Data operation management method and system

Abstract

The invention provides a data operation management method and system, and the method comprises the steps: distributing labels for a plurality of data sources according to the sources, and dividing public data according to structured public data and unstructured public data; grading is carried out according to the sensitivity of the public data, and the public data after label division and grading are obtained; auditing the application of the data service provider needing to obtain the public data, and authenticating the data service provider after auditing to obtain public data development authority conforming to auditing; distributing the demand of the public data to a data service provider for development; verifying the public data product which is developed by the data service provider and corresponds to the demand, and issuing and displaying the public data product which passes the verification in a portal; and the whole life cycle of the public data is supervised through the block chain. The system comprises a data processing module, a demand distribution module and a publishing and displaying module. According to the invention, standardized, secure and efficient management of public data is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of public data management, and in particular to a data operation management method and system. Background Art

[0002] As a vital component of data resources, public data holds immense economic and social value and forms a crucial foundation for the transformation of digital systems. As a crucial component of data resources, public data accounts for 70%-80% of the total data volume. Currently, my country has begun to comprehensively deploy and implement a public data openness system to provide guidance for regional digital development and sharing.

[0003] Prior Art 1, application number CN202311539200.X, discloses a data model integration system for the development and utilization of public data, including: a data management module that acquires and manages data sets; a model development module that extracts data sets from the data management module and uses the extracted data sets to develop artificial intelligence models; a model database that stores the developed artificial intelligence models; a model deployment module that calls the artificial intelligence models to provide external model application services; and an operations management module that manages the model development module and the model deployment module. Although an isolated sandbox space is constructed to support all processes from data access, model development, and model application, in a distributed environment, models can be developed and deployed to business applications more quickly than before, and the time for data model training and deployment can be significantly simplified and shortened, truly making artificial intelligence accessible, it mainly focuses on the development and deployment of artificial intelligence models and lacks refined classification management and security grading of the public data itself.

[0004] Prior art 2, application number: CN202410107498.5 discloses a business operation management system for an economic park, including a park management terminal, an enterprise user terminal, and an agent investment terminal. The permissions of the system login user are set according to the business operation management objects of the economic park. The management personnel conduct operation management through the park management terminal. The park management terminal includes investment management, certificate management, finance and taxation management, enterprise management, park management, personnel management, data center, and tool management; the enterprise user terminal is used for business management by industrial and commercial households in the economic park. The enterprise user terminal includes enterprise information, park information, and value-added services; the agent investment terminal is used by investment agencies, which submits industrial and commercial registration information in real time and receives the enterprise processing progress data transmitted by the enterprise user terminal for comprehensive statistical management. The agent investment terminal includes investment information, investment data, and investment agent management. Although full coverage of business applications has been achieved, the user system of the investment management platform has been improved, and the online investment model has been enriched, it is mainly aimed at business management such as investment promotion, certificate application, finance and taxation within the park, and does not involve the development and sharing of public data.

[0005] Prior Art 3, application number CN202410304355.3, discloses a big data-based smart park operations management platform. By monitoring and analyzing historical energy consumption data of monitored energy equipment, this platform identifies abnormal performance characteristics of the equipment and then determines whether any abnormalities exist. While this platform can promptly alert relevant technicians to take appropriate measures, such as repairing, adjusting, or replacing abnormal parts, to reduce energy waste and safety hazards, it primarily focuses on identifying equipment energy consumption and abnormal conditions, and does not address the full lifecycle supervision of public data.

[0006] Currently, existing technologies 1, 2, and 3 have deficiencies in public data classification management, development and sharing, and transparent supervision. They lack standardized, secure, and efficient management of public data, and cannot fully reflect the value of public data resources. Therefore, the present invention provides a data operation and management method and system. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a data operation management method, comprising the following steps:

[0008] Assign labels to several data sources according to their sources, obtain public data from several data sources, and classify the public data into structured public data and unstructured public data; classify the public data according to its sensitivity, and obtain labeled and classified public data;

[0009] Review applications from data service providers who need to obtain public data, authenticate the data service providers after review, and obtain public data development permissions that meet the review requirements; allocate public data requirements to data service providers for development;

[0010] Verify the public data products developed by data service providers that correspond to the needs, and publish and display the verified public data products in the portal; supervise the entire life cycle of public data through blockchain.

[0011] Optionally, the process of obtaining labeled and classified public data includes the following steps:

[0012] After obtaining public data, the data is divided into structured data and unstructured data according to the existence form of the public data. Public data with fields and formats are classified as structured data, and public data without fixed formats and structures are classified as unstructured data.

[0013] After completing the division of structured data and unstructured data, analyze the content, usage, and potential impact to determine sensitivity and classify structured data and unstructured data;

[0014] The public data that have been labeled and graded are integrated into a resource library, and each public data has source label, structure type and sensitivity level information.

[0015] Optionally, structured data is in the form of fields and formats of tables, databases, and spreadsheets; unstructured data includes text files, images, audio, video, and social media content, and does not have a fixed format and structure.

[0016] Optionally, the process of assigning public data requirements to data service providers for development includes the following steps:

[0017] Based on the applications submitted by data service providers, we analyze the matching degree between their development requirements and public data and screen the data service providers;

[0018] The data service providers that have passed the screening will be subject to qualification review. Based on the service provider's historical development record, industry reputation, and the professional background of the technical team, a comprehensive assessment will be made as to whether they have the ability to develop public data. Service providers that pass the review will be granted corresponding development permissions.

[0019] Based on the development authority of the data service provider, specific public data requirements will be allocated to the development platform of the data service provider. For highly sensitive public data, encrypted transmission and access control mechanisms will be adopted.

