Scientific research data modeling method and device, electronic equipment and storage medium
By using a scientific research data modeling method based on a digital object architecture, the heterogeneity and sharing problems of traditional scientific research data modeling methods in multimodal data processing are solved, and unified management and cross-platform collaborative innovation of multimodal scientific research data are realized.
Patent Information
- Application Number
- CN202510875472.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-27
- Publication Date
- 2025-10-28
AI Technical Summary
Traditional scientific research data modeling methods cannot effectively handle the heterogeneity of multimodal data, cannot achieve data sharing and exchange, cannot identify the row-level granularity of data, and have poor data access adaptability.
The DO-IRP protocol, based on a digital object architecture, is adopted to uniformly describe multimodal scientific research data through scientific research data modeling algorithms. Digital object classes are established, unique digital object identifiers are assigned across the entire network, and scientific research data models are generated. The scientific research data model is then used to run a support platform for parsing and storage.
It enables unified modeling and management of multimodal scientific research data, improves the adaptability of data management and the efficiency of system operation, realizes data security and quality management, and supports cross-platform collaborative innovation.
Smart Images
Figure CN120849394A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of software engineering and data modeling technology, and specifically relates to a scientific research data modeling method, device, electronic device and storage medium. Background Technology
[0002] Innovation in scientific research management and services requires the collection of massive amounts of multimodal data from research institutions and enterprises across various systems and regions. Intelligent processing of scientific research big data is essential for achieving collaborative innovation and adapting to new research paradigms. The collection and service of this multimodal data involves numerous heterogeneous platforms and data sets; therefore, the architecture, technology, platform, and governance system of scientific research data have become fundamental engineering projects for technological innovation. How to uniformly model multimodal scientific research data and build data-driven scientific research management and services has become a core area of technological empowerment.
[0003] Traditional scientific research data modeling methods typically utilize relational databases to set up data structures, forming SQL (Structured Query Language) data modeling. While this data modeling method can effectively solve data collection and storage problems, it still has the following shortcomings:
[0004] 1) Traditional scientific research data modeling is generally suitable for modeling structured two-dimensional SQL databases, but it cannot achieve data encapsulation that is independent of technology when sharing and exchanging data elements on a larger scale.
[0005] 2) Traditional scientific research data modeling methods are generally only for modeling structured two-dimensional SQL databases in management systems. They cannot model unstructured digital object files and spatiotemporal streaming data collected by intelligent instruments and equipment in scientific research.
[0006] 3) The data model description is a table structure. Traditional scientific research data modeling methods are basically SQL relational models, which cannot effectively identify the row-level granularity of data tables, and access requires programming of upper-level applications.
[0007] 4) In traditional scientific research data modeling methods, data access relies on SQL applications, resulting in the lack of a universal protocol for storage, access, and API interfaces, leading to poor adaptability across different platforms and operating environments. Summary of the Invention
[0008] This application provides a scientific data modeling method, apparatus, electronic device, and storage medium, which aims to at least partially solve one of the aforementioned technical problems in the prior art.
[0009] To address the above problems, this application provides the following technical solution:
[0010] A scientific research data modeling method, comprising:
[0011] The DO-IRP protocol based on the digital object architecture uses scientific research data modeling algorithms to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes digital object classes;
[0012] Each multimodal scientific research data resource is assigned a unique digital object identifier across the entire network through the established identification system;
[0013] The metadata of digital object classes is used to define the digital object model, and the relationship types of digital objects are established to generate a scientific research data model.
[0014] The scientific research data model is parsed and stored through the scientific research data model operation support platform.
[0015] The technical solution adopted in this application embodiment further includes: the DO-IRP protocol based on the digital object architecture uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata. Before establishing the digital object class, it also includes:
[0016] Collect multimodal scientific research data to be modeled; the multimodal scientific research data includes structured data, digital object files and spatiotemporal streaming data; the structured data includes data tables in an SQL database, and the digital object files include, but are not limited to, scientific and technological reports, analysis reports, experimental data files, gene sequencing files and image files; the spatiotemporal streaming data includes, but is not limited to, temperature, humidity, air pressure, voltage, current or image data collected by instruments and equipment.
[0017] The technical solution adopted in this application embodiment further includes: the DO-IRP protocol based on the digital object architecture uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes digital object classes, including:
[0018] The scientific research data modeling algorithm is a tool software based on front-end and back-end separation. The front-end uses an interactive method to define the data structure by describing the attributes and metadata of the multimodal scientific research data. The back-end is a scientific research data model running support platform used to parse and store the generated scientific research data model.
