A method for establishing an epidemiological ontology database

Abstract

The present invention discloses a method for establishing an epidemiological ontology database, comprising a custom ontology database module for storing epidemiological ontology data; a database call module for loading the custom ontology database module into a survey form, setting a corresponding ontology database for a specific field, and implementing real-time call and retrieval of the custom ontology database module in the corresponding field during the survey or data input process; an instant marking module for acquiring and matching ontology data that matches the input content in real time through an array search function based on the JSON format, and using the ontology data to perform instant marking and matching on the input raw data; and a data storage management module for storing the ontology data annotated by the instant marking module in the custom ontology database module, thereby implementing standardized quality control of the ontology data. The present invention is simple to implement, efficient, and convenient for researchers to widely apply, and plays an important role in improving the quality of data standardization in epidemiological research.

Description

Technical Field

[0001] The present invention belongs to the technical field of databases, and in particular relates to a method for establishing an epidemiological ontology database. Background Art

[0002] An ontology is a standardized description of an object in a specific field. A collection of mappings between objects and their ontologies is an ontology repository. Building an ontology repository is crucial for data standardization and data circulation. By building an ontology repository, we can clarify the relationships between complex professional terms. Using unified, standardized terminology as the ontology, metadata can be described and labeled. Metadata can then be efficiently indexed and integrated through ontologies, enabling comprehensive data mining and analysis.

[0003] In the field of epidemiology, researchers and related institutions both domestically and internationally have developed a series of ontology repositories for researchers to use, such as Gene Ontology (GO), CBioPortal, Epidemiology Ontology (EPO), Genomic Epidemiology Ontology (GenEpiO), Exposure Ontology (ExO), and MedPortal. However, these repositories focus primarily on providing precise definitions of authoritative professional terms, supporting only basic query and indexing functions, functioning more like "dictionaries" and often inefficiently. After data collection is complete, these repositories are often manually annotated based on the repositories, rather than being used in real-time during actual research. This is prone to errors and inefficient. Furthermore, these repositories are often in English, making them inconvenient for practical use in China. With the rapid development of international ontology repositories, some domestic research teams have begun developing localized ontology platforms. The National Population and Health Data Center has developed the MedPortal ontology information storage and application platform, but this platform also lacks the ability for researchers to customize ontologies and provide real-time annotation. In addition, Ontology China has also established tools such as Ontobee and Ontofox in China, but the interface is in English and the application requires some programming basics.

[0004] Therefore, traditional ontology databases have problems such as no support for customization, inconvenient use, inability to call and annotate instantly, insufficient localization, and low efficiency. It is necessary to provide a reliable ontology database to reasonably solve the above problems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method for establishing an epidemiological ontology database in response to the above-mentioned deficiencies in the existing technology, so as to solve the problems that the existing ontology resource library does not support customization, is inconvenient to use, and cannot be called immediately.

[0006] The present invention adopts the following technical solutions:

[0007] A method for establishing an epidemiological ontology database comprises the following steps:

[0008] S1. Use PHP+JavaScript programming language to create a custom ontology database module and a timely marking module, and input the specified ontology data into the custom ontology database module and assign corresponding key values ​​through the interactive operation interface of the timely marking module;

[0009] S2. Build a data storage management module based on the MySQL database, and compile and produce a database call module based on the REDCap platform. The database call module establishes secure communication with the data storage management module to achieve real-time calling and standardized annotation of the local / remote custom ontology database module, thereby completing the establishment of the epidemiological ontology database.

[0010] Specifically, in step S1, the custom ontology database module is used to store epidemiological ontology data; the instant marking module obtains and matches ontology data that matches the input content in real time through an array search function based on the JSON format, and uses the epidemiological ontology data to instantly mark and match the input raw data.

[0011] Specifically, in step S1, the custom ontology database module is embedded in the electronic data collection system REDCap. The custom ontology database module matches the custom ontology and metadata according to the ontology mapping rules to generate a custom ontology database. The timely marking module is used to mark and automatically match the ontology data of the custom ontology database in real time. The data storage management module is used to store the marked ontology data in the custom ontology database to achieve standardized quality control of the ontology data.