[0020] Optionally, the process of comprehensively determining whether an enterprise has the ability to develop public data includes the following steps:

[0021] Conduct a preliminary analysis of the application submitted by the data service provider to extract key information such as its technical capabilities, development experience, and target application scenarios. Combined with the data service provider's historical development records, analyze the completion status of past projects, technical implementation results, and user feedback, and extract the data service provider's technical capability characteristics from the massive historical development records.

[0022] Evaluate the industry reputation of the data service provider and correlate its industry performance with its technical capabilities. Analyze its collaboration record, customer reviews, and technical influence within the industry to determine its professionalism and reliability. Analyze the background of the data service provider's technical team and compare the team's technical expertise with public data development requirements to determine its ability to complete development tasks.

[0023] The analysis results of technical capability characteristics, industry reputation and technical team background are comprehensively evaluated to generate a capability score for the data service provider, and whether to grant it development permissions is decided based on the score results.

[0024] Optionally, the process of generating a data service provider capability score includes the following steps:

[0025] Verify the input comprehensive technical capability characteristic value, industry reputation and technical team background matching. If any anomaly is found, the evaluation will be terminated and an error message will be returned. According to the preset rules, initial weights are assigned to the comprehensive technical capability characteristic value, industry reputation and technical team background matching respectively.

[0026] Calculate the preliminary score using a weighted formula, check the distribution of each score based on the preset dynamic adjustment rules, and normalize the preliminary score to the range of [0, 100];

[0027] Set a scoring threshold. If the normalized score is greater than or equal to the threshold, the data service provider is determined to have development capabilities and development permissions are granted; otherwise, it is determined that it does not have development capabilities and permissions are denied. Output the normalized score and judgment results as a basis for decision-making.

[0028] Optionally, the process of assigning initial weights according to a preset rule includes the following steps:

[0029] Collect the data service provider's historical development records, industry reputation, and technical team's professional background to obtain the corresponding multiple comprehensive technical capability characteristic values, industry reputation, and technical team background matching; and conduct development authority impact analysis to obtain multiple development authority impacts;

[0030] For different development permissions, the weights of development permissions are assigned based on the influence of multiple development permissions, and multiple initial weights are obtained for historical development records, industry reputation, and professional background of the technical team;

[0031] Based on the initial weights, a development permission database with preset rules is constructed to store the weight allocation rules; dynamic adjustments are made based on real-time feedback from the scoring results.

[0032] Optionally, the process of obtaining the impact of multiple development permissions includes the following steps:

[0033] Based on the data service provider's historical development records, industry reputation, and technical team's professional background, we extract multiple comprehensive technical capability feature values, industry reputation, and technical team background matching degrees. We then correlate these comprehensive technical capability feature values, industry reputation, and technical team background matching degrees by data service provider to form an initial data set.

[0034] Each data service provider is a node in the graph, and its node attributes include technical capability characteristics, industry reputation score, and team background matching. Each project is a node in the graph, and its node attributes include project scale, technical complexity, and delivery time.

[0035] Through the performance of the data service provider in the project, the relationship between the data service provider and the project is established; through the industry reputation score of the data service provider, the relationship between the data service provider and the industry reputation is established; through the matching degree of the data service provider's technical team background, the relationship between the data service provider and the team background is established, and the impact of development permissions is determined based on the relationship.

[0036] Optional verification of the public data products developed by the data service provider that meet the requirements includes the following steps:

[0037] Conduct integrity checks on public data products submitted by data service providers to ensure that they contain all required data fields and content. By comparing the structure of the requirements document with the data product, verify whether the data product covers all specified data dimensions and check for missing or redundant data.

[0038] During the verification process, blockchain technology is used to monitor the entire life cycle of data products, recording every key node from development to release, including data sources, processing, verification results, and release status.

[0039] Feedback the verification results to the data service provider, and optimize the data products based on the verification results.

[0040] The present invention provides a data operation management system, comprising:

[0041] The data processing module is responsible for assigning labels to several data sources according to their sources, obtaining public data from several data sources, and classifying the public data into structured public data and unstructured public data; classifying the public data according to its sensitivity, and obtaining the labeled and classified public data;

[0042] The demand allocation module is responsible for reviewing applications from data service providers who need to obtain public data, authenticating the data service providers after review, and obtaining public data development permissions that meet the review requirements; and allocating public data requirements to data service providers for development;

[0043] The publishing and display module is responsible for verifying the public data products developed by data service providers that correspond to the needs, and publishing and displaying the verified public data products in the portal; and supervising the entire life cycle of public data through blockchain.

[0044] The present invention achieves refined classification management of public data by assigning labels to data sources, dividing structured and unstructured data, and grading them according to sensitivity; by reviewing and authenticating the applications of data service providers, it ensures that only qualified service providers can obtain development permissions and standardizes the access mechanism of data service providers; by verifying the public data products developed by data service providers, it ensures that they meet the requirements and quality standards, and publishes and displays them in the portal, achieving standardized management and openness and transparency of data products; through blockchain technology, the entire life cycle of public data is supervised, the traceability and non-tamperability of public data are achieved, and the transparency and security of public data management are enhanced.

[0045] Other features and advantages of the present invention will be described in the following description, and some of the contents will be more clearly demonstrated through the accompanying drawings and examples, and can also be obtained by practicing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and drawings.

