360 results about "Data sharing" patented technology

The invention discloses a verifiable medical data query method based on a DAG block chain architecture, and belongs to the technical field of block chains and medical information management. According to the method, medical events such as diagnosis and treatment records and image reports are modeled into DAG nodes, an on-chain topology with time sequence and causal association is constructed by encrypting a hash pointer, dynamic indexing and multi-keyword verifiable query are achieved in combination with an off-chain authentication data structure, a verification object containing a matching node set and a verification path is received, and the verification object is subjected to dynamic indexing and multi-keyword verifiable query. The authenticity, integrity and timeliness verification of the result is independently completed based on the authentication root stored on the chain without depending on a third party. According to the method, through an on-chain and off-chain collaborative storage and incremental authentication updating mechanism, on the premise of ensuring privacy and tamper-proofing of medical data, query efficiency, verification performance and expandability under high concurrency are remarkably improved, communication and resource expenses are lower, and the method is suitable for large-scale popularization and application. The method is suitable for application scenes such as cross-institution medical data sharing, remote diagnosis and treatment and compliance auditing.

The invention belongs to the crossing field of artificial intelligence and material informatics, discloses a multi-layer material knowledge graph construction method and system based on a large model, and solves the problems of low utilization rate of multi-modal information, flat knowledge representation, uncontrollable quality and insufficient entity alignment precision in the prior art. The method comprises the following steps: analyzing material science and technology literatures, extracting multi-modal information of texts, tables and images, and preprocessing the multi-modal information into structured data; constructing a three-layer semantic framework of a concept term layer, a material entity layer and a material data layer; extracting knowledge by a large model layer by layer to generate a triple, and performing multi-dimensional quality evaluation and dynamic threshold filtering; entity fusion is realized by adopting hybrid alignment of semantic embedding and literal similarity and large model discrimination, and an atlas is maintained by combining incremental updating and version management. According to the method, knowledge integrity and accuracy are improved, entity heterogeneous scenes in the material field are adapted, whole-process automation is achieved, and high-quality knowledge support is provided for material research and development and data sharing.

The invention relates to the technical field of computers, in particular to a data sharing management system and method for a database, and the system comprises an identity verification module, a permission adaptation and grading approval module, a risk control module and an iteration module, and the method correspondingly executes the functions of the modules. The identity verification guarantees the legality of an access subject through format verification and multi-dimensional hierarchical authentication, and the intensity of the hierarchical authentication is dynamically adjusted along with the data sensitivity; authority management and control execute differentiation logic according to public, internal and confidential three levels, and fine authorization is achieved; the risk control module monitors abnormal operation in real time and performs grading processing; all operations are recorded in a block chain audit log, and the system realizes dynamic iteration through regular verification and historical data optimization. The data sharing security and cooperation efficiency are considered, the risk controllability and the system adaptability are improved, and the multi-scene data sharing requirements such as enterprise cross-department and external cooperation are met.

The invention provides a clinical test data security sharing method and device based on a block chain. The method is applied to the technical field of data processing, and comprises the following steps: extracting feature dimensions corresponding to various types of data, and calculating corresponding data sensitivity coefficients; determining a data sensitivity level of the corresponding data category; extracting corresponding associated metadata; selecting a corresponding encryption algorithm to encrypt the data, and generating corresponding encrypted data and a data abstract; uploading the associated metadata, the encrypted data and the data abstract to a block chain node, constructing a clinical test data sharing account book, and recording a timestamp and a node signature of data operation; extracting identity authentication information and historical access records of visitors, and calculating access credibility; judging whether the visitor is allowed to acquire the decryption key or not; after the visitor obtains the encrypted data, the integrity in the data transmission process is verified based on the non-tampering property of the block chain. Therefore, the security of clinical test data sharing based on the block chain is improved.

The invention discloses a homomorphic encryption-based cross-industry health insurance data sharing and privacy protection method, and relates to the technical field of health insurance data security, and the method specifically comprises the steps: standardizing medical and insurance industry core data, quantifying key indexes such as a disease clinical risk value and an occupational basic risk coefficient, achieving the format unification of cross-industry data, and achieving the privacy protection of the cross-industry data; further generating ownership, risk and business labels, carrying out encryption processing on data through homomorphic encryption on the risk labels based on three scenes of data sensitivity and business influence grading, business label binding pricing, underwriting and claim settlement prediction, adding an integrity check code to high-risk data, screening ciphertexts based on the labels, and then executing fusion calculation; the comprehensive risk adjustment coefficient ciphertext is generated, the data integrity is verified, the comprehensive risk adjustment coefficient is obtained after collaborative decryption, the comprehensive risk adjustment coefficient is applied to premium pricing, underwriting conclusion generation and claim risk pre-judgment, and the scientificity and accuracy of health insurance pricing and underwriting decision making are improved.