[0012] Furthermore, the ontology mapping rules are as follows:

[0013] The matching rules are listed in the form of a value list, the body and metadata are separated by a bar separator, and the matching rules are described using a JSON array.

[0014] Specifically, in step S1, the instant marking module includes:

[0015] Ontology database retrieval module: when calling field data, the electronic data collection system REDCap searches in the custom ontology database module according to the input content and displays the search results in real time;

[0016] The metadata matching module selects the corresponding ontology from the search results and completes the matching between data and ontology;

[0017] Data is marked immediately. Based on the selection results, the input metadata is marked using the ontology, and the metadata is matched one-to-one with the ontology and stored in the corresponding survey records.

[0018] Specifically, in step S2, the database calling module is used to load the custom ontology database module into the survey form, set the corresponding ontology database for the specific field, and realize the real-time calling and retrieval of the custom ontology database module in the corresponding field during the survey process or data input process;

[0019] The data storage management module is used to store the ontology data marked by the instant marking module in the custom ontology database module to achieve standardized quality control of the ontology data.

[0020] Specifically, in step S2, the database calling module includes:

[0021] Design the questionnaire module, import the questionnaire template or edit it online into an electronic questionnaire, and set up various question fields through the electronic data collection system REDCap;

[0022] The database calling module, in the field setting, performs ontology setting for a specific field and specifies the customized ontology database, which is used to call the specified ontology database in real time.

[0023] Specifically, in step S2, when inputting data into the fields set by the database calling module, only standardized data that complies with the ontology database matching rules is allowed to be input.

[0024] Specifically, in step S2, the data storage management module includes:

[0025] Data storage module, which stores data after the entity is marked;

[0026] The data export module exports the data after ontology labeling for data integration and analysis.

[0027] Specifically, in step S1, the custom ontology database module complies with the CSIRO open source software license agreement.

[0028] Compared with the prior art, the present invention has at least the following beneficial effects:

[0029] The present invention provides a method for establishing an epidemiological ontology database, comprising four core modules: a custom ontology database, database call, real-time tagging, and data storage management. Each module is designed and optimized for its own needs. Data communication between modules is achieved through program interfaces. Module functions are rationally designed based on the principles of high cohesion and low coupling, achieving standardized storage and secure, efficient use of the epidemiological ontology database. The custom ontology database facilitates researchers to independently determine, input, and normalize epidemiological ontology data, making it convenient for researchers to use as needed. The database call module communicates with the ontology database via an application programming interface (API), providing a structured data source for the operation and proper functioning of the real-time tagging module and the data storage management module. The widely used MySQL database, a database management system with multiple advantages such as open source, small size, and fast query speed, is used to efficiently implement data storage, management, and indexing. The PHP+JavaScript programming language and MySQL database, widely used general-purpose technical software and code, are convenient to use and feature rich expansion capabilities, facilitating the successful establishment of the ontology database. In the process of implementing the ontology database, the main difference from existing platforms, software and databases lies in the specific implementation of functions. It adopts widely used general technical software and codes, which is convenient to use and conducive to the expansion and development of functional modules of the REDCap system.

[0030] Furthermore, the instant tagging module realizes real-time tagging and automatic matching of ontology data through an array search function based on the JSON format, which facilitates researchers to quickly annotate; by using a variety of methods to customize the matching rules of ontology and metadata and generate a corresponding customized ontology database, it can facilitate different researchers to choose the appropriate structuring method and matching rules of epidemiological ontology data according to actual needs and their own characteristics, which is conducive to expanding the application scope of this database to adapt to various studies or conditions.

[0031] Furthermore, using the REDCap platform to build an ontology database can quickly adapt to the needs of various epidemiological research projects, fully utilize the platform's existing project design, data collection and management tools, improve research efficiency, and reduce the difficulty of building the ontology database.

