A cross-domain multi-modal scientific and technological resource identification full life cycle management system

Abstract

The application discloses a kind of cross-domain multimodal science and technology resource identification's whole life cycle management system, it is related to whole life cycle management technical field.The cross-domain multimodal science and technology resource identification's whole life cycle management system includes the following steps: resource update management module;Capture and synchronization management module;Storage and analysis management module.The application monitors the update condition of multimodal science and technology resources, based on the monitoring result, the identification capture and synchronization analysis of multimodal science and technology resource identification are carried out, whether the identification storage and analysis are judged according to the analysis result, if it is carried out, the identification storage and analysis are triggered, and whether the trigger identification analysis optimization is carried out, if it is judged not to be carried out, then the incremental operation of internal queue processing rate is executed, the effect of improving identification synchronization accuracy is achieved, the problem of low identification synchronization accuracy of cross-domain multimodal science and technology resources in the update and derivative form generation process in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of full life cycle management, in particular to a cross-domain multi-modal scientific and technological resource identification full life cycle management system. BACKGROUND

[0002] In order to systematically manage scientific and technological resource identification from different fields (cross-domain), different forms (such as scientific data, academic papers, software code, experimental instruments, scientific researchers, and supporting text, image, audio, video, algorithm model, etc.), the existing method first standardizes the description of multi-modal scientific and technological resources and generates and strongly binds the unique identifier, realizes the unique generation of cross-domain multi-modal resource, and generates tamper-proof identification; then through the block chain evidence and digital signature technology, the multi-modal scientific and technological resource identification and its metadata are registered in the distributed registration center. When the user initiates a resolution request, the system can quickly locate and return the resource address and metadata, and simultaneously start the verification service to ensure the integrity of the resource content and the authenticity of the source. On this basis, the multi-modal scientific and technological resource identification as a trusted hub triggers a series of intelligent services such as reference analysis, correlation discovery, and traceability visualization, and continuously collects usage data for dynamic evaluation and influence assessment, and finally completes the standard cancellation and archiving when the resource is invalid. In the evaluation stage, through the on-chain storage of analysis logs, usage credentials and user feedback, a multi-dimensional credit score and dynamic cancellation mechanism is constructed to drive continuous optimization and closed-loop management of identification quality, thereby systematically supporting the full life cycle trusted management of cross-domain multi-modal scientific and technological resources from birth to retirement.

[0003] For example, the Chinese invention patent with publication number CN116797029B discloses an IDI full life cycle risk digital management method and system, which includes: obtaining a baseline risk assessment value of a target building unit based on a preset engineering evaluation rule; in response to a risk impact event occurring in the target building unit, updating the baseline risk assessment value according to the risk impact event to obtain a pending risk assessment value; in response to the confirmation result of the pending risk assessment value and the risk impact event, setting the pending risk assessment value as an application risk assessment value; based on the application risk assessment value, adjusting and updating the security settlement resources of the target building, and publishing the updated security settlement resources.

[0004] For example, the invention patent with the publication number CN112749335B discloses a life cycle state prediction method, device, computer equipment and storage medium, which comprises: obtaining user behavior data; initializing the life cycle state of the participating business according to the user behavior data to obtain a binary expression; initializing the business dynamic matrix according to the resource consumption and the number of life cycle states for each participating business; using matrix decomposition method, the binary expression and the business expression are interactively learned, the consumption resource amount of the participating business is fitted as the target, and the mean square error is taken as the loss function, the training is carried out, and the mean square error is obtained; the mean square error is assigned to the corresponding position of the corresponding dynamic business matrix; iterative training, dynamic programming solution learning obtains a life cycle state path that minimizes the mean square error; determine the life cycle state according to the life cycle state path.