The invention discloses a cross-industry data sharing method and system using a trusted data space, and relates to the technical field of data sharing, and the method comprises the steps: obtaining a cross-industry data dimension relation; obtaining a sharing request, and carrying out dimension migration analysis on the sharing request to obtain a dimension migration path set; according to the dimension migration path set, adaptive reorganization operation is executed on the to-be-shared data, and reorganized shared data is obtained; according to the cross-industry data dimension relationship and the dimension migration path set, performing cross-industry confidence evaluation on the recombined shared data to generate a shared decision result; and performing data sharing on the recombined shared data through a secure channel of the trusted data space. The technical problems that existing cross-industry data sharing is difficult, and data resources are wasted are solved.

The invention relates to the technical field of medical information and block chain crossing, in particular to a medical image co-processing system and method based on a block chain value network, and the system comprises a block chain network, a privacy calculation gateway, an intelligent contract module, a hybrid storage module and a communication module. The intelligent contract module is provided with a collaborative annotation sub-module, a verifiable federated learning sub-module and a dynamic value distribution sub-module; the method comprises the steps of data preprocessing and encryption uploading, collaborative labeling and quality verification, verifiable federated learning model training, dynamic value distribution, consensus evidence storage and supervision auditing. Medical data islands are broken through by means of the block chain network, data availability and invisibility are achieved in combination with the privacy computing gateway multi-encryption technology, the contradiction between data sharing and privacy security is solved, accurate contribution and return matching is achieved through the multi-dimensional contribution degree evaluation model and the intelligent contract, and the accuracy of data sharing is improved. The traceability and the compliance are ensured by full-process operation logs and data uplink evidence storage.

The invention discloses an intelligent medical data security sharing system based on a block chain, and belongs to the technical field of medical data sharing, the system comprises a data acquisition and preprocessing module, a block chain core module, a data sharing and interaction module and an operation and maintenance management module, the data acquisition and preprocessing module is used for integrating multi-source heterogeneous medical data, the block chain core module is used for improving throughput through a slave multi-chain architecture and promoting participation of medical institutions in combination with a dynamic incentive mechanism, and the data sharing and interaction module is used for hierarchical encryption and dynamic authority balance security and efficiency and improving concurrency ability in combination with a master-slave chain architecture. And the operation and maintenance management module is used for alliance governance, real-time monitoring, security audit and data full-life-cycle management. On the basis of realizing medical data sharing, privacy protection and sharing efficiency can be improved, and clinical decision can be supported.

The invention relates to the technical field of block chains, in particular to a drug cross-region transfer tracing and multi-subject data sharing system based on a block chain. According to the temperature data distribution of each monitoring point at different moments, the temperature sudden change factor of each monitoring point at each moment is obtained; according to the temperature data distribution of different monitoring points at different moments and the temperature sudden change factors, in combination with the position distribution of different monitoring points, obtaining the chemical impact degree of transportation at each moment; according to the change trend of the vibration data at different moments and the vehicle speed data, the physical impact degree of transportation at each moment is obtained; according to the transportation chemical impact degree and the transportation physical impact degree at each moment, obtaining the transportation environment abnormity at each moment; and writing the data into the block chain in real time, and carrying out transfer tracing and multi-subject data sharing on the medicines. According to the method, the transportation environment abnormity at each moment is accurately obtained, so that the accuracy of block chain tracing and data sharing is improved.

The invention relates to the technical field of international marine scientific investigation collaborative technology and mutual identification, and discloses an international marine observation data fusion and achievement mutual identification system suitable for joint scientific investigation. Comprising a multi-source data standardization access module, a polar region adaptive intelligent fusion module, an international achievement mutual recognition standard and verification module, a hierarchical sharing and mutual recognition process management module, a collaborative iteration and operation and maintenance management module, a block chain full-process traceability system and an international joint collaborative operation and maintenance mechanism. According to the system, the problem of international data heterogeneity is solved through multi-source data standardization preprocessing, accurate data fusion under polar region / open sea complex working conditions is realized by utilizing an intelligent fusion technology, a mutual recognition system of bidirectional verification is established, and the traceability of the whole process is ensured by adopting a block chain. The system supports hierarchical sharing and dynamic iterative optimization, is cooperatively operated and maintained by two international parties, guarantees long-term adaptation to standard updating and equipment iteration of the two parties, and effectively improves the joint scientific investigation data sharing efficiency and the result mutual recognition credibility.