[0032] Furthermore, custom matching rules for ontology and metadata come in three forms: a value list approach, which is easy to use and simply lists matching rules, making it easier to build a simple ontology database; a stripe-separated mode, which requires data to be organized in a contingency table format, with the ontology and metadata separated by a delimiter. This creates a structured ontology database and facilitates rapid import from existing ontology databases; and a JSON array mode, which uses a JSON array to describe matching rules and is suitable for building large ontology databases. These three forms expand the scope of ontology database use, making it easier for researchers to build appropriate ontology databases based on their research types and data requirements.

[0033] Furthermore, by developing an instant tagging module, the ontology that matches the input content can be obtained and matched in real time, and the input raw data can be marked instantly with the ontology.

[0034] Furthermore, the database call module facilitates loading the customized ontology database into the survey form when designing the survey form and setting the corresponding ontology database for specific fields, thereby realizing real-time call and retrieval based on the customized ontology database during the survey process or data input process.

[0035] Furthermore, the database call module may only allow the input of standardized data during the data input process, integrating the data input process with the standardization process, thereby reducing the tedious work of subsequent data labeling and management.

[0036] Furthermore, by developing a data storage management module, the data can be standardized after the ontology and metadata matching tags are stored, which facilitates subsequent data communication, management and analysis.

[0037] Furthermore, the data storage management module stores the labeled ontology data in a custom ontology database, efficiently realizing standardized quality control of the ontology data. The present invention establishes a custom customized ontology database for data quality control and annotation based on the mapping rules specified by the user, and realizes real-time call during the data collection process in the epidemiological survey stage. The existing ontology database platform is only an online query tool that integrates authoritative ontology data, and cannot be customized according to needs and called in real time during use.

[0038] Furthermore, the epidemiology ontology database complies with the open source software license agreement of the Joint Scientific and Industrial Research Organization (CSIRO) and is available free of charge to scientific researchers conducting non-profit epidemiological research. It provides tools for customizing the ontology database to facilitate real-time call of the ontology database in research, achieve data standardization, and promote the development of the discipline of epidemiology.

[0039] In summary, the present invention selects appropriate mapping rules and establishes a custom ontology database according to pre-established ontology mapping rules, thereby realizing real-time quality control and standardized annotation of data collected during epidemiological surveys. The implementation method is simple and efficient, and is convenient for researchers to widely apply.

[0040] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a functional module structure diagram of a customized epidemiological ontology database proposed in the present invention;

[0042] Figure 2 It is the setting interface for customizing the ontology database module;

[0043] Figure 3 To call the search result interface of the ontology database;

[0044] Figure 4 It is the standardized data display interface after ontology labeling. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] In the description of the present invention, it is to be understood that the terms “include” and “comprise” indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0047] It should also be understood that the terms used in the present specification are only for the purpose of describing particular embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0048] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0049] The accompanying drawings illustrate various schematic diagrams of structures according to embodiments disclosed herein. These figures are not drawn to scale; for clarity, some details are exaggerated and some details may be omitted. The shapes of the various regions and layers shown in the figures, as well as their relative sizes and positional relationships, are merely exemplary and may deviate in practice due to manufacturing tolerances or technical limitations. Those skilled in the art may design regions / layers with different shapes, sizes, and relative positions as needed.

[0050] The present invention provides a method for establishing an epidemiological ontology database, comprising the following steps:

[0051] S1. Build REDCap, an electronic data collection system for clinical research;

[0052] REDCap, an electronic data collection system for clinical research, was built based on the REDCap platform source code, the PHP+JavaScript programming language, and the MySQL database engine. The REDCap system includes modules for project management, project design, data collection and quality control, and data management. The established REDCap system provides high-quality project management and secure and efficient data collection tools for epidemiological surveys and research.

[0053] S2. Embed the custom ontology database module (SimpleOntology Module) into the REDCap system built in step S1;

[0054] The custom ontology database module complies with the CSIRO open source software license agreement, supports multiple languages, and can provide customized ontology databases and real-time call functions.

[0055] A custom ontology database module is embedded into the REDCap system to realize the custom construction and instant call functions of the ontology database.