[0005] The above-mentioned technology at least has the following technical problems:

[0006] In the generation process of cross-domain multi-modal scientific and technological resources, due to the update of cross-domain multi-modal scientific and technological resources, it is difficult to capture the full amount of updates in real time and synchronize to the identifier (especially for image and video derived form of cross-domain multi-modal scientific and technological resources generated by visualization processing, it is difficult to accurately capture and synchronize to the corresponding identifier due to the update of the original data driving the derived form iteration), at the same time, the existing technology often uses fixed data collection, cleaning and storage process, lacks dynamic adaptation ability for cross-domain multi-modal characteristics, lacks dynamic detection model or form conversion capture algorithm, so as to accurately capture dynamic association and derived change, which may cause the following two core problems: one is the rupture of the association relationship between the identifier and the derived form of the resource, the other is that the metadata update lags behind the actual form change of the resource, so that the analysis request returns the outdated resource address or metadata, which does not match the latest resource state expected by the user, and then causes the resource hash or pointer returned by the analysis module to be inconsistent with the actual resource version, at the same time, causes logical discontinuity in the association discovery and tracing process, and then causes the analysis log, use voucher and user feedback data in the evaluation stage to exist deviation, and then causes the cross-domain multi-modal scientific and technological resources in the update and derived form generation process to have the problem of low accuracy of identifier synchronization. SUMMARY

[0007] In order to solve the technical problem of low accuracy of identifier synchronization of cross-domain multi-modal scientific and technological resources in the update and derived form generation process in the prior art, the embodiment of the present application provides a full life cycle management system for cross-domain multi-modal scientific and technological resource identifier. The technical scheme is as follows:

[0008] Provided is a cross-domain multi-modal technological resource identification full life cycle management system, comprising a resource update management module, a capture and synchronization management module, and a storage and analysis management module; the resource update management module is used to monitor the update of the multi-modal technological resource in the update and derivative form generation process of the cross-domain multi-modal technological resource, to evaluate the multi-modal technological resource update delay, and to transmit the corresponding monitoring result to the capture and synchronization management module after monitoring; the capture and synchronization management module is used to capture and synchronize the multi-modal technological resource identification based on the received monitoring result, to evaluate the qualification of the multi-modal technological resource identification capture and synchronization, to judge whether to perform identification storage and analysis based on the analysis result, to reflect the storage qualification of the multi-modal technological resource identification in the blockchain storage process, to transmit the corresponding analysis result to the storage and analysis management module if it is judged to perform, and to perform an incremental operation of the internal queue processing rate if it is judged not to perform, to solve the identification processing backlog and avoid synchronization lag accumulation; the storage and analysis management module is used to perform identification storage and analysis based on the received analysis result, to judge whether to trigger identification analysis optimization according to the identification storage and analysis result, to accelerate the identification update on-chain, and to guarantee the consistency of the blockchain management consensus.

[0009] The technical scheme provided by the embodiment of the application has at least the following beneficial effects:

[0010] 1. By monitoring the update of the multi-modal technological resource, real-time perception of the full update of the cross-domain multi-modal technological resource is achieved, the iterative changes of the original data update and the derivative form (such as visual images and videos) are accurately captured, the multi-modal technological resource identification is captured and synchronized based on the monitoring result, and whether to perform identification storage and analysis is judged according to the analysis result, which helps to realize the accuracy and consistency of the blockchain storage data, prevents the storage hash from not matching the actual resource due to identification synchronization deviation, performs identification storage and analysis based on the received analysis result if it is judged to perform, judges whether to trigger identification analysis optimization according to the identification storage and analysis result, performs an incremental operation of the internal queue processing rate if it is judged not to perform, helps to realize efficient flow of identification processing tasks, quickly digests the identification tasks accumulated due to failed verification, avoids synchronization lag accumulation, guarantees smoothness of the identification management process closed loop, and further improves the identification synchronization accuracy of the cross-domain multi-modal technological resource in the update and derivative form generation process, solving the problem of low identification synchronization accuracy of the cross-domain multi-modal technological resource in the update and derivative form generation process in the prior art.

[0011] 2. The preset update interference degree data is obtained by monitoring the update situation of the multi-modal technological resource. When the preset update interference degree data is within the preset update interference degree qualified range, the multi-modal technological resource identifier is captured and synchronously analyzed. Compared with the passive monitoring of the update interference in the prior art, it helps to realize the accurate identification of the cross-domain multi-modal technological resource update behavior, avoid the identification capture deviation caused by the update interference, and ensure the accuracy of the initial association of the identifier and the resource (especially the derivative form resource).