The invention provides a medical data sharing interface based on a standardized API and a low-code construction method. The method comprises the steps that a set of standardized medical core data models is predefined; a unified data sharing service API layer is constructed, an adapter used for being in butt joint with a heterogeneous medical data source and converting the heterogeneous medical data source into data matched with a predefined model format is configured, and an API interface is generated based on the predefined model; a component library is preset through a visual interface configuration platform, each component in the component library is bound with a field of a predefined model, the components are arranged and / or combined in a dragging mode, and a data binding relation between the components and an API interface is configured; and analyzing and generating a structured interface description file according to the information of visual interface construction and configuration, dynamically loading the interface description file through an engine when a client runs, calling an API (Application Program Interface), and rendering a final user interface. According to the scheme, the development cycle can be shortened, the ability threshold of developers can be reduced, and good expandability is achieved.

The invention relates to the technical field of computers, discloses a data sharing method and system for patients suffering from metabolic acidosis, and aims to solve the problem of out-of-control safety caused by extensive authority, bare transmission and traceless behaviors in cross-institution medical data circulation. A dynamic authority strategy based on roles and scenes is constructed by extracting and standardizing patient diagnosis and treatment data from a hospital system; end-to-end encrypted transmission is realized through bidirectional authentication and a temporary session key; establishing a three-layer block chain type audit log tracking access, a secret key and a data flow direction; dynamic desensitization, quality verification, cache acceleration and intelligent contract extension mechanisms are integrated, and a visual authority topology monitoring and credit scoring system is supplemented. According to the technical scheme, data field-level accurate authorization, encryption and anti-theft in the whole transmission process, traceability in the whole operation period and use compliance self-feedback are achieved, and the scientific research value of clinical data is released to the maximum extent while the privacy safety of a patient is effectively guaranteed.

The invention discloses an interpretable differential privacy parameter adaptive method for a generative medical record, and relates to the technical field of medical data privacy protection and artificial intelligence. The method comprises the following steps: acquiring an original medical record data set, and identifying a field containing sensitive information; constructing a multi-dimensional evaluation model, and respectively calculating the sensitivity score of each field and the utility score of the downstream task; dynamically allocating differential privacy budget parameters for each field by using a constraint optimization algorithm based on a game relationship between sensitivity and utility; in the training process of the generative model, corresponding noise is injected into a gradient or an input layer according to the distributed parameters; and finally, generating a synthetic medical record and outputting an interpretability report of privacy parameter distribution. By automatically adjusting the DP parameters, the data features of the low-sensitivity and high-value fields are reserved while the high-sensitivity fields are ensured to obtain strong privacy protection, the problem that privacy protection and data availability are difficult to consider in medical data sharing is effectively solved, and a transparent auditing basis is provided.

The invention provides a clinical data management system, a clinical data privacy protection method, equipment and a medium. Obtaining an identity identifier corresponding to the medical institution identity information of the requester and a patient anonymous identifier associated with the medical record text data; performing medical semantic analysis on clinical contents in the medical record text data, identifying a plurality of sensitive entities containing diagnosis and treatment features, physiological indexes and personal identifiers of patients, associating medical contexts of the sensitive entities, and generating a specified replacement seed value for each sensitive entity based on anonymous identifiers of the patients; and for each sensitive entity, determining corresponding replacement content from a preset desensitization rule base according to the medical context of the sensitive entity and the replacement seed value. And finally, replacing each sensitive entity with the corresponding replacement content, and generating a desensitized clinical text associated with the anonymous identifier of the patient. According to the scheme, context-aware privacy protection can be realized in a clinical data sharing environment.

The invention provides a river trajectory data protection method based on differential privacy, and belongs to the field of environmental data privacy protection. According to the method, river flow velocity and flow direction data are discretized into a two-dimensional grid, spatial-temporal characteristics are extracted by using a graph convolutional network (GCN), and a Markov transfer matrix is established; and according to the grid access frequency and the spatial density, privacy budget is adaptively allocated through a dual attenuation factor model, and differential privacy protection is realized. In the trajectory generation stage, dynamic privacy budget is combined, noise is injected into direction and time features by adopting an index mechanism and a Laplace mechanism, and a synthetic trajectory conforming to physical constraints is generated; and finally, evaluating and optimizing the track quality by using Savitzky-Golay filtering and multiple indexes (such as Frechet distance, access frequency error and KL divergence). According to the method, the privacy leakage risk is effectively reduced while the space-time continuity of the trajectory is kept, the data privacy and availability are considered, and the method is suitable for hydrological monitoring, ecological analysis and environmental data sharing.