[0056] S3. Establish a custom ontology database;

[0057] Through the custom ontology database module, the matching rules between custom ontology and metadata are adopted, and the corresponding custom ontology database is generated and stored in the REDCap system;

[0058] See also Figure 1 ,The epidemiological ontology database includes : a custom ontology database module, a ,database call module, an instant marking module and a data storage ,management module.

[0059] The custom ontology database module is used by researchers to define the ontology database according to their research purposes and store it in the system for easy access.

[0060] The custom ontology database module includes ontology database construction and import.

[0061] To build an ontology database, researchers define a set of rules for matching metadata with their ontology based on their research objectives, and record them in JSON arrays, Excel spreadsheets, and other formats. Importing an ontology database is accomplished through the "Ontology" module described in this invention, which allows ontology databases in a specific format to be imported and stored in the cloud for easy access.

[0062] The database call module is used to specify the fields that need to call the ontology database when designing the questionnaire, and set the corresponding ontology database for the field. When inputting data into the set fields, only standardized data that meets the matching rules of the ontology database is allowed to be input.

[0063] The database calling module includes designing questionnaires and calling databases.

[0064] To design the questionnaire module, researchers imported the questionnaire template or edited it online into an electronic questionnaire, and used the data collection tool design function of the REDCap system to set various question fields.

[0065] The database calling module, in the field setting, performs ontology setting for a specific field or fields and specifies a customized ontology database for it, so that when the field data is entered during the survey process, the specified ontology database is called in real time.

[0066] The instant tagging module is used to obtain and match the ontology that matches the input content in real time during the process of filling in the survey data, and then use the ontology to instantly tag the input raw data to achieve standardization in the data input process.

[0067] The instant tagging module includes ontology database retrieval, metadata matching and data instant tagging.

[0068] Ontology database search means that when you input the field data of the ontology database, the system will automatically search the ontology database based on the input content, supporting multiple methods such as single keyword search and whole sentence search, and display the search results in real time in the drop-down box of the field text box, such as Figure 3 As shown in the figure. Metadata matching involves the data entry personnel selecting the corresponding ontology from the search results based on metadata characteristics and work experience, thereby matching the data with the ontology. Instant data tagging involves the system automatically tagging the input metadata with the ontology based on the data entry personnel's selection, establishing a one-to-one correspondence between the metadata and the ontology, and storing it in the survey record.

[0069] The data storage and management module is used to store standardized data after the ontology and metadata matching tags are completed. The data includes the original input data and its corresponding ontology. Researchers can export the data into data sets suitable for various statistical software formats such as SPSS, SAS, and R, and realize data circulation and statistical analysis through the ontology.

[0070] The data storage and management module includes data storage and data export. After ontology-labeled data is stored in the system's cloud, it can be viewed, modified, deleted, and other operations. Data export involves exporting standardized labeled data, including metadata and corresponding ontology, into a format compatible with major statistical analysis software for subsequent data integration and analysis.

[0071] S4, calling the custom ontology database established in step S3;

[0072] When setting up the data collection tool in the REDCap system, you can set it to call the corresponding ontology database in one or several fields, so that the specified ontology database can be called in real time during the data input process of the field;

[0073] S5. Real-time ontology tagging during the survey process. After setting up the ontology database in a certain entry, the corresponding ontology can be searched and matched according to the input content during the survey data input process. The standardized ontology is used to tag the data during the entry input process, and data standardization is completed quickly.

[0074] S6. Data storage and export.

[0075] See also Figure 4 ,The standardized data after ontology labeling can be stored in the REDCap system cloud for ,viewing, modification and other operations, and can also be further exported into ,a format suitable for various statistical software for subsequent statistical ,analysis.

[0076] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0077] The ontology database proposed in this application can be used in major universities, hospitals, scientific research institutions, etc., specifically to quickly achieve data standardization and ensure data flow and interoperability, saving manpower and material resources, and facilitating subsequent data integration and analysis.