[0046] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 This is a flow chart of the data operation management method in Example 1 of the present invention;

[0049] Figure 2 This is a schematic diagram of the data operation management method in Example 1 of the present invention;

[0050] Figure 3 This is a process diagram for obtaining public data after label division and classification in Example 2 of the present invention;

[0051] Figure 4 A diagram showing the process of allocating public data requirements to data service providers for development in Example 3 of the present invention;

[0052] Figure 5 This is a process diagram for comprehensively determining whether a device has the ability to develop public data in Example 4 of the present invention;

[0053] Figure 6 A diagram showing the process of generating a capability score for a data service provider in Example 5 of the present invention;

[0054] Figure 7 This is a diagram of the process of allocating initial weights according to preset rules in Example 6 of the present invention;

[0055] Figure 8 This is a process diagram for obtaining the influence of multiple development permissions in Example 7 of the present invention;

[0056] Figure 9 This is a process diagram for verifying a public data product developed by a data service provider that corresponds to a demand in Example 8 of the present invention;

[0057] Figure 10 This is a block diagram of the data operation and management system in Example 9 of the present invention. DETAILED DESCRIPTION

[0058] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0059] The terms used in the embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present application. The singular forms "a", "the" and "the" used in the embodiments of the present application are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0060] When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements, unless the context clearly indicates otherwise. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0061] Example 1: Figure 1 As shown, an embodiment of the present invention provides a data operation management method, comprising the following steps:

[0062] S100: Assign labels to multiple data sources based on their sources, obtain public data from the multiple data sources, and classify the public data into structured public data and unstructured public data; classify the public data based on its sensitivity, and obtain labeled and classified public data; public data refers to data resources with public attributes that are controlled, managed, and provided by the government or public institutions, and are derived from government activities, public services, social governance, and other fields of government departments, covering multiple aspects such as the economy, society, people's livelihood, and the environment;

[0063] S200: Review applications from data service providers who need to obtain public data. After review, authenticate the data service providers and obtain public data development permissions that meet the review requirements. Allocate public data requirements to data service providers for development.

[0064] S300: Verify the public data products developed by data service providers that correspond to the needs, and publish and display the verified public data products in the portal; supervise the entire life cycle of public data through blockchain.

[0065] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first assigns labels to several data sources according to their sources, obtains public data from several data sources, and divides the public data into structured public data and unstructured public data; grades the public data according to its sensitivity, and obtains public data with labels, divisions and classifications; secondly, reviews the application of the data service provider who needs to obtain public data, and authenticates the data service provider after the review to obtain the public data development authority that meets the review; allocates the public data demand to the data service provider for development; finally, verifies the public data products developed by the data service provider that correspond to the demand, and publishes and displays the verified public data products in the portal; supervises the entire life cycle of public data through blockchain (the principle of which is shown in the attached figure). Figure 2 ). The steps of the above scheme achieve refined classification management of public data by assigning labels to data sources, dividing structured and unstructured data, and grading them according to sensitivity; by reviewing and authenticating the applications of data service providers, ensuring that only qualified service providers can obtain development permissions, and standardizing the access mechanism of data service providers; by verifying the public data products developed by data service providers, ensuring that they meet the requirements and quality standards, and publishing and displaying them in the portal, achieving standardized management and openness and transparency of data products; through the use of blockchain technology to supervise the entire life cycle of public data, achieving traceability and non-tamperability of public data, and enhancing the transparency and security of public data management. This embodiment realizes the standardized, secure and efficient management of public data, enhances the value of public data resources, and provides technical support for the healthy development of the data ecosystem.

[0066] Example 2: Figure 3 As shown, based on Example 1, the process of obtaining public data with label division and classification provided by the embodiment of the present invention includes the following steps:

[0067] S101: After obtaining public data, classify the public data into structured data and unstructured data according to the existence form of the public data, classify the public data with fields and formats as structured data, and classify the public data without fixed formats and structures as unstructured data;

[0068] Structured data has clear fields and formats in tables, databases, and spreadsheets, such as annual economic data and census data released by government statistics departments. Unstructured data includes text files, images, audio, video, social media content, etc., which lack fixed formats and structures. For example, government policy documents, user feedback in public services, and image data from environmental monitoring.

[0069] S102: After completing the classification of structured data and unstructured data, analyze the content, usage, and potential impact to determine sensitivity and classify the structured data and unstructured data;

[0070] S103: Integrate the labeled and graded public data into a resource library, where each public data has a source label, structure type and sensitivity level information.

[0071] The working principle and beneficial effects of the above technical solution are as follows: First, after obtaining public data, this embodiment divides the public data into structured data and unstructured data according to the existence form of the public data, and divides the public data with fields and formats into structured data, and divides the public data without a fixed format and structure into unstructured data; among them, structured data has clear fields and formats such as tables, databases and spreadsheets, for example, annual economic data and census data released by government statistical departments; unstructured data includes text files, images, audio, video, social media content, etc., which lack a fixed format and structure; for example, policy documents released by the government, user feedback in public services, image data in environmental monitoring, etc.; secondly, after completing the division of structured data and unstructured data, the content, purpose and potential impact are analyzed to determine the sensitivity, and the structured data and unstructured data are graded; finally, the public data after label division and grading are integrated into a resource library, and each public data has a source label, structure type and sensitivity level information. By labeling and grading public data and combining the various steps, the above solution enables public data operations management to achieve more efficient, accurate, and secure resource integration and utilization. Dividing public data into structured and unstructured data can help operations managers quickly identify the organizational form of the data, thereby adopting appropriate processing and analysis methods for different types of data. For example, structured data can be directly used for data analysis and modeling, while unstructured data can be deeply mined through technologies such as natural language processing and image recognition. Secondly, by grading the sensitivity of data based on its content, purpose, and potential impact, it is possible to effectively identify highly sensitive data and less sensitive data, and adopt differentiated management strategies during data sharing and openness. For example, for highly sensitive data, access control and encryption protection can be strengthened to ensure data security; while for less sensitive data, it can be more widely opened and shared, promoting data circulation and innovative applications. The grading mechanism not only improves the level of refinement of data management, but also provides guarantees for the safe and compliant use of data. Finally, the labeled and graded public data is integrated into a resource library, with additional source tags, structure types, and sensitivity level information. This provides data users with clear data context and attribute information. The establishment of the resource library not only facilitates data retrieval and access, but also facilitates cross-departmental and cross-domain data collaboration. Furthermore, through labeling management, operations managers can more efficiently monitor data usage, promptly identify and resolve potential issues, and thus improve the overall operational efficiency of public data.