The invention belongs to the technical field of data security, and particularly relates to a community data sharing and exchanging security control method based on a block chain, which realizes fine-grained and dynamic access control by performing refined permission division on user characteristics and data attributes and constructing a verifiable attribute permission mapping relationship in an intelligent contract. The slave logic layer prevents unauthorized access vulnerabilities; a mode of combining a fully homomorphic encryption algorithm and a lightweight homomorphic encryption algorithm is adopted, direct operation of data in an encryption state is realized, a permission verification mechanism without data content leakage is constructed in combination with zero-knowledge proof, and dual protection of'calculation without decryption and verification without leakage 'is formed. According to the method, the data leakage risk caused by smart contract code vulnerabilities is fundamentally immunized, an extensive permission allocation mode is broken through by an attribute-based permission management method, refined permission division can be performed according to actual attributes of users and data, permission abuse and unauthorized access are effectively avoided, and the normalization and security of data access are greatly improved.

The invention relates to the technical field of medical information sharing, and discloses a medical information sharing application method and system, and the system comprises a medical information collection module, a data preprocessing module, a security encryption module, a sharing strategy management module, a path optimization module, a monitoring auditing module, a data synchronization module, and a feedback optimization module. When medical information sharing is carried out, standardized medical data are encrypted and anonymized based on privacy protection requirements, and safe medical data are generated in real time by adopting homomorphic encryption and differential privacy technologies, so that whether the privacy disclosure problem occurs in the transmission process of the shared data can be dynamically verified; according to the method, the data is protected in time when being accessed and tampered in an unauthorized mode, the privacy leakage risk of a patient is reduced, a sharing strategy is dynamically matched according to user roles and permission setting information, permission control is automatically executed in combination with an attribute-based encryption technology and an intelligent contract, and the accuracy and controllability of data sharing are guaranteed.

The invention provides a federated learning and privacy calculation-based cross-border earthquake risk assessment method, which solves the fundamental contradiction between data sovereignty and privacy security in cross-border data sharing by constructing a federated learning architecture fusing hierarchical desensitization and hybrid encryption. Through the multi-source data cooperative training and CNN-LSTM mixed disaster chain model, the problem that the assessment precision is insufficient due to the fact that a single country model cannot describe a complex cross-border disaster chain is solved; finally, a cross-border disaster scene is constructed, and the defect that a static evaluation tool is disjointed with an actual combat is overcome through a multi-agent dynamic policy simulation system; according to the method, the security collaboration under the condition that the data is not out of the scene is realized, the multi-country collaboration participation rate is improved by 60%, the risk assessment accuracy rate is improved to 92% or above, the policy assessment period is shortened from several months to several hours, a quantifiable scientific basis is provided for cross-border emergency decision making, and the joint prevention and joint control capability of regional earthquake disasters is effectively improved.

The application relates to the technical field of information transmission and discloses an At-211 separation process data sharing and collaborative analysis method and system based on a cloud platform. The method comprises the following steps: acquiring multi-source data of an At-211 separation process in real time, analyzing the correlation degree of the multi-source data and the At-211 separation, and obtaining separation correlation characteristic values representing the importance of various types of data for the separation; the separation correlation characteristic values are generated to accurately reflect the importance of the At-211 separation data, and a communication priority coefficient is generated through collaborative calculation combined with network state data, so that the emergency degree of data transmission can be divided, bandwidth disorder competition can be avoided, data differentiation uploading is realized through dynamic encapsulation configuration, a transmission evaluation index is generated combined with a transient transmission disturbance coefficient, a common collaborative priority coefficient is generated by fusing multiple parameters, transmission deviation is corrected, key data high-speed stable transmission is guaranteed, and the real-time performance and accuracy of cloud platform data sharing and collaborative analysis are improved.