[0078] This system is developed based on the REDCap platform source code, the PHP+JavaScript programming language, and the MySQL database engine. It complies with the CSIRO open source software license agreement and supports multiple languages. It provides customizable ontology databases, real-time call processing, and instant tagging capabilities. It comprises four functional modules: a custom ontology database module, a database call module, an instant tagging module, and a data storage and management module.

[0079] See also Figure 2 ,The operation rules of the custom ontology database module include:

[0080] First, define the correspondence rules between ontology and metadata according to the research purpose. A series of correspondence rules are integrated to form the original ontology database, which can be stored in any form, such as Excel spreadsheet, text list, JSON array, etc.

[0081] Secondly, the customized ontology database is input into the system. This can be achieved through the settings of the "Ontology" module. Through the settings, the name, type, language, search method, etc. of the ontology database can be specified. Languages ​​include Chinese, English, Spanish, etc.

[0082] There are two search methods: "Word-based" and "Complete Match".

[0083] In the "word-based" type, the REDCap system searches for each word typed (separated by spaces) separately. For example, if you type "cholera mild," the search results for "cholera" and "mild" will be returned at the same time.

[0084] "Complete Match" performs a full-text match search. The system treats the entire text entered in the text box as a keyword for full-text match search. By checking "When no matching results are found, display 'No results found'" you can set the objects and entities that are displayed when no matching results are found.

[0085] The system reads values ​​in three predefined modes: "Value List," "Bar-delimited - Ontology | Object," and "JSON Array." Beyond the format, the ontology module does not specify the language or content of values; it can be correctly read, set, and displayed in any language. Researchers can freely fill in the value according to their specific needs and research context, enabling the construction of a highly customized ontology repository.

[0086] Finally, the system will store the researcher's customized ontology database in the cloud for the next step of modification, calling, marking and other operations.

[0087] The database call module is used to load a customized ontology database into the survey form. It sets the corresponding ontology database for a specific field, enabling real-time call and retrieval of the ontology database within that field during the survey or data input process. After completing the ontology resource library setup, enabling the ontology function in the survey form allows real-time call of the ontology resource library during the questionnaire survey.

[0088] First, design the questionnaire using the electronic form (data collection tool) design function of the REDCap system. Then, depending on the research objectives, enable the ontology database in one or more fields. On the collection tool settings page, click "Add Field," select the field type that supports the ontology function - "Text Box," and then select the ontology function in the verification options on the right. Select the corresponding ontology name. It should be noted that different fields can use the same ontology database or different ones, making the setup operation simple and flexible.

[0089] The instant tagging module is used to perform instant retrieval, matching, and tagging of the ontology database during data input. After designing the data collection tool and enabling the ontology function, click "Add / Edit Record" to enter the data input interface of the questionnaire. Type the data in the text box of this field. In the data input interface, the search results will be displayed in the drop-down box. Researchers can click the correct search result according to the actual situation to complete the ontology matching and tagging. The final storage content of this text box can only be the search result clicked in this step, and the input content cannot be finally stored. Therefore, it is guaranteed that all the data in this field comes from the standardized data of the annotated ontology in the ontology resource library, avoiding problems such as incorrect filling and random filling that affect data quality.

[0090] The data storage management module can realize the function of storing and managing the data after ontology standardization and labeling, and complete the data display format after ontology matching and labeling. Figure 4 As shown, the content displayed in the text box is the input object, namely the disease name, and the content displayed on the right side of the text box is the corresponding ontology, namely the ICD10 code. This part of the data will be saved in the database in the form of object and ontology matching, which can be used for subsequent query, modification, export and statistical analysis.

[0091] Conducting a population survey based on the customized epidemiological ontology database of the present invention includes the following steps:

[0092] Step 1: Researchers customize the ontology database of a certain field according to research needs, or import an existing ontology database;

[0093] Step 2: Based on the custom ontology database module, import and store the ontology database into the RE DCap system;

[0094] Step 3: Design the electronic form, set the required fields, and call the ontology database;

[0095] Step 4: Input the survey data. Based on the input data and its corresponding search results, select the appropriate ontology to complete the matching and instant ontology tagging.

[0096] Step 5: Data storage and management.