[0012] 3. A round of capture verification is performed to obtain a round of capture verification quantitative value. When the round of capture verification quantitative value is greater than the preset round of capture verification quantitative value, a second round of synchronous verification is triggered, otherwise a capture verification management optimization is triggered. Compared with the single fixed verification process in the prior art, it helps to realize the accuracy controllable of the multi-modal technological resource identifier capture and synchronization, accurately capture the resource derivative form change and dynamic association through hierarchical verification and targeted optimization (dynamic adjustment of polling frequency), solve the update synchronization lag problem, and ensure the real-time alignment of the identifier and the resource state.

[0013] 4. The preset storage certificate qualified degree score is obtained by performing identifier storage and analysis. If the preset storage certificate qualified degree score is within the pre-set storage certificate qualified range, the identifier analysis accuracy analysis is started and an identifier analysis analysis value is obtained. When the identifier analysis analysis value is not greater than the preset identifier analysis analysis value, the identifier analysis optimization is triggered. Compared with the limitations of the fixed caching and analysis strategy in the prior art, it helps to realize the efficient cooperation of the blockchain storage and analysis, accelerates the identifier chaining and analysis response by dynamically reducing the cache window, avoids returning obsolete metadata or resource addresses in the analysis, ensures that the analysis result is consistent with the latest resource state of the user demand, and improves the analysis correctness and timeliness.

[0014] 5. When considering data verification at nodes in different areas, the multi-modal technological resource identifier life cycle gradually enters the decay stage, the analysis accuracy of some nodes gradually decays, and some unstable network nodes cannot provide accurate verification results. Based on the identifier analysis analysis model, the identifier analysis accuracy analysis is performed, and when the value output by the identifier analysis analysis model is within the preset qualified analysis qualified range, the qualified blockchain node consensus verification data is archived. It helps to realize the accurate screening and reliable retention of the decay period identifier verification data, eliminate invalid node interference data, ensure the authenticity and integrity of the archived data, and further ensure the closed-loop nature of the multi-modal technological resource identifier full life cycle management. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required by the embodiments described in the present application. Obviously, the drawings described in the following embodiments are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0016] Figure 1 is a structural schematic diagram of a cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiments of the present application;

[0017] Figure 2 is a general overview diagram of a cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiments of the present application;

[0018] Figure 3 is a capture verification management optimization schematic diagram of a cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiments of the present application;

[0019] Figure 4 is an identification analysis optimization schematic diagram of a cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiments of the present application. DETAILED DESCRIPTION

[0020] The technical solutions in the present application will be described below with reference to the drawings.

[0021] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0022] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent. "Of", "corresponding" and "corresponding" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent.

[0023] In order to make the technical problems, technical solutions and advantages of the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0024] The embodiments of the present application provide a cross-domain multi-modal scientific and technological resource identification full life cycle management system. As shown inFigure 1 The structure diagram of the whole life cycle management system of the cross-domain multi-modal scientific and technological resource identification is shown, which includes a resource update management module, a capture and synchronization management module, and a storage and analysis management module. The resource update management module is used to monitor the update of the multi-modal scientific and technological resource during the update and derivative form generation process of the cross-domain multi-modal scientific and technological resource, to evaluate the update delay of the multi-modal scientific and technological resource, and to transmit the corresponding monitoring result to the capture and synchronization management module after monitoring. Through resource update management, it helps to realize the dynamic adaptation of cross-domain multi-modal scientific and technological resource update behavior, accurately capture the iterative changes of derivative forms driven by original data, break the adaptation limitations of fixed processes to multi-modal characteristics, and ensure the real-time and integrity of resource state from the source.

[0025] The capture and synchronization management module is used to capture and synchronize the multi-modal scientific and technological resource identification based on the received monitoring result, to evaluate the qualified condition of the multi-modal scientific and technological resource identification capture and synchronization, to judge whether to perform identification storage and analysis based on the analysis result to reflect the storage qualified condition of the multi-modal scientific and technological resource identification in the process of blockchain storage, if it is judged to perform, the corresponding analysis result is transmitted to the storage and analysis management module, if it is judged not to perform, the incremental operation of internal queue processing rate is executed, which is used to solve the identification processing backlog to avoid synchronization lag accumulation; through the capture and synchronization management, it helps to realize the real-time binding of resource update state and unique identification, reduce the association breakage of derivative forms and original resources, avoid the update of metadata lagging behind the actual change of resources, and ensure the accuracy of identification synchronization.