This invention relates to the field of data analysis technology, specifically to a cloud-based tumor detection data analysis and sharing system. The invention includes a cloud service platform and multiple local terminals. The local terminals communicate with the cloud service platform via a network and are deployed in various medical institutions. They digitize tumor detection samples to generate raw medical data and extract metadata. The cloud service platform includes a data receiving module for receiving raw data and metadata; a template management module for building and maintaining a feature template library, including a two-stream ensemble classifier; a data calibration module for calling standardized parameter sets from metadata and generating standardized data through a reversible neural network; a data analysis module for analyzing the standardized data; and a data sharing module for responding to requests to share data. The system solves the problem of heterogeneity in multi-center data, improves the model's generalization ability and robustness, and achieves efficient data sharing and accurate analysis.

The application belongs to the technical field of data processing and sharing, and particularly relates to a job worker safety portrait data sharing method and system based on a blockchain technology, wherein safety behavior data of a job worker is acquired, a weighted scoring card model is trained, a safety score distribution is obtained, a dynamic safety portrait is constructed, verification is performed in combination with zero-knowledge proof and a polynomial commitment, and a digital identity certificate is generated; an improved blockchain network is used to construct associated data chains, a chain feature map is generated in combination with IPFS distributed storage, a cross-chain consensus mechanism and a smart contract are fused, a multi-node weight distribution mechanism is used to locate a high-risk job key area and analyze a behavior abnormality mode, and a risk evolution trend is output; a distributed random forest model is used to quantitatively score a comprehensive safety, a risk level is identified and a visual atlas is generated, and high-risk personnel are labeled, and meanwhile, data sharing is performed. Thus, the problems of missing key features, misjudging risk areas and incomplete portraits in the prior art are solved.

The invention provides a civil aviation data processing system and method and electronic equipment, and the system comprises a data collection module which is used for obtaining various civil aviation operation data; the flight planning module is used for determining a flight plan based on the real-time operation data; the simulation operation module is used for calculating operation index data according to the historical operation data and the flight plan; the analysis module is used for generating an operation index increment corresponding to the operation index data and calculating a total state increment based on the operation index increment; and the feedback optimization module is used for controlling the analysis module to update the total state increment based on the operation index increment when the total state increment does not meet the preset threshold range, so that the updated total state increment meets the preset threshold range. According to the method, data fusion and linkage processing in multiple business fields are realized, information islands are eliminated, cross-department data sharing and business collaboration are realized, the total state increment can be automatically iteratively updated, and the timeliness and accuracy of civil aviation data processing are improved.

The invention provides a method for realizing objection processing in a data sharing process, belongs to the technical field of web application, and aims at summarizing and reporting various objection encountered in the data sharing process through an objection proposing function, and realizing a message prompting function by connecting a short message platform. And through the objection management module, objection overall management of submission is realized. The method is mainly used for providing objection proposing, objection list and objection examination functions for an objection proposing party so that the objection proposing party can propose objection and check objection aiming at problem resources, problem applications, problem directory peers and the like of the department and can examine results after problems are solved. An objection acceptance function and an objection distribution function are provided for a platform management party, so that the platform management party analyzes the objection situation and decides whether processing is needed or not and who processes the objection; and objection checking and objection list functions are provided for the objection receiver, so that the objection receiver can check and solve the objection situation of the department.

The application relates to the technical field of government affair shared data encryption, and discloses a self-adaptive government affair shared data shape-preserving encryption method and system.The method comprises the following steps: an improved entity recognition model is used to recognize data entities containing potential sensitive contents in original government affair data after structured analysis, and a sensitive label is generated;sensitivity evaluation is performed on the data entities, and an improved clustering algorithm is used to perform sensitive grading processing on the data entities;an adaptive encryption algorithm is used to perform encryption processing and data replacement on the sensitive graded data entities, and government affair shared data is obtained.The application proposes a government affair data protection method fusing entity recognition, sensitivity evaluation and adaptive encryption strategy, a multi-dimensional sensitivity matrix is constructed, potential sensitive fields are finely graded, a matched encryption mode is matched, shape-preserving encryption protection of high-sensitivity entities is realized, desensitization replacement of low-sensitivity entities is realized, and the privacy security and structural usability of government affair data sharing are improved.

The invention provides a data sharing method and system of an industrial internet, and relates to the technical field of the industrial internet, and the method comprises the steps: obtaining equipment data of various heterogeneous industrial equipment in the industrial internet, and carrying out the analysis of the equipment data to obtain protocol type features and structured data; then dynamically distributing the structured data to an edge computing node or a cloud computing node through a load balancing strategy according to the protocol type characteristics, the data size and the real-time level; after distribution is completed, semantic analysis is carried out on the structured data by using a deep neural network based on an attention mechanism to extract key semantic information, and the key semantic information is converted into intermediate representation data; and finally, performing differential privacy processing on the intermediate representation data according to the data sensitivity level and the query frequency, and sharing the processed data in the industrial internet. The heterogeneous data sharing efficiency of the industrial internet is improved.