[0097] The standardized data after ontology labeling is stored in the system cloud, or exported to the required format for statistical analysis.

[0098] In summary, the present invention provides a method for establishing an epidemiological ontology database and a customized epidemiological ontology database, which has the following characteristics:

[0099] It is possible to implement customized matching rules between ontology and metadata, complete the construction of ontology resource library, mark homogeneous metadata with the same ontology, and integrate various databases through ontology for subsequent analysis and research.

[0100] The ontology resource library set by researchers can be used to complete the unified annotation of raw data during the data collection stage, achieving high customization and standardization of the research database and avoiding the subsequent tedious labeling work.

[0101] It is simple to operate, supports Chinese, is easy to use, and saves manpower and material resources.

[0102] It supports a variety of research survey designs, meets the actual needs of research designers, and greatly improves the efficiency of scientific researchers.

[0103] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0104] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0105] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0106] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0107] The above content is only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A method for establishing an epidemiological ontology database, characterized in that: The following steps are involved: S1. Use PHP+JavaScript programming language to create a custom ontology database module and an instant tagging module. Input the specified ontology data into the custom ontology database module and assign corresponding key values ​​through the interactive operation interface of the instant tagging module. The custom ontology database module is embedded in the electronic data collection system REDCap. The custom ontology database module matches the custom ontology and metadata according to the ontology mapping rules to generate a custom ontology database. The instant tagging module is used to perform real-time tagging and automatic matching on the ontology data in the custom ontology database. The data storage management module is used to store the marked ontology data in the custom ontology database to achieve standardized quality control of the ontology data. The ontology mapping rules are as follows: Use a value list to list the matching rules, use a bar separator to separate the body and metadata, and use a JSON array to describe the matching rules; S2. Build a data storage management module based on the MySQL database, and compile and create a database call module based on the REDCap platform. The database call module establishes secure communication with the data storage management module to achieve real-time call and standardized annotation of local / remote custom ontology database modules, completing the establishment of the epidemiological ontology database. The database call module is used to load the custom ontology database module into the survey form, set up the corresponding ontology database for specific fields, and achieve real-time call and retrieval of the custom ontology database module in the corresponding fields during the survey or data input process. The data storage management module is used to store the ontology data marked by the instant marking module in the custom ontology database module to achieve standardized quality control of the ontology data.

2. The method for establishing an epidemiological ontology database according to claim 1, characterized in that: In step S1, the custom ontology database module is used to store epidemiological ontology data; the instant marking module obtains and matches ontology data that matches the input content in real time through an array search function based on the JSON format, and uses the epidemiological ontology data to instantly mark and match the input raw data.

3. The method for establishing an epidemiological ontology database according to claim 1, wherein: In step S1, the instant marking module includes: Ontology database retrieval module: when calling field data, the electronic data collection system REDCap searches in the custom ontology database module according to the input content and displays the search results in real time; The metadata matching module selects the corresponding ontology from the search results and completes the matching between data and ontology; Data is marked immediately. Based on the selection results, the input metadata is marked using the ontology, and the metadata is matched one-to-one with the ontology and stored in the corresponding survey records.

4. The method for establishing an epidemiological ontology database according to claim 1, wherein: In step S2, the database calling module includes: Design the questionnaire module, import the questionnaire template or edit it online into an electronic questionnaire, and set up various question fields through the electronic data collection system REDCap; The database calling module, in the field setting, performs ontology setting for a specific field and specifies the customized ontology database, which is used to call the specified ontology database in real time.

5. The method for establishing an epidemiological ontology database according to claim 1, wherein: In step S2, when inputting data into the fields set by the database call module, only standardized data that complies with the ontology database matching rules is allowed to be input.

6. The method for establishing an epidemiological ontology database according to claim 1, wherein: In step S2, the data storage management module includes: Data storage module, which stores data after the entity is marked; The data export module exports the data after ontology labeling for data integration and analysis.

7. The method for establishing an epidemiological ontology database according to claim 1, wherein: In step S1, the custom ontology database module complies with the CSIRO open source software license agreement.

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