[0026] The storage and analysis management module is used to perform identification storage and analysis based on the received analysis result, to judge whether to trigger identification analysis optimization according to the identification storage and analysis result, to accelerate the identification update on chain, and to ensure the consistency of blockchain management consensus; through the storage and analysis management, it helps to realize the trusted storage of identification and metadata in the blockchain, to ensure the data hash consistency of node consensus verification, to ensure the return of the latest and accurate resource address and metadata of the analysis request, and to avoid the deviation of analysis result.

[0027] It should be noted that before the design of the whole life cycle management system of the cross-domain multi-modal scientific and technological resource identification provided in the present application, various types of setting data are stored, which are used to store various types of setting data to ensure efficient operation and accurate management of the system. The database is stored by using a relational database management system (such as MySQL, Oracle, etc.), which utilizes its mature data storage and management functions to ensure the safety and reliability of data; the database contains but is not limited to preset capture verification quantitative values, preset optimization capture verification values, etc., in which various types of values are directly set by technical personnel.

[0028] AsFigure 2 As shown, it is a general overview diagram of a cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiment of the application; by Figure 2 It can be known that: by monitoring the update of the multi-modal scientific and technological resource to obtain preset update interference degree data, when the preset update interference degree data is not within the qualified range of the preset update interference degree, a feedback prompt of re-acquiring the multi-modal scientific and technological resource is sent to the preset personnel, otherwise, a round of capture verification is performed to obtain a round of capture verification quantitative value; when the monitored round of capture verification quantitative value is not greater than the preset round of capture verification quantitative value, capture verification management optimization is performed, otherwise, a second round of synchronous verification is triggered to obtain a second round of synchronous verification quantitative value; when the second round of synchronous verification quantitative value obtained after the second round of synchronous verification is not greater than the preset second round of synchronous verification quantitative value, identification storage and analysis are started, if the internal queue processing rate increases to the maximum value of the corresponding preset range, the second round of synchronous verification quantitative value is still greater than the preset second round of synchronous verification quantitative value, and a second round of synchronous verification alarm prompt is sent; by performing identification storage and analysis, a preset storage qualified degree score is obtained, when the monitored preset storage qualified degree score is within the pre-set storage qualified range, identification analysis accuracy analysis is started, otherwise, an identification analysis accuracy analysis start failure prompt is sent.

[0029] In the embodiment, through the interaction and mutual contact of the resource update management module, the capture and synchronous management module and the storage and analysis management module, the cross-domain multi-modal scientific and technological resource is helpful to realize the full-process closed-loop management and control from the update perception, identification synchronization to the storage analysis, solve a series of problems caused by the asynchronous resource update and identification synchronization, further guarantee the logical integrity of the correlation discovery and traceability visualization, ensure the accuracy of the analysis log, use voucher and other data relied on in the evaluation stage, and provide solid support for the full life cycle trusted management of the cross-domain multi-modal scientific and technological resource.

[0030] Further, the updating of the multi-modal technological resource is monitored, and the specific process is as follows: based on the obtained multi-modal technological resource updating request sending time and the corresponding updating signal captured by the system, the quantitative processing is carried out, and the multi-modal technological resource updating interference value for quantifying the multi-modal technological resource updating delay condition is output; through the multi-modal technological resource updating monitoring corresponding to the preset time period, based on the timer, the multi-modal technological resource updating request sending time and the time when the corresponding updating signal is captured by the system are monitored, and the time difference between the two is represented as the multi-modal technological resource updating interference value; according to the multi-modal technological resource updating interference value, it is judged whether the identification capture and synchronization process is triggered, and the specific judgment is: the multi-modal technological resource updating interference value is substituted into the preset resource updating interference degree comparison table, if the preset updating interference degree data output by the preset resource updating interference degree comparison table is within the preset updating interference degree qualified range set by the preset personnel in advance, the corresponding multi-modal technological resource identification is obtained, and the obtained multi-modal technological resource identification is subjected to identification capture and synchronization analysis, otherwise, the feedback prompt of reacquiring the multi-modal technological resource is sent to the preset personnel.