[0072] In summary, this embodiment enables technical optimization of public data operation and management in terms of data classification, security classification, and resource integration, providing strong support for the efficient use and secure sharing of public data.

[0073] Example 3: Figure 4 As shown, based on Example 1, the process of allocating public data requirements to data service providers for development provided by this embodiment of the present invention includes the following steps:

[0074] S201: Based on the applications submitted by data service providers, analyze the matching degree between their development requirements and public data, and screen the data service providers;

[0075] S202: Qualification review of data service providers who have passed the screening process will be conducted. A comprehensive assessment will be made of their historical development records, industry reputation, and the professional background of their technical team to determine whether they have the ability to develop public data. Service providers who have passed the review will be granted corresponding development permissions.

[0076] S203: Based on the development authority of the data service provider, specific public data requirements are allocated to the development platform of the data service provider. For highly sensitive public data, encrypted transmission and access control mechanisms are adopted.

[0077] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first analyzes the matching degree between the development requirements and public data of the data service providers based on the applications submitted by the data service providers, and screens the data service providers; secondly, the qualifications of the data service providers that pass the screening are reviewed, and the service providers are comprehensively judged to determine whether they have the ability to develop public data based on their historical development records, industry reputation and the professional background of their technical team; the service providers that pass the review will be granted corresponding development permissions; finally, based on the development permissions of the data service providers, specific public data requirements will be allocated to the development platform of the data service providers. For highly sensitive public data, encrypted transmission and access control mechanisms will be adopted. The above solution can accurately identify suitable data service providers by analyzing the matching degree between the development needs of data service providers and public data, ensure the efficiency and pertinence of public data allocation, realize preliminary screening, avoid waste of resources, and provide a reliable basis for qualification review and authority allocation; conduct qualification review on the data service providers that pass the screening, and comprehensively evaluate their development capabilities based on their historical development records, industry reputation and the professional background of the technical team; ensure that only service providers with corresponding technical strength and compliance can obtain development permissions, thereby ensuring the quality and security of public data development; allocate specific public data needs to their development platform according to the development permissions of the data service provider, and protect highly sensitive public data through encrypted transmission and access control mechanisms, which not only achieves efficient allocation of public data, but also ensures the security of public data during transmission and use through technical means, and prevents the leakage or abuse of public data.

[0078] In summary, this embodiment has built a complete process from demand matching, qualification review to public data distribution and security control, achieving efficient, secure and standardized distribution of public data needs. Through intelligent screening and qualification review, the matching of the development capabilities of data service providers with public data needs is ensured; through encrypted transmission and access control mechanisms, the security of highly sensitive data is guaranteed; it not only improves the efficiency and quality of public data development, but also provides a standardized development environment for data service providers, promoting the effective use and social application of public data resources. At the same time, through technical means, the transparency and traceability of the data distribution process are achieved, providing technical support for the compliance and security of public data management.

[0079] Example 4: Figure 5 As shown, based on Example 3, the process of comprehensively determining whether a user has the ability to develop public data provided by the embodiment of the present invention includes the following steps:

[0080] S2021: Conduct a preliminary analysis of the application submitted by the data service provider to extract key information such as its technical capabilities, development experience, and target application scenarios. Combined with the data service provider's historical development records, analyze the completion status of past projects, technical implementation results, and user feedback. Extract the data service provider's technical capability characteristics from the massive historical development records, and then obtain the data service provider's comprehensive technical capability characteristic value.

[0081] S2022: Evaluate the industry reputation of data service providers, correlate their industry performance with their technical capabilities, and judge their professionalism and reliability by analyzing their industry partnership record, customer reviews, and technical influence. Analyze the background of the data service provider's technical team, comparing the team's technical expertise with public data development requirements to determine their ability to complete development tasks, and calculate the match between the data service provider's industry reputation and the technical team's background.

[0082] S2023: Comprehensively evaluate the data service provider's comprehensive technical capability characteristics, industry reputation and technical team background matching to generate a capability score for the data service provider, and decide whether to grant it development permissions based on the score results.

[0083] Among them, the S2021 technical capability feature extraction and massive historical development record analysis expression:

[0084]

[0085] Where, T cap represents the comprehensive technical capability characteristic value of the data service provider; n represents the total number of massive historical development records; α i represents the weight coefficient of the i-th project, which is determined by the complexity, scale and influence of the project; represents the completion score of the i-th project, ranging from [0, 1]; represents the user satisfaction score of the i-th item, ranging from [0, 1]; Indicates the technical implementation effect score of the i-th project, ranging from [0, 1]; represents the completion score of the jth project, ranging from [0, 1]; represents the user satisfaction score of the jth item, ranging from [0, 1]; represents the technical implementation effect score of the jth project, ranging from [0, 1]; β represents the adjustment coefficient of the technical team size on technical capabilities; N dev It represents the total number of people in the technical team of the data service provider; σ represents the deviation value of the industry's average technical team size, which is used for normalization processing; the technical capability characteristic value of the data service provider is quantified by weighted calculation of the completion rate, user satisfaction and technical implementation effect of historical projects, combined with the adjustment factor of the technical team size.