[0019] The technical solution adopted in this application embodiment also includes: the DO-IRP protocol based on the digital object architecture uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes a digital object class, specifically:
[0020] The establishment of the digital object class includes a structural description and an access description. The structural description includes a description of the data structure of the multimodal scientific research data through metadata. The access description includes a description of the system access address and addressing method. Specifically, the structural description includes: a structural description of the name, attributes, and value rules of each field or data domain in the data table; an attribute description of the author, title, publication time, publication carrier, and keywords of the digital object file and its content; and a parameter description of the spatiotemporal streaming data. The digital object file includes: JPG image files, EXCEL data files, and PDF report format files. The parameters include: the type of instrument and equipment, and the physical quantities collected.
[0021] The technical solution adopted in this application embodiment also includes: assigning a unique digital object identifier to each multimodal scientific research data resource through the established identification system, specifically:
[0022] The digital object identifier includes: <data center address identifier>, <digital object class identifier>, and <digital object sequence identifier>; wherein, the <data center address identifier> is identified by an Internet DNS domain name, the <digital object class identifier> is assigned a unique data directory name by the organization, and the <digital object sequence identifier> is identified by the key field ID of the SQL database or the system-wide sequence code.
[0023] The technical solution adopted in this application embodiment also includes: defining a digital object model using metadata of digital object classes, establishing relational types of digital objects, and generating a scientific research data model, including:
[0024] The relational types of the digital objects include object entity tables, first object extension models, second object extension models, and object relational models; the scientific research data model includes three levels: data class, digital object, and domain. The data class corresponds to datasets with the same data structure and business characteristics, and the digital object is an entity of a data class with a unique identifier.
[0025] Another technical solution adopted in this application embodiment is: a scientific research data modeling device, comprising:
[0026] Digital Object Class Creation Module: This module is used to create digital object classes by uniformly describing the data structure of multimodal scientific research data according to metadata based on the scientific research data modeling algorithm of the DO-IRP protocol under the digital object architecture.
[0027] Identifier Allocation Module: Used to assign a unique digital object identifier to each multimodal scientific research data resource through a defined identifier system;
[0028] Model generation module: Used to define digital object models using metadata of digital object classes, establish relational types of digital objects, and generate scientific research data models;
[0029] Model storage module: Used to parse and store scientific research data models through the scientific research data model running support platform.
[0030] The technical solution adopted in this application embodiment further includes: the digital object class establishment module, based on the DO-IRP protocol under the digital object architecture, uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes a digital object class, specifically:
[0031] The establishment of the digital object class includes a structural description and an access description. The structural description includes a description of the data structure of the multimodal scientific research data through metadata. The access description includes a description of the system access address and addressing method. Specifically, the structural description includes: a structural description of the name, attributes, and value rules of each field or data domain in the data table; an attribute description of the author, title, publication time, publication carrier, and keywords of the digital object file and its content; and a parameter description of the spatiotemporal streaming data. The digital object file includes: JPG image files, EXCEL data files, and PDF report format files. The parameters include: the type of instrument and equipment, and the physical quantities collected.
[0032] Another technical solution adopted in this application embodiment is: an electronic device, the electronic device including a processor and a memory coupled to the processor, wherein,
[0033] The memory stores program instructions for implementing the scientific data modeling method;
[0034] The processor is used to execute the program instructions stored in the memory to control the scientific data modeling method.
[0035] Another technical solution adopted in this application embodiment is: a storage medium storing processor-executable program instructions, the program instructions being used to execute the scientific research data modeling method.
[0036] Compared to existing technologies, the beneficial effects of the embodiments of this application are as follows: The scientific research data modeling method, apparatus, electronic device, and storage medium of the embodiments of this application utilize a digital object model under the DOA architecture to uniformly model multimodal scientific research data, including structured data, unstructured data, and spatiotemporal streaming data. This facilitates the integrated management needs of digital objects and effectively improves the adaptability and system operation efficiency of digital solutions for scientific research data management. By managing scientific research data at the row-level granularity through data description and identification, it is beneficial for subsequent data security and quality management, achieving high-precision security control of scientific research data. The scientific research data model is parsed and stored through a scientific research data model operation support platform, enabling data access and use of SQL data and other digital objects, achieving unified data encapsulation. Through DOA modeling of scientific research data, and using DOIP to achieve system-independent distributed sharing, collaborative innovation of scientific research resources and data is realized among different scientific research institutions and innovation entities. Attached Figure Description
[0037] Figure 1 This is a flowchart of the scientific research data modeling method according to an embodiment of this application;
[0038] Figure 2 This is a diagram of the scientific data modeling algorithm architecture in an embodiment of this application.