[0031] It should be noted that in the embodiments of the present application, a series of key information extracted from the database is described, including the preset resource updating interference degree comparison table, the preset first-level polling frequency related comparison list, the preset second-level polling frequency related comparison list, the preset synchronization verification related comparison list, the preset storage qualified degree related list, the preset cache window related list, the preset analysis deviation level related table, the preset cache time reading table, etc. And the corresponding mapping relationship has the characteristics of dynamic change, which can realize the accurate one-to-one mapping relationship between a single parameter and a single parameter, and also can realize the complex many-to-one mapping between multiple parameters and a single parameter.

[0032] The specific operation process is as follows: first, the combination of the update interference value of the multi-modal scientific and technological resource collected by the preset personnel in the historical time period, the first capture verification quantitative value and the query request times of the multi-modal scientific and technological resource identifier, the combination of the second capture verification quantitative value and the query request times of the multi-modal scientific and technological resource identifier, the combination of the two-round synchronous verification quantitative value and the network capacity corresponding to the multi-modal scientific and technological resource identifier, the storage qualified judgment value, the parameter combination of the identifier analysis analysis value and the cache request duration of the multi-modal scientific and technological resource identifier, the identifier analysis deviation characteristic value, the identifier analysis deviation degree level value and the combination of the access frequency of the multi-modal scientific and technological resource identifier and other related information are input into the machine learning model in turn. The model selected here is, for example, a decision tree model, which has the ability to reveal the key degree of features. With the feature splitting mechanism of the model, the corresponding weight value or other data information can be extracted, which are the preset update interference degree data, the preset first polling frequency optimization degree value, the preset second polling frequency optimization degree value, the preset queue processing rate adjustment value, the preset storage qualified degree score, the preset cache window adjustment value, the identifier analysis deviation degree level value, the preset cache time adjustment value, etc.; then, the data obtained by the model in the historical time period is associated and matched with the corresponding weight or data to generate the preset resource update interference degree table, the preset first polling frequency related comparison list, the preset second polling frequency related comparison list, the preset synchronous verification related comparison list, the preset storage qualified degree related list, the preset cache window related list, the preset analysis deviation degree related table, the preset cache time reading table, etc.; finally, the update interference value of the multi-modal scientific and technological resource collected in real time, the combination of the first capture verification quantitative value and the query request times of the multi-modal scientific and technological resource identifier, the combination of the second capture verification quantitative value and the query request times of the multi-modal scientific and technological resource identifier, the combination of the two-round synchronous verification quantitative value and the network capacity corresponding to the multi-modal scientific and technological resource identifier, the storage qualified judgment value, the parameter combination of the identifier analysis analysis value and the cache request duration of the multi-modal scientific and technological resource identifier, the identifier analysis deviation characteristic value, the identifier analysis deviation degree level value and the combination of the access frequency of the multi-modal scientific and technological resource identifier and other related information are substituted into the preset resource update interference degree table, the preset first polling frequency related comparison list, the preset second polling frequency related comparison list, the preset synchronous verification related comparison list, the preset storage qualified degree related list, the preset cache window related list, the preset analysis deviation degree related table, the preset cache time reading table, etc. which have been constructed, according to the preset mapping relationship, the preset update interference degree data, the preset first polling frequency optimization degree value, the preset second polling frequency optimization degree value, the preset queue processing rate adjustment value, the preset storage qualified degree score, the preset cache window adjustment value, the identifier analysis deviation degree level value, the preset cache time adjustment value, etc. related results whose value range is limited in the interval of 0-1.

[0033] In the embodiment, the updating interference value and the preset updating interference degree data of the multi-modal technological resource are obtained by monitoring the updating situation of the multi-modal technological resource, and when the preset updating interference degree data is within the qualified range of the preset updating interference degree, identification capture and synchronous analysis are performed, otherwise a feedback prompt for re-acquiring the multi-modal technological resource is sent to the preset personnel, which helps to realize the pre-control of the updating quality of the multi-modal technological resource, filter invalid identification synchronization behaviors caused by excessive updating interference, ensure that the resource updating state is real and reliable in the identification capture and synchronization link, avoid mismatch between identification and resource state caused by interference data, further ensure the consistency of data hash in subsequent blockchain storage, improve the accuracy of analysis request return result, provide high-quality data basis for intelligent services such as association discovery, traceability visualization and dynamic evaluation, and promote the precision of the whole process of multi-modal technological resource identification synchronization.