[0086] S2022 represents the industry reputation and technical team background matching analysis expression:

[0087]

[0088] Where R rep represents the matching degree between the industry reputation of the data service provider and the background of the technical team; m represents the total number of cooperation records in the industry; γ k represents the weight coefficient of the kth cooperation record, which is determined by the influence of the partner and the scale of cooperation; represents the customer evaluation score in the k-th cooperation record, ranging from [0, 1]; represents the score of technical influence in the k-th collaboration record, ranging from [0, 1]; represents the score of the depth of cooperation in the k-th cooperation record, ranging from [0, 1]; δ represents the adjustment coefficient of the technical team background matching; p represents the total number of items that match the technical team background and development requirements; θ l represents the weight coefficient of the lth matching item, which is determined by the importance of technical expertise; Indicates the matching score between the technical expertise of the lth matching item and the development requirements, ranging from [0, 1]; The weight of the development requirement of the lth matching item is in the range of [0, 1]. The matching degree between the industry reputation of the data service provider and the technical team background is quantified by weighted calculation of customer evaluation, technical influence and depth of cooperation in the industry cooperation record, combined with the matching degree between the technical team background and development requirements.

[0089] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first conducts a preliminary analysis of the application submitted by the data service provider, extracts key information such as its technical capabilities, development experience, and target application scenarios; combines the historical development records of the data service provider, analyzes the completion status of its past projects, technical implementation effects, and user feedback, and extracts the technical capability characteristics of the data service provider from massive historical development records; secondly, the industry reputation of the data service provider is evaluated, and the industry performance of the data service provider is correlated with its technical capabilities. By analyzing its cooperation records, customer evaluations, and technical influence in the industry, the professionalism and reliability are judged; the background of the data service provider's technical team is analyzed, and the team's technical expertise is compared with public data development needs to obtain the ability to complete development tasks; finally, the analysis results of the technical capability characteristics, industry reputation, and technical team background are comprehensively evaluated to generate a capability score for the data service provider, and a decision is made based on the score result whether to grant it development permissions. The above solution initially analyzes application information to extract key information such as technical capabilities, development experience, and target application scenarios. Combined with historical development records, it constructs a technical capability model for the data service provider, extracting key technical capability indicators such as development efficiency, technical implementation results, and user satisfaction from massive historical data. The solution also assesses the data service provider's industry reputation and, in conjunction with its technical capabilities, conducts correlation analysis, analyzing textual data such as collaboration records, customer reviews, and technical influence, to quantify its professionalism and reliability. The solution also conducts an in-depth analysis of the technical team's background, comparing its technical expertise with public data development requirements and matching the team's technical expertise with the requirements of the development task to assess its ability to complete the development task. The analysis of the above technical capability characteristics, industry reputation, and technical team background is then comprehensively evaluated to generate a capability score for the data service provider, which in turn generates a final capability score. The score will serve as the core basis for determining whether development permissions are granted.

[0090] Example 5: Figure 6 As shown, based on Example 4, the process of generating the capability score of a data service provider provided by this embodiment of the present invention includes the following steps:

[0091] S20231: Verify the input comprehensive technical capability characteristic value, industry reputation, and technical team background matching. If any anomalies are found, the evaluation is terminated and an error message is returned. Based on preset rules, initial weights are assigned to the comprehensive technical capability characteristic value, industry reputation, and technical team background matching.

[0092] S20232: Calculate preliminary scores using a weighted formula, check the distribution of each score based on preset dynamic adjustment rules, and normalize the preliminary scores to the range of [0, 100];

[0093] S20233: Set a scoring threshold. If the normalized score is greater than or equal to the threshold, the data service provider is determined to have development capabilities and development permissions are granted; otherwise, it is determined that it does not have development capabilities and permissions are denied; the normalized score and judgment result are output as the basis for decision-making.

[0094] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first verifies the input comprehensive technical capability characteristic value, industry reputation and technical team background matching. If there is an anomaly, the evaluation is terminated and an error message is returned; according to the preset rules, initial weights are assigned to the comprehensive technical capability characteristic value, industry reputation and technical team background matching respectively; secondly, a preliminary score is calculated by a weighted formula, and according to the preset dynamic adjustment rules, the distribution of each score is checked and the preliminary score is normalized to the range of [0, 100]; finally, a score threshold is set. If the normalized score is greater than or equal to the threshold, the data service provider is judged to have development capabilities and development permissions are granted; otherwise, it is judged to have no development capabilities and permissions are denied; the normalized score and judgment result are output as the basis for decision-making. The above solution ensures the legitimacy and integrity of the input comprehensive technical capability characteristic value, industry reputation and technical team background matching, and avoids distortion of the evaluation results due to data anomalies; at the same time, the initial weight is assigned by the preset rules, providing a basis for weighted calculation, ensuring the scientificity and standardization of the evaluation process; the preliminary score is calculated by the weighted formula, combined with the dynamic adjustment rules, to ensure that the scoring results can reflect the true capabilities of the data service provider. Normalization processing unifies the scores to the range of [0, 100], which facilitates threshold determination and result comparison, and improves the standardization and operability of the evaluation results; by setting the scoring threshold and clarifying the judgment criteria, the objectivity and consistency of the evaluation results are ensured; and finally, the normalized scores and judgment results are output, providing a clear and reliable basis for decision-making, thereby improving decision-making efficiency and accuracy.

[0095] In summary, this embodiment achieves a comprehensive and accurate assessment of the development capabilities of data service providers, ensures the scientificity, standardization and operability of the assessment process, and provides reliable support for decision-making.

[0096] Example 6: Figure 7 As shown, based on Example 5, the process of allocating initial weights according to preset rules provided in this embodiment of the present invention includes the following steps:

[0097] S202331: Collect the data service provider's historical development records, industry reputation, and technical team's professional background to obtain the corresponding multiple comprehensive technical capability characteristic values, industry reputation, and technical team background matching; and conduct development permission impact analysis to obtain multiple development permission impacts;

[0098] S202332: For different development permissions, weights are assigned to development permissions based on the influence of multiple development permissions. Initial weights are obtained for historical development records, industry reputation, and the professional background of the technical team.