The invention discloses a hierarchical privacy protection data sharing method and device based on classification transformation perturbation, and the method comprises the steps: a terminal user freely selects a privacy budget, carries out the standardized preprocessing of numeric privacy data, carries out the classification of the preprocessed privacy data, and carries out the classification perturbation under the corresponding privacy budget. And carrying out classified restoration operation to output privacy-protected data, and uploading the classified and restored data and the corresponding privacy level to a server for hierarchical storage. And finally, grading data sharing is performed on the data under the multiple privacy grades, and the data users of the corresponding credibility grades can only obtain the disturbance reduction data under the corresponding privacy budget for data analysis. According to the method, a new solution is provided for high-availability hierarchical privacy protection mean value estimation.

This invention relates to the field of micro-frontend architecture technology, providing a method and device for cross-application data reactive sharing based on the Qiankun micro-frontend. The method includes: encapsulating a data sharing hook module and creating a cross-application shared data scope on a global window object; exposing an initialization method within the data sharing hook module; the initialization method receiving a unique identifier for reactive data and default values ​​for reactive data initialization as parameters, creating or retrieving a corresponding reactive data storage object within the cross-application shared data scope, attaching the reactive object to the storage object, and simultaneously returning the reactive data of the current application and its setting function; when any Qiankun micro-frontend application calls the setting function to update data, the data sharing hook module locates the corresponding reactive data storage object based on the unique identifier of the reactive data, triggering reactive updates in each application view. This invention simplifies the development process and enables synchronous updates across application views.

This invention discloses a cross-disciplinary report data sharing and matching method and system based on ontology mapping, belonging to the field of power system data processing technology. This invention deeply integrates data anti-tampering and loss recovery mechanisms with the real-time power flow calculation unique to the power grid. While completing the cross-disciplinary data record sequence completion, it automatically triggers underlying physical reversal tracking. Then, when tracing affected distribution paths, it accurately identifies power flow reversals and automatically generates reverse power receiving tags for relevant nodes. Business data containing directional dimension features is accurately synchronized to the marketing asset system through an ontology mapping dictionary. This not only solves the pain point of abnormal line loss calculations caused by business systems relying on fixed incorrect topologies, achieving adaptive consistency between the line loss model and the actual power flow of the physical power grid, but also greatly reduces the workload of manual verification caused by changes in power grid operation modes, improving the high-concurrency processing efficiency and intelligence level of data traceability.

The invention discloses a data processing system based on BIM (Building Information Modeling) multi-specialty collaborative building design, and belongs to the technical field of calculation instruments. Data full-process processing of building, structure and electromechanical multi-specialty collaborative design is realized through modular design. The core process of the method comprises the steps of collecting and purifying multi-professional design parameters, extracting pipeline and building-structure collaborative conflict characteristic parameters, quantitatively generating two types of conflict indexes, performing risk grading, triggering grading visual early warning and corresponding disposal strategies, and realizing real-time data sharing and whole-process linkage based on a collaborative center of a unified standard. According to the system, the problems of insufficient model depth, low conflict processing efficiency, poor software interoperability, collaboration barriers and the like in traditional BIM application are solved, the data fine management level and the conflict processing efficiency are improved, the data consistency in the whole period of design-construction-operation and maintenance is guaranteed, and the system is suitable for various building engineering multi-specialty collaboration design scenes.

The invention discloses a data sharing and exchanging method based on deep learning, and relates to the technical field of computers, the method is based on dynamic evaluation of state metadata, real-time traffic events, vehicle space-time states and equipment quality are jointly mapped into value evaluation scores, a client participates in decision making and is updated in real time along with evolution of the events, and the data sharing and exchanging efficiency is improved. Therefore, omission of key data in an emergency scene due to static trajectory similarity is reduced; a time-space fusion mechanism of road network topological coding and event guidance is introduced into a value evaluation network, so that event influence can cover upstream and downstream road sections along a topological relation and is associated with a time difference, and then the identification capability and scheduling consistency of vehicles on key paths are improved; in addition, quality information such as positioning precision, sensor validity and missing rate is brought into evaluation input, and a missing / verification processing and parameter updating validity verification mechanism is introduced in a training scheduling and aggregation link, so that abnormal client updating is inhibited or eliminated, and the stability of a cooperative training process is improved.