[0034] Further, the identification capture and synchronous analysis includes a round of capture verification for evaluating the identification capture state of the multi-modal technological resource and a round of synchronous verification for evaluating the identification synchronization state of the multi-modal technological resource. The specific process of the round of capture verification is as follows: the actual updating times of the multi-modal technological resource are quantitatively processed to obtain a round of capture verification quantitative value for quantifying the identification capture accuracy of the multi-modal technological resource; the round of capture verification quantitative value represents the actual updating times of the multi-modal technological resource successfully captured by the counter in a preset time period corresponding to the multi-modal technological resource updating monitoring; based on the round of capture verification quantitative value, it is judged whether to trigger the round of synchronous verification, specifically: if the round of capture verification quantitative value is greater than a preset round of capture verification quantitative value, the round of synchronous verification is triggered, otherwise the corresponding round of capture verification quantitative value is marked as a to-be-optimized capture verification quantitative value, and the multi-modal technological resource identification is fed back to the preset personnel in the preset time period corresponding to the current multi-modal technological resource updating monitoring, and the capture verification management optimization is performed in the next adjacent multi-modal technological resource updating monitoring corresponding to the preset time period, so as to ensure the synchronization of identification and resource state, wherein the preset round of capture verification quantitative value is represented by the average value of the historical time period round of capture verification quantitative value.

[0035] As shown in Figure 3 Fig. 1 is a capture verification management optimization schematic diagram of a whole life cycle management system of cross-domain multi-modal technological resource identification provided by the embodiment of the present application; and Figure 3It can be seen that when the to-be-optimized capture verification quantitative value is greater than the preset to-be-optimized capture verification value, a first-level capture verification correlation analysis is triggered, a magnitude corresponding to a preset first-level polling frequency optimization degree value is taken as a regulation step, and the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier; when the to-be-optimized capture verification quantitative value is not greater than the preset to-be-optimized capture verification value, a second-level capture verification correlation analysis is triggered, a magnitude corresponding to a preset second-level polling frequency optimization degree value is taken as a regulation step, and the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier.

[0036] It should be added that the specific process of capture verification management optimization is as follows: based on the to-be-optimized capture verification quantitative value and the preset to-be-optimized capture verification value, the optimization level of the capture verification management optimization is judged: when the to-be-optimized capture verification quantitative value is greater than the preset to-be-optimized capture verification value, the corresponding to-be-optimized capture verification quantitative value is marked as a first-level capture verification quantitative value, otherwise the corresponding to-be-optimized capture verification quantitative value is marked as a second-level capture verification quantitative value, wherein the preset to-be-optimized capture verification value is represented by the average value of the to-be-optimized capture verification quantitative value in the historical time period; when the first-level capture verification quantitative value is monitored, a first-level capture verification correlation analysis is triggered, and the analysis process is: the first-level capture verification quantitative value and the number of query requests of the multi-modal scientific resource identifier monitored by the counter are substituted into the preset first-level polling frequency correlation list, the corresponding preset first-level polling frequency optimization degree value is queried, and the magnitude corresponding to the preset first-level polling frequency optimization degree value is taken as a regulation step, and the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier; when the second-level capture verification quantitative value is monitored, a second-level capture verification correlation analysis is triggered, and the analysis process is: the second-level capture verification quantitative value and the number of query requests of the multi-modal scientific resource identifier are substituted into the preset second-level polling frequency correlation list, the corresponding preset second-level polling frequency optimization degree value is queried, and the magnitude corresponding to the preset second-level polling frequency optimization degree value is taken as a regulation step, and the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier; the first-level capture verification correlation analysis and the second-level capture verification correlation analysis further include: after the polling frequency of the multi-modal scientific resource identifier is increased once, if the re-acquired one-round capture verification quantitative value is greater than the preset one-round capture verification quantitative value, a two-round synchronous verification is started, if it is monitored that the polling frequency reaches the maximum value corresponding to the preset range set by the preset personnel, the one-round capture verification quantitative value is still not greater than the preset one-round capture verification quantitative value, and a capture verification management optimization warning prompt is sent.