[0099] S202333: Based on the initial weights, a development permission database with preset rules is constructed to store the weight allocation rules; dynamic adjustments are made based on real-time feedback from the scoring results.

[0100] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first collects the historical development records, industry reputation and professional background of the data service provider's technical team to obtain the corresponding multiple comprehensive technical capability characteristic values, industry reputation and technical team background matching; and performs development authority impact analysis to obtain multiple development authority impacts; secondly, for different development permissions, with reference to multiple development authority impacts, weights are assigned to development permissions, and multiple initial weights are obtained for historical development records, industry reputation and technical team professional background; finally, based on the initial weights, a development permission database with preset rules is constructed to store weight assignment rules; and dynamic adjustments are made based on real-time feedback from the scoring results. The above solution realizes the initial weight assignment of development permissions by combining the comprehensive technical capability characteristic values, industry reputation and technical team background matching, and combining the development authority impact analysis. Specifically, first, by collecting the historical development records, industry reputation and technical team professional background of the data service provider, multiple comprehensive technical capability characteristic values, industry reputation and technical team background matching are obtained, and development authority impact analysis is performed to obtain multiple development authority impacts. Next, for different development permissions, weights are assigned based on multiple development permission influences, yielding initial weights based on historical development records, industry reputation, and the technical team's professional background. Finally, based on these initial weights, a pre-defined development permission database is constructed to store these weightings and dynamically adjust them based on real-time feedback from the scoring results. This enables precise and dynamic management of development permissions, ensuring the rationality and adaptability of their allocation, thereby improving overall development efficiency and quality.

[0101] Example 7: Figure 8 As shown, based on Example 6, the process of obtaining the influence of multiple development permissions provided by this embodiment of the present invention includes the following steps:

[0102] S2023331: Based on the data service provider's historical development records, industry reputation, and technical team's professional background, extract multiple comprehensive technical capability feature values, industry reputation, and technical team background matching degrees; associate the comprehensive technical capability feature values, industry reputation, and technical team background matching degrees by data service provider to form an initial data set;

[0103] S2023332: Each data service provider is a node in the graph, and node attributes include technical capability characteristics, industry reputation score, and team background matching. Each project is a node in the graph, and node attributes include project scale, technical complexity, and delivery time.

[0104] The edge between the service provider and the project represents the project in which the service provider is involved, and the weight of the edge is determined by the service provider's performance in the project. The edge between the service provider and the industry reputation represents the service provider's industry reputation, and the weight of the edge is determined by the reputation score. The edge between the service provider and the technical team represents the background of the service provider's technical team, and the weight of the edge is determined by the team background match.

[0105] S2023333: Establish a correlation between the data service provider and the project through the data service provider's performance in the project; establish a correlation between the data service provider and the industry's reputation through the data service provider's industry reputation score; establish a correlation between the data service provider and the team's background through the background matching of the data service provider's technical team, and determine the impact of development permissions based on the correlation.

[0106] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first extracts multiple comprehensive technical capability feature values, industry reputation and technical team background matching based on the historical development records, industry reputation and professional background of the data service provider; associates the comprehensive technical capability feature values, industry reputation and technical team background matching according to the data service provider to form an initial data set; secondly, each data service provider is regarded as a node in the graph, and the node attributes include technical capability feature values, industry reputation scores and team background matching; each project is regarded as a node in the graph, and the node attributes include project scale, technical complexity and delivery time, etc.; the edge between the service provider and the project: represents For projects in which a service provider participates, the weight of the edge is determined by the service provider's performance in the project; the edge between the service provider and its industry reputation represents the service provider's industry reputation, and the weight of the edge is determined by the reputation score; the edge between the service provider and its technical team represents the service provider's technical team background, and the weight of the edge is determined by the matching degree of the team background; finally, the relationship between the data service provider and the project is established based on the data service provider's performance in the project; the relationship between the data service provider and its industry reputation is established based on the data service provider's industry reputation score; the relationship between the data service provider and its team background is established based on the matching degree of the data service provider's technical team background, and the influence of development permissions is determined based on the relationship. The above scheme constructs a multi-dimensional development authority impact assessment system based on the data service provider's historical development record, industry reputation and technical team professional background; by extracting the comprehensive technical capability characteristic value, industry reputation score and technical team background matching, the relationship between the data service provider, project, industry reputation and technical team background is systematically modeled to form a dynamic and quantifiable development authority impact assessment framework; by extracting the historical development record, industry reputation and technical team background of the data service provider, an initial data set is formed to ensure the comprehensiveness and accuracy of the basic data for the assessment; the data service provider, project, industry reputation and technical team background are used as nodes in the graph, and the relationship between them is represented by edge weights; the edge weight between the service provider and the project is determined by the service provider's performance in the project, the edge weight between the service provider and the industry reputation is determined by the reputation score, and the edge weight between the service provider and the technical team is determined by the team background matching; the multi-dimensional association relationship modeling makes the assessment of development authority impact not only based on single-dimensional data, but also comprehensively considers the interaction between technical capabilities, industry reputation and team background.

[0107] In summary, in this embodiment, through the modeling method, the evaluation of the impact of development authority can dynamically reflect the actual performance of the data service provider in different projects, changes in industry reputation, and the matching of the technical team background; it can not only provide a scientific basis for the allocation of development authority, but also dynamically adjust the evaluation model through real-time data feedback to ensure that it adapts to the needs of industry changes and technological development; through multi-dimensional data association and dynamic modeling, the accurate quantification of the impact of development authority is achieved, providing efficient and reliable technical support for the capability evaluation and project matching of data service providers.

[0108] Example 8: Figure 9 As shown, based on Example 1, the process of verifying the public data products developed by the data service provider and corresponding to the needs provided by the embodiment of the present invention includes the following steps:

[0109] S301: Perform integrity checks on public data products submitted by data service providers to ensure that they contain all required data fields and content. By comparing the structure of the requirements document with the data product, verify whether the data product covers all specified data dimensions and check for missing or redundant data.