[0039] Figure 3 This is a schematic diagram of the scientific data modeling device according to an embodiment of this application;
[0040] Figure 4 This is a schematic diagram of the electronic device structure according to an embodiment of this application;
[0041] Figure 5 This is a schematic diagram of the structure of the storage medium according to an embodiment of this application. Detailed Implementation
[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0043] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or electronic device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or electronic devices.
[0044] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0045] Specifically, please refer to Figure 1 This is a flowchart of a scientific data modeling method according to an embodiment of this application. The scientific data modeling method according to an embodiment of this application includes the following steps:
[0046] S100: Collect multimodal scientific research data to be modeled;
[0047] In this step, the collected multimodal scientific research data includes structured data, unstructured digital object files, and spatiotemporal streaming data. Structured data includes data tables in SQL databases, and unstructured data such as scientific reports, analysis reports, experimental data files, gene sequencing files, and image files are included, but are not limited to data such as temperature, humidity, air pressure, voltage, and current collected by instruments and equipment.
[0048] S110: Based on the DO-IRP protocol under the Digital Object Architecture (DOA), scientific research data modeling algorithms are used to uniformly describe the data structure of multimodal scientific research data according to metadata, and to establish digital object classes;
[0049] In this step, the Digital Object Architecture (DOA) is a logical extension of the existing Internet architecture, capable of supporting data interoperability needs between different systems. The basic element of the DOA is the Digital Object (DO), a unified abstraction of Internet data resources. A DO consists of four parts: identifier, metadata, data description, and DO entity. The identifier is a permanent and unique attribute pointing to a DO; metadata is the descriptive information of the DO, used for retrieval and discovery. The data description includes information such as the DO's attributes, addressing and access points, and access methods, used for locating and accessing the DO. The DO entity is the actual content contained within the DO, which can be any bit sequence or a collection of bit sequences, i.e., a document or data. Modeling DOs based on DOA first requires uniformly describing the DOs according to their metadata.
[0050] Furthermore, embodiments of this application employ scientific research data modeling algorithms within a digital object architecture to model multimodal scientific research data, specifically as follows: Figure 2 The diagram shown illustrates the architecture of a scientific research data modeling algorithm according to an embodiment of this application. The scientific research data modeling algorithm is a software tool based on a front-end and back-end separation model. The front-end uses an interactive method to define the data structure using the attributes and metadata of multimodal scientific research data, and can extend the description of relationships between data models. The back-end is a support platform for running the scientific research data model, which can parse and store the scientific research data model, and can generate data storage entities from the data model through data mapping relationships.
[0051] Specifically, digital object classes are categorized data that provide a unified description of relevant scientific research data. Establishing a digital object class includes structural description and access description. Structural description includes describing the data structure of multimodal scientific research data through metadata, while access description includes describing the system access address and addressing method. Specifically, structural description includes: describing the names, attributes, and value rules of each field or data domain in the data table; describing the attributes of digital object files and content, such as author, title, publication time, publication medium, and keywords; and describing the parameters of spatiotemporal streaming data. Digital object files include: JPG image files, EXCEL data files, and PDF report format files, etc.; parameters include the type of instrument and equipment and the physical quantities collected, etc.
[0052] S120: By establishing an identification system, each multimodal scientific research data resource is assigned a unique digital object identifier across the entire network;
[0053] In this step, the digital object identifier comprises three parts: <Data Center Address Identifier>, <Digital Object Class Identifier>, and <Digital Object Serial Number>. The <Data Center Address Identifier> uses an Internet DNS domain name, such as do.abc.cn. The <Digital Object Class Identifier> is assigned a unique data directory name by the organization. The <Digital Object Serial Number> uses the key field ID from an SQL database or a system-wide serial number for identification. By assigning a globally unique digital object identifier to each multimodal scientific research data resource, access to that resource is not restricted by location, format, or technology.
[0054] S130: Define the digital object model using the metadata of the digital object class, establish the relationship types of digital objects, and generate a scientific research data model;
[0055] In this step, defining the digital object model involves designing a data organization method (model) to meet different application scenarios. For example, in data-driven application scenarios, the Entity-Relationship (ER) model is typically used for storage to address data redundancy and consistency issues in transaction processing. In data analysis scenarios, digital object models include ER models, star schemas, and multidimensional models, etc. This application embodiment uses metadata such as the structural description of digital object classes to define the digital object model, enabling the manipulation and use of digital objects.