[0037] By triggering a first-level capture verification correlation analysis when the to-be-optimized capture verification quantitative value is greater than the preset to-be-optimized capture verification value, and taking the amplitude corresponding to the preset first-level polling frequency optimization degree value as the adjustment step, the polling frequency of the multi-modal technological resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal technological resource identifier, which helps to improve the capture sensitivity and response speed of the multi-modal technological resource (especially the derived form) update behavior in high-interference and high-dynamic update scenarios, quickly make up for the identifier synchronization lag caused by the capture not in time, and then realize the accurate improvement of the capture verification quality in high-priority update scenarios, and guarantee the real-time association of the identifier and the resource update state.

[0038] By triggering a second-level capture verification correlation analysis when the to-be-optimized capture verification quantitative value is not greater than the preset to-be-optimized capture verification value, and taking the amplitude corresponding to the preset second-level polling frequency optimization degree value as the adjustment step, the polling frequency of the multi-modal technological resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal technological resource identifier, which helps to improve the stability and efficiency of the capture verification in low-interference and conventional update scenarios, while avoiding excessive consumption of resources, steadily optimizing the comprehensiveness of capture coverage, reducing the risk of potential update omission, and providing continuous and reliable support for the accuracy of identifier synchronization.

[0039] It needs to be specifically pointed out that the specific process of the second round of synchronization verification is as follows: based on the obtained metadata of the multi-modal scientific and technological resource identifier binding, the time of completing the update and the time of writing the metadata into the distributed registration center are quantized to obtain the second round of synchronization verification quantitative value representing the degree of asynchronization of the multi-modal scientific and technological resource identifier; in the preset time period corresponding to the multi-modal scientific and technological resource update monitoring, based on the time of completing the update of the metadata of the multi-modal scientific and technological resource identifier binding monitored by the timer and the time of writing the metadata into the distributed registration center, the time difference between the two is represented as the second round of synchronization verification quantitative value; based on the second round of synchronization verification quantitative value, if the second round of synchronization verification quantitative value is not greater than the preset second round of synchronization verification quantitative value, the corresponding result is marked as performing identifier storage and analysis, and the identifier storage and analysis process is started, wherein the preset second round of synchronization verification quantitative value is represented by the average value of the historical time period second round of synchronization verification quantitative value, otherwise the corresponding result is marked as not performing identifier storage and analysis, and the multi-modal scientific and technological resource identifier obtained in the preset time period corresponding to the present multi-modal scientific and technological resource update monitoring is fed back to the preset personnel, and in the next adjacent preset time period corresponding to the multi-modal scientific and technological resource update monitoring, the amplitude corresponding to the preset queue processing rate adjustment value of the multi-modal scientific and technological resource identifier is used as the adjustment step, and on the basis of the initial queue processing rate of the multi-modal scientific and technological resource identifier, the incremental operation of the internal queue processing rate is performed, which helps to improve the processing efficiency of the identifier synchronization task, avoid the intensification of identifier and resource state synchronization delay caused by queue congestion, adapt to the synchronization demand in the high-frequency update scene of multi-modal scientific and technological resources (including original resources and derivative forms), and then realize the dynamic matching of the identifier synchronization link and the resource update rhythm, so as to ensure that the synchronized identifier can accurately reflect the latest state of the resource, and provide efficient process support for the data hash consistency in subsequent blockchain storage and the accuracy of the return result of the analysis request; the preset queue processing rate adjustment value is obtained by inputting the second round of synchronization verification quantitative value and the network capacity corresponding to the multi-modal scientific and technological resource identifier monitored by the network tester into the preset synchronization verification related comparison list; every time the incremental operation of the internal queue processing rate is performed, the value synchronization verification of the second round of synchronization verification quantitative value is triggered, that is, when the newly obtained second round of synchronization verification quantitative value is not greater than the preset second round of synchronization verification quantitative value, the identifier storage and analysis is started; the value synchronization verification also includes: if the internal queue processing rate increases to the maximum value of the preset range set by the preset personnel, and the second round of synchronization verification quantitative value is still greater than the preset second round of synchronization verification quantitative value, a second round of synchronization verification alarm is sent.