[0110] S302: During the verification process, the entire life cycle of the data product is supervised through blockchain technology; every key node from development to release of the data product is recorded, including data source, processing process, verification results and release status;

[0111] S303: Feedback the verification results to the data service provider, and optimize the data product based on the verification results.

[0112] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first performs an integrity check on the public data product submitted by the data service provider to ensure that the data product contains all data fields and content related to the requirements; by comparing the structure of the requirements document with the data product, it verifies whether the data product covers all specified data dimensions and checks for data missing or redundancy; secondly, during the verification process, the entire life cycle of the data product is supervised through blockchain technology; every key node from development to release of the data product, including data source, processing process, verification results and release status; finally, the verification results are fed back to the data service provider, and the data product is optimized based on the verification results. The above solution forms a systematic, closed-loop public data product verification process. Through integrity checks, blockchain full life cycle supervision, and verification result feedback and optimization, it ensures that the public data products developed by the data service provider meet the expected standards in terms of technology, compliance, and usability. First, the integrity check ensures that the data product fully matches the requirements in the basic framework by comparing the data product structure with the requirements document, avoiding data missing or redundancy, and laying the foundation for data integrity in the verification process. Secondly, the introduction of blockchain technology oversees the entire lifecycle of data products, recording key milestones from data source and processing to verification results and release status. This ensures high transparency and traceability of data products, effectively preventing data tampering and information asymmetry. Finally, a feedback and optimization mechanism for verification results promptly provides data service providers with feedback on any issues discovered during the verification process, driving improvements and optimization of data products and ensuring they meet practicality and compliance requirements before release.

[0113] In summary, this implementation ensures the accuracy of the data infrastructure through integrity checks, enhances the transparency and traceability of data products through blockchain oversight, and improves the quality of data products through feedback and optimization mechanisms. This technically enables closed-loop management and continuous optimization of the entire data product verification process. This not only improves the quality and credibility of public data products, but also enhances the efficiency and reliability of data operations management, providing a solid technical foundation for the development and application of public data resources.

[0114] Example 9: Figure 10 As shown, based on Examples 1 to 8, the data operation management system provided by the embodiment of the present invention includes:

[0115] The data processing module is responsible for assigning labels to several data sources according to their sources, obtaining public data from several data sources, and classifying public data into structured public data and unstructured public data. It also classifies public data according to its sensitivity, obtaining labeled and classified public data. Public data refers to data resources with public attributes that are controlled, managed, and provided by the government or public institutions. They come from government affairs activities, public services, social governance, and other fields of government departments, covering multiple aspects such as the economy, society, people's livelihood, and the environment.

[0116] The demand allocation module is responsible for reviewing applications from data service providers who need to obtain public data, authenticating the data service providers after review, and obtaining public data development permissions that meet the review requirements; and allocating public data requirements to data service providers for development;

[0117] The publishing and display module is responsible for verifying the public data products developed by data service providers that correspond to the needs, and publishing and displaying the verified public data products in the portal; and supervising the entire life cycle of public data through blockchain.

[0118] The working principle and beneficial effects of the above technical solution are as follows: the data processing module of this embodiment assigns labels to several data sources according to their sources, obtains public data from several data sources, and divides the public data into structured public data and unstructured public data; the public data is graded according to its sensitivity to obtain public data with labels, divisions and classifications; wherein, public data refers to data resources with public attributes that are controlled, managed and provided by the government or public institutions, and are derived from government affairs activities, public services, social governance and other fields of government departments, covering multiple aspects such as economy, society, people's livelihood, and environment; the demand allocation module reviews the application of data service providers who need to obtain public data, and after the review, authenticates the data service providers to obtain public data development permissions that meet the review; allocates the demand for public data to data service providers for development; the publishing and display module verifies the public data products developed by data service providers that correspond to the demand, and publishes and displays the verified public data products in the portal; and supervises the entire life cycle of public data through blockchain. The data processing module of this solution provides a clear foundation for public data management and use by labeling, classifying structured and unstructured data, and grading its sensitivity. This not only enhances the identifiability and operability of public data but also provides a basis for security grading and differentiated management of public data, ensuring that public data meets compliance and security requirements during sharing and development. Secondly, the demand allocation module reviews and authenticates applications from data service providers, ensuring that public data development permissions are granted only to qualified data service providers. This not only effectively controls the scope of public data use and prevents its misuse, but also precisely matches development tasks to qualified service providers through demand allocation, thereby improving the efficiency and quality of public data development. Finally, the publishing and display module verifies public data products developed by data service providers and publishes them on the portal, ensuring their reliability and availability. Furthermore, blockchain technology oversees the entire lifecycle of public data, ensuring transparent management and immutable records, and enhancing the trust and credibility of public data operations.

[0119] In summary, this embodiment has built a complete closed loop from public data acquisition, processing to development, release and supervision, which not only realizes the efficient use and safe sharing of public data, but also provides a standardized development environment for data service providers and reliable data products for the public; it provides strong technical support for the value mining and social application of public data, and promotes the openness and innovation of public data resources.

[0120] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention's equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A data operation management method, characterized in that: The following steps are involved: Assign labels to several data sources according to their sources, obtain public data from several data sources, and classify the public data into structured public data and unstructured public data; classify the public data according to its sensitivity, and obtain labeled and classified public data; Review applications from data service providers who need to obtain public data, authenticate the data service providers after review, and obtain public data development permissions that meet the review requirements; allocate public data requirements to data service providers for development; Verify the public data products developed by data service providers that correspond to the needs, and publish and display the verified public data products in the portal; supervise the entire life cycle of public data through blockchain.