[0056] The relational types for digital objects include Object Entity Table (DO), First Object Extension Model (MD), Second Object Extension Model (ME), and Object Relational Model (ER). A detailed description of each relational type is shown in Table 1 below:
[0057] Table 1 Relationship Types of Digital Objects
[0058]
[0059]
[0060] The scientific research data model comprises three levels: data classes, digital objects, and domains. Data classes correspond to datasets with the same data structure and business characteristics, such as data tables in SQL databases, digital object files (such as unstructured documents like scientific reports, analysis reports, experimental data files, gene sequencing files, and image files), and spatiotemporal streaming data collected by scientific instruments and equipment. Data classes contain data description metadata and attributes of the data domain. A digital object is an entity of a data class with a unique identifier.
[0061] S140: The scientific research data model is parsed and stored through the scientific research data model operation support platform;
[0062] In this step, the scientific research data model operation support platform is used to parse and store the generated scientific research data model, solving the storage and access problems of different types of scientific research data, such as traditional SQL databases, digital object files, and spatiotemporal streaming data collected by instruments and equipment.
[0063] Based on the above, the scientific research data modeling method of this application utilizes a digital object model under the DOA architecture to uniformly model multimodal scientific research data, including structured data, unstructured data, and spatiotemporal streaming data. This facilitates the integrated management of digital objects and effectively improves the adaptability and operational efficiency of digital solutions for scientific research data management. By managing scientific research data at the row-level granularity through data description and identification, it facilitates subsequent data security and quality management, achieving highly refined security control of scientific research data. The scientific research data model is parsed and stored through a scientific research data model operation support platform, enabling access and use of SQL data and other digital objects, achieving unified data encapsulation. Through DOA modeling of scientific research data, DOIP is used to achieve system-independent distributed sharing, realizing collaborative innovation of scientific research resources and data among different research institutions and innovation entities.
[0064] Please see Figure 3 This is a schematic diagram of the scientific data modeling device according to an embodiment of this application. The scientific data modeling method device 40 according to an embodiment of this application includes:
[0065] Digital object class creation module 41: Used to create digital object classes by uniformly describing the data structure of multimodal scientific research data according to metadata based on the scientific research data modeling algorithm of the DO-IRP protocol under the digital object architecture;
[0066] Identifier allocation module 42: used to assign a unique digital object identifier to each multimodal scientific research data resource through a defined identifier system;
[0067] Model generation module 43: Used to define digital object models using metadata of digital object classes, establish relational types of digital objects, and generate scientific research data models;
[0068] Model storage module 44: Used to parse and store scientific research data models through the scientific research data model operation support platform.
[0069] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.
[0070] The apparatus provided in this application can be applied to the foregoing method embodiments. For details, please refer to the description of the above method embodiments, which will not be repeated here.
[0071] Please see Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. The electronic device 50 includes:
[0072] Memory 51 storing executable program instructions;
[0073] Processor 52 connected to memory 51;
[0074] The processor 52 is used to call the executable program instructions stored in the memory 51 and perform the following steps: Based on the DO-IRP protocol under the digital object architecture, the data structure of multimodal scientific research data is uniformly described according to the metadata using scientific research data modeling algorithms, and a digital object class is established; a unique digital object identifier is assigned to each multimodal scientific research data resource through the established identification system; the digital object model is defined using the metadata of the digital object class, and the relationship type of digital objects is established to generate a scientific research data model; the scientific research data model is parsed and stored through the scientific research data model operation support platform.
[0075] The processor 52 can also be referred to as a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.
[0076] Please see Figure 5This is a schematic diagram of the storage medium in an embodiment of this application. The storage medium in this embodiment stores program instructions 61 capable of implementing the following steps: Based on the DO-IRP protocol under the Digital Object Architecture, a scientific research data modeling algorithm is used to uniformly describe the data structure of multimodal scientific research data according to metadata, establishing digital object classes; a unique digital object identifier is assigned to each multimodal scientific research data resource through a defined identification system; a digital object model is defined using the metadata of the digital object class, and the relationship types of digital objects are established to generate a scientific research data model; the scientific research data model is parsed and stored through a scientific research data model operation support platform. The program instructions 61 can be stored in the aforementioned storage medium in the form of a software product, including several instructions to cause an electronic device (which may be a personal computer, server, or network electronic device, etc.) or processor to execute all or part of the steps of the methods in various embodiments of this application. The aforementioned storage medium includes various media capable of storing program instructions, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or terminal electronic devices such as computers, servers, mobile phones, and tablets. The server can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.
[0077] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, apparatuses, or units, and may be electrical, mechanical, or other forms.
[0078] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.
Claims
1. A scientific research data modeling method, characterized in that, include: The DO-IRP protocol based on the digital object architecture uses scientific research data modeling algorithms to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes digital object classes; Each multimodal scientific research data resource is assigned a unique digital object identifier across the entire network through the established identification system; The metadata of digital object classes is used to define the digital object model, and the relationship types of digital objects are established to generate a scientific research data model. The scientific research data model is parsed and stored through the scientific research data model operation support platform.
