information. The execution scheduling engine module 330 supports synchronous and asynchronous execution modes and manages the status of model execution tasks.

[0116] The execution scheduling engine module 330 is also used to handle abnormal situations during model execution and record model execution log information.

[0117] The calculation result management module 340 is used to receive the raw calculation results returned by the calculation model, and parse the raw calculation results based on the output parsing rules to generate structured calculation result description information; construct result directory information based on the calculation result description information, wherein corresponding spatial layer data is generated for the spatial data results in the result directory information; and send the generated spatial layer data to the digital earth platform so that the digital earth platform can load the spatial layer data and perform visualization display.

[0118] For example, in this embodiment, the calculation result management module 340 is mainly used to receive the original calculation results of the model returned by the execution scheduling engine module 330, and automatically parse the original calculation results based on the model output interface specification and the pre-configured output parsing rules.

[0119] During the analysis process, the calculation result management module 340 automatically identifies and constructs the corresponding spatial layer data, statistical data items, or file resource links based on the type of output results, and generates structured result directory information. This result directory information is transmitted to the Digital Earth platform, where it is used to automatically generate result nodes corresponding to this model execution task in the layer management interface.

[0120] The process of parsing and visualizing the calculation results requires no manual intervention, enabling the automatic conversion of model output results into visual elements of the digital earth platform.

[0121] In addition to the model registration module 310, model configuration management module 320, execution scheduling engine module 330, and calculation result management module 340, the computational model rapid integration and automatic ball loading visualization processing device 300 of this embodiment of the invention may also include: API service gateway, resource monitoring and management module, and topic manager.

[0122] The API service gateway provides a unified model access interface to the Digital Earth platform, serving as a unified access point between the model management framework and the Digital Earth platform, thereby shielding the implementation complexity within the model management framework.

[0123] The API service gateway also provides interfaces for querying model lists, obtaining model parameter configurations, submitting model execution requests, and querying model execution status and results, and supports a unified interface authentication and access control mechanism.

[0124] The resource monitoring and management module is used to monitor the status of computing resources used during system operation and the running status of registered model services, and to schedule and control the execution of model tasks based on the monitoring results.

[0125] The resource monitoring and management module can limit the number of concurrent model executions, monitor long-running tasks, and provide resource status information to the execution scheduling engine to support the dynamic adjustment of model execution scheduling strategies.

[0126] The theme manager allows for personalized configuration of the output visualization, providing a variety of themes and style options (such as colors, symbols, transparency, and labeled fields), while also allowing users to adjust them on the front end.

[0127] The computational model rapid integration and automatic visualization processing device provided in this invention adopts a core architecture design of a model management module. This design constitutes an intermediate framework connecting the computational model layer and the digital earth platform. The core module, the model registration center, is responsible for storing and managing model metadata. The model configuration management module parses input metadata to generate interface configurations and output metadata to generate result parsing rules. The execution scheduling engine module schedules model execution (synchronously / asynchronously), handles parameter verification, service calls, and task status management. The computational result management module parses raw result data according to rules and constructs a structured result directory and visualization context. This architecture and its components' collaborative workflow serve as the core carrier for realizing the entire automated pipeline. It achieves decoupled integration between third-party computational models and the digital earth platform, enabling computational models from different sources and with different implementation methods to quickly access, configure parameters, and visualize results without modifying the front-end code, thereby improving system scalability and model integration efficiency.

[0128] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present invention, or at least part of the functions of any one or more of them, can be implemented in a single module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be implemented by being divided into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, and firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present invention can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0129] For example, any multiple of the model registration module 310, model configuration management module 320, execution scheduling engine module 330, and calculation result management module 340 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functions of one or more of these modules / units / subunits can be combined with at least some of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of the present invention, at least one of the model registration module 310, model configuration management module 320, execution scheduling engine module 330, and calculation result management module 340 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the model registration module 310, model configuration management module 320, execution scheduling engine module 330, and calculation result management module 340 can be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0130] It should be noted that the computational model rapid integration and automatic ball loading visualization processing device part in the embodiments of the present invention corresponds to the computational model rapid integration and automatic ball loading visualization processing method part in the embodiments of the present invention. For a detailed description of the computational model rapid integration and automatic ball loading visualization processing device part, please refer to the computational model rapid integration and automatic ball loading visualization processing method part, which will not be repeated here.

[0131] Figure 4 The diagram illustrates the structure of an electronic device suitable for implementing a method for rapid integration of computational models and automatic ball loading visualization processing according to an embodiment of the present invention. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0132] like Figure 4 As shown, an electronic device 400 according to an embodiment of the present invention includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage portion 408 into a random access memory (RAM) 403. The processor 401 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 401 may also include onboard memory for caching purposes. The processor 401 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0133] The storage section 408 stores various programs and data required for the operation of the electronic device 400. The processor 401, ROM 402, and storage section 408 are interconnected via bus 404. The processor 401 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 402 and / or storage section 408. It should be noted that the programs may also be stored in one or more memories other than ROM 402 and storage section 408. The processor 401 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in said one or more memories.