2. The data operation management method according to claim 1, wherein: The process of obtaining labeled and classified public data includes the following steps: After obtaining public data, the data is divided into structured data and unstructured data according to the existence form of the public data. Public data with fields and formats are classified as structured data, and public data without fixed formats and structures are classified as unstructured data. After completing the division of structured data and unstructured data, analyze the content, usage, and potential impact to determine sensitivity and classify structured data and unstructured data; The public data that have been labeled and graded are integrated into a resource library, and each public data has source label, structure type and sensitivity level information.

3. The data operation management method according to claim 2, wherein: in, Structured data is in the form of fields and formats in tables, databases, and spreadsheets; unstructured data includes text files, images, audio, video, and social media content, which do not have a fixed format or structure.

4. The data operation management method according to claim 1, wherein: The process of allocating public data requirements to data service providers for development includes the following steps: Based on the applications submitted by data service providers, we analyze the matching degree between their development requirements and public data and screen the data service providers; The data service providers that have passed the screening will be subject to qualification review. Based on the service provider's historical development record, industry reputation, and the professional background of the technical team, a comprehensive assessment will be made as to whether they have the ability to develop public data. Service providers that pass the review will be granted corresponding development permissions. Based on the development authority of the data service provider, specific public data requirements will be allocated to the development platform of the data service provider. For highly sensitive public data, encrypted transmission and access control mechanisms will be adopted.

5. The data operation management method according to claim 4, wherein: The process of comprehensively judging whether an enterprise has the ability to develop public data includes the following steps: Conduct a preliminary analysis of the application submitted by the data service provider to extract key information about its technical capabilities, development experience, and target application scenarios. Combined with the data service provider's historical development records, analyze the completion status of past projects, technical implementation results, and user feedback, and extract the data service provider's technical capability characteristics from the massive historical development records. Evaluate the industry reputation of the data service provider and correlate its industry performance with its technical capabilities. Analyze its collaboration record, customer reviews, and technical influence within the industry to determine its professionalism and reliability. Analyze the background of the data service provider's technical team and compare the team's technical expertise with public data development requirements to determine its ability to complete development tasks. The analysis results of technical capability characteristics, industry reputation and technical team background are comprehensively evaluated to generate a capability score for the data service provider, and whether to grant it development permissions is decided based on the score results.

6. The data operation management method according to claim 5, wherein: The process of generating a data service provider's capability score includes the following steps: Verify the input comprehensive technical capability characteristic value, industry reputation and technical team background matching. If any anomaly is found, the evaluation will be terminated and an error message will be returned. According to the preset rules, initial weights are assigned to the comprehensive technical capability characteristic value, industry reputation and technical team background matching respectively. Calculate the preliminary score using a weighted formula, check the distribution of each score based on the preset dynamic adjustment rules, and normalize the preliminary score to the range of [0, 100]; Set a scoring threshold. If the normalized score is greater than or equal to the threshold, the data service provider is deemed to have development capabilities and is granted development permissions. Otherwise, it is determined that it does not have the development capability and the permission is denied; the normalized score and judgment result are output as the basis for decision-making.

7. The data operation management method according to claim 6, wherein: The process of assigning initial weights according to preset rules includes the following steps: Collect the data service provider's historical development records, industry reputation, and technical team's professional background to obtain the corresponding multiple comprehensive technical capability feature values, industry reputation, and technical team background matching; And conduct development permission impact analysis to obtain the impact of multiple development permissions; For different development permissions, the weights of development permissions are assigned based on the influence of multiple development permissions, and multiple initial weights are obtained for historical development records, industry reputation, and professional background of the technical team; Based on the initial weights, a development permission database with preset rules is constructed to store the weight allocation rules; dynamic adjustments are made based on real-time feedback from the scoring results.

8. The data operation management method according to claim 7, wherein: The process of obtaining the influence of multiple development permissions includes the following steps: Based on the data service provider's historical development records, industry reputation, and technical team's professional background, we extract multiple comprehensive technical capability feature values, industry reputation, and technical team background matching degrees. We then correlate these comprehensive technical capability feature values, industry reputation, and technical team background matching degrees by data service provider to form an initial data set. Each data service provider is a node in the graph, and its node attributes include technical capability characteristics, industry reputation score, and team background matching. Each project is a node in the graph, and its node attributes include project scale, technical complexity, and delivery time. Through the performance of the data service provider in the project, the relationship between the data service provider and the project is established; through the industry reputation score of the data service provider, the relationship between the data service provider and the industry reputation is established; through the matching degree of the data service provider's technical team background, the relationship between the data service provider and the team background is established, and the impact of development permissions is determined based on the relationship.

9. The data operation management method according to claim 1, wherein: The process of verifying the public data products developed by data service providers that correspond to the requirements includes the following steps: Conduct integrity checks on public data products submitted by data service providers to ensure that they contain all required data fields and content. By comparing the structure of the requirements document with the data product, verify whether the data product covers all specified data dimensions and check for missing or redundant data. During the verification process, blockchain technology is used to monitor the entire life cycle of data products, recording every key node from development to release, including data sources, processing, verification results, and release status. Feedback the verification results to the data service provider, and optimize the data products based on the verification results.

10. A data operation management system, characterized in that: Include: The data processing module is responsible for assigning labels to several data sources according to their sources, obtaining public data from several data sources, and dividing the public data into structured public data and unstructured public data; Classify public data according to its sensitivity to obtain labeled and classified public data; The demand allocation module is responsible for reviewing applications from data service providers who need to obtain public data, authenticating the data service providers after review, and obtaining public data development permissions that meet the review requirements; and allocating public data requirements to data service providers for development; The publishing and display module is responsible for verifying the public data products developed by data service providers that correspond to the needs, and publishing and displaying the verified public data products in the portal; and supervising the entire life cycle of public data through blockchain.

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