2. The scientific research data modeling method according to claim 1, characterized in that, The DO-IRP protocol based on the digital object architecture uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata. Before establishing the digital object class, it also includes: Collect multimodal scientific research data to be modeled; the multimodal scientific research data includes structured data, digital object files and spatiotemporal streaming data; the structured data includes data tables in an SQL database; the digital object files include, but are not limited to, scientific and technological reports, analysis reports, experimental data files, gene sequencing files and image files; the spatiotemporal streaming data includes, but is not limited to, temperature, humidity, air pressure, voltage, current or image data collected by instruments and equipment.
3. The scientific research data modeling method according to claim 1, characterized in that, The DO-IRP protocol based on the digital object architecture employs a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes digital object classes, including: The scientific research data modeling algorithm is a tool software based on front-end and back-end separation. The front-end uses an interactive method to define the data structure by describing the attributes and metadata of the multimodal scientific research data. The back-end is a scientific research data model running support platform used to parse and store the generated scientific research data model.
4. The scientific data modeling method according to claim 3, characterized in that, The DO-IRP protocol based on the digital object architecture employs a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and establishes digital object classes, specifically: The establishment of the digital object class includes a structural description and an access description. The structural description includes a description of the data structure of the multimodal scientific research data through metadata. The access description includes a description of the system access address and addressing method. Specifically, the structural description includes: a structural description of the name, attributes, and value rules of each field or data domain in the data table; an attribute description of the author, title, publication time, publication carrier, and keywords of the digital object file and its content; and a parameter description of the spatiotemporal streaming data. The digital object file includes: JPG image files, EXCEL data files, and PDF report format files. The parameters include: the type of instrument and equipment, and the physical quantities collected.
5. The scientific data modeling method according to any one of claims 1 to 4, characterized in that, The established identification system assigns a unique digital object identifier to each piece of multimodal scientific research data across the entire network, specifically: The digital object identifier includes: <data center address identifier>, <digital object class identifier>, and <digital object sequence identifier>; wherein, the <data center address identifier> is identified by an Internet DNS domain name, the <digital object class identifier> is assigned a unique data directory name by the organization, and the <digital object sequence identifier> is identified by the key field ID of the SQL database or the system-wide sequence code.
6. The scientific data modeling method according to claim 5, characterized in that, The method of defining a digital object model using metadata of digital object classes and establishing relational types for digital objects to generate a scientific research data model includes: The relational types of the digital objects include object entity tables, first object extension models, second object extension models, and object relational models; the scientific research data model includes three levels: data class, digital object, and domain. The data class corresponds to datasets with the same data structure and business characteristics, and the digital object is an entity of a data class with a unique identifier.
7. A scientific research data modeling device, characterized in that, include: Digital Object Class Creation Module: This module is used to create digital object classes by uniformly describing the data structure of multimodal scientific research data according to metadata based on the scientific research data modeling algorithm of the DO-IRP protocol under the digital object architecture. Identifier Allocation Module: Used to assign a unique digital object identifier to each multimodal scientific research data resource through a defined identifier system; Model generation module: Used to define digital object models using metadata of digital object classes, establish relational types of digital objects, and generate scientific research data models; Model storage module: Used to parse and store scientific research data models through the scientific research data model running support platform.
8. The scientific data modeling device according to claim 7, characterized in that, The digital object class creation module, based on the DO-IRP protocol under the digital object architecture, uses a scientific research data modeling algorithm to uniformly describe the data structure of multimodal scientific research data according to metadata, and creates digital object classes, specifically: The establishment of the digital object class includes a structural description and an access description. The structural description includes a description of the data structure of the multimodal scientific research data through metadata. The access description includes a description of the system access address and addressing method. Specifically, the structural description includes: a structural description of the name, attributes, and value rules of each field or data domain in the data table; an attribute description of the author, title, publication time, publication carrier, and keywords of the digital object file and its content; and a parameter description of the spatiotemporal streaming data. The digital object file includes: JPG image files, EXCEL data files, and PDF report format files. The parameters include: the type of instrument and equipment, and the physical quantities collected.
9. An electronic device, characterized in that, The electronic device includes a processor and a memory coupled to the processor, wherein, The memory stores program instructions for implementing the scientific data modeling method according to any one of claims 1-6; The processor is used to execute the program instructions stored in the memory to control the scientific data modeling method.
10. A storage medium, characterized in that, The device stores processor-executable program instructions for performing the scientific data modeling method according to any one of claims 1 to 6.