[0134] According to an embodiment of the present invention, the electronic device 400 may further include an input / output (I / O) interface 405, which is also connected to a bus 404. The electronic device 400 may also include one or more of the following components connected to the input / output (I / O) interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output (I / O) interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0135] According to embodiments of the present invention, the method flow according to embodiments of the present invention can be implemented as a computer software program. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by processor 401, it performs the functions defined in the system of the embodiments of the present invention. According to embodiments of the present invention, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0136] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0137] According to embodiments of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0138] For example, according to embodiments of the present invention, a computer-readable storage medium may include the ROM 402 and / or storage portion 408 described above and / or one or more memories other than ROM 402 and storage portion 408.

[0139] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of the present invention. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the methods provided in the embodiments of the present invention.

[0140] When the computer program is executed by the processor 401, it performs the functions defined in the system / apparatus of this embodiment of the invention. According to embodiments of the invention, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0141] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via communication section 409, and / or installed from removable medium 411. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0142] According to embodiments of the present invention, program code for executing the computer programs provided in the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention can be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or pairings fall within the scope of this invention.

[0144] The embodiments of the present invention have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of the invention. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the invention, and all such substitutions and modifications should fall within the scope of the invention.

Claims

1. A method for rapid integration of computational models and automatic ball placement visualization processing, characterized in that, Applied to a model management framework, the method includes: The system receives an interface description file from a computational model and parses the interface description file to generate model metadata. The interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computational model. Based on the model metadata, the input interface configuration information and output parsing rules of the computing model are generated, and the input interface configuration information is sent to the Digital Earth platform so that the Digital Earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the input parameters configured by the user. The system receives a model execution request from the digital earth platform, verifies the validity of the input parameters in the model execution request, and sends the model execution request to the computing model to execute the computing task in response to the successful verification. Receive the raw calculation results returned by the calculation model, and parse the raw calculation results based on the output parsing rules to generate structured calculation result description information; Based on the calculation result description information, a result directory information is constructed with the model execution task as the unit, wherein, for the spatial data results in the result directory information, corresponding spatial layer data is generated; The generated spatial layer data is sent to the digital earth platform so that the digital earth platform can load the spatial layer data and display it visually.

2. The method according to claim 1, characterized in that, The input interface specification includes parameter name, parameter identifier, parameter type, default value, parameter constraints, parameter description information, data format, and input component type; The output interface specification includes the output item name, output identifier, output type, output description information, and output data format description.

3. The method according to claim 2, characterized in that, The step of generating the input interface configuration information and output parsing rules of the computational model based on the model metadata includes: Based on the model metadata, the input interface configuration information of the computing model is generated using predefined parameter-interaction component mapping rules. Based on the model metadata, output parsing rules are generated using predefined output interface specifications to parse the model output results.

4. The method according to claim 1, characterized in that, The model execution request includes model identification information for identifying the target model, and input parameter values ​​for characterizing the model execution parameters.

5. The method according to claim 4, characterized in that, The validation of the input parameters in the model execution request includes: The parameter types, parameter ranges, and required parameters of the input parameters in the model execution request are validated, and the parameter data format of the input parameters in the model execution request is adapted and converted when the preset conditions are met.

6. The method according to claim 1, characterized in that, The step of constructing a result catalog information based on the calculation result description information, organized by model execution task, includes: In the results management interface of the digital earth platform, parent result nodes are created on a per-model execution task basis; Under the parent result node, child nodes corresponding to the model output results are generated according to the output result type, wherein the child nodes include at least one of spatial layer nodes, statistical chart nodes, and file resource nodes.

7. The method according to claim 1, characterized in that, An application programming interface service gateway is provided between the model management framework and the digital earth platform; The application programming interface service gateway serves as a unified access point between the model management framework and the digital earth platform. It provides functions such as model list query, model parameter configuration acquisition, model execution request submission, and model execution status and result query, and supports a unified interface authentication and access control mechanism.

8. The method according to claim 1, characterized in that, The method further includes: The real-time monitoring system monitors the status of computing resources used during operation and the generation status of the model metadata. Based on the monitoring results, the tasks executed by the model are scheduled and controlled.

9. The method according to claim 1, characterized in that, The method further includes: Based on theme management rules, visualization theme parameters are configured for the spatial layer data, wherein the theme parameters include at least one of color, symbol, transparency, and annotation fields.

10. A computational model rapid integration and automatic ball loading visualization processing device, characterized in that, The device, applied to a model management framework, includes: The model registration module is used to receive the interface description file from the computing model, parse the interface description file, and generate model metadata. The interface description file is used to provide a structured description of the input interface specifications and output interface specifications of the computing model. The model configuration management module is used to generate the input interface configuration information and output parsing rules of the computing model based on the model metadata, and send the input interface configuration information to the digital earth platform so that the digital earth platform can generate a model parameter configuration interface based on the input interface configuration information, and generate a model execution request after receiving the input parameters configured by the user. The execution scheduling engine module is used to receive model execution requests from the digital earth platform, and to perform validity checks on the input parameters in the model execution request. In response to the successful verification, the module sends the model execution request to the computing model to execute the computing task. The calculation result management module is used to receive the raw calculation results returned by the calculation model, and parse the raw calculation results based on the output parsing rules to generate structured calculation result description information; construct result directory information based on the calculation result description information, wherein corresponding spatial layer data is generated for the spatial data results in the result directory information; and send the generated spatial layer data to the digital earth platform so that the digital earth platform can load the spatial layer data and perform visualization display.

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