[0040] In the embodiment, a round of capture verification is performed to obtain a round of capture verification quantitative value, and when the round of capture verification quantitative value is greater than a preset round of capture verification quantitative value, a second round of synchronization verification is triggered, otherwise a capture verification management optimization is triggered, which helps to realize accurate quality control of the multi-modal technological resource identification capture link, screen out scenes with substandard capture quality through quantitative indicators and optimize the capture strategy in a timely manner, and at the same time ensure that the updated data with up-to-standard capture effect enters the subsequent synchronization link, thereby improving the accuracy and reliability of identification capture from the source; a second round of synchronization verification is performed to obtain a second round of synchronization verification quantitative value, and when the second round of synchronization verification quantitative value is not greater than a preset second round of synchronization verification quantitative value, an identification storage and analysis process is started, otherwise an incremental operation of the internal queue processing rate is performed, which helps to realize dynamic adaptation and efficiency regulation of the identification synchronization process, avoid identification lag caused by insufficient synchronization rate, and ensure that the synchronized identification and resource state are highly matched to provide a stable precondition for subsequent storage and analysis.

[0041] Through the mutual influence of the round of capture verification and the second round of synchronization verification, the multi-modal technological resource identification is subjected to double verification and dynamic optimization from capture to synchronization, the hash consistency of the blockchain storage and the accuracy of the analysis result are ensured, and a solid identification foundation is provided for the correlation discovery, traceability visualization and dynamic evaluation in the whole life cycle of the cross-domain multi-modal technological resource.

[0042] Further, the specific process of identification storage and analysis is as follows: storage qualification determination is performed: the obtained storage qualification determination value is input into a preset storage qualification degree related list, and a preset storage qualification degree score is output; the average number of consistent nodes in the hash value of the blockchain storage of the resource data corresponding to the same multi-modal technological resource identification is taken as the storage qualification determination value through the counter monitoring; the storage qualification determination value is used to reflect the storage qualification degree in the process of blockchain storage based on the multi-modal technological resource identification; the deviation degree is judged based on the preset storage qualification degree score; if the preset storage qualification degree score is within the preset storage qualification range, the corresponding blockchain node consensus verification data (such as the unique identification code of the multi-modal technological resource, the identification version number, the identification generation timestamp, etc.) is marked as qualified blockchain node consensus verification data, and identification analysis accuracy analysis is started, otherwise an identification analysis accuracy analysis start failure prompt is sent.

[0043] In the embodiment, the qualified determination value and the preset storage certificate qualified score are obtained by performing the identification storage certificate and analysis, when the preset storage certificate qualified score is within the storage certificate qualified range, the identification analysis accuracy analysis is started, otherwise the identification analysis accuracy analysis start failure prompt is sent, which is helpful to realize the front-end quality control of the multi-modal scientific and technological resource identification storage certificate link, filter out the effective identification with the storage certificate state compliance and data hash consistency from the source, and ensure the credibility of the identification basic data entering the analysis link.

[0044] As an embodiment of the first aspect, the specific process of identification analysis accuracy analysis is as follows: obtaining an identification analysis value reflecting the analysis accuracy when the data is analyzed based on the qualified blockchain node consensus verification; monitoring the number of correct analysis of the multi-modal scientific and technological resource identification corresponding analysis request and the total number of analysis request by the counter, and representing the ratio of the two as the identification analysis value; judging based on the identification analysis value; if the identification analysis value is greater than the preset identification analysis value, the corresponding qualified blockchain node consensus verification data is archived, otherwise the qualified blockchain node consensus verification data obtained in the preset time period corresponding to the identification storage certificate and analysis is fed back to the preset personnel, and the identification analysis optimization is triggered in the next adjacent preset time period corresponding to the identification storage certificate and analysis, wherein the preset identification analysis value is represented by the average value of the historical time period identification analysis value.

[0045] As shown in Figure 4 , it is a kind of identification analysis optimization schematic diagram of cross-domain multi-modal scientific and technological resource identification full life cycle management system provided by the embodiment of the application; specifically, the specific process of triggering identification analysis optimization is as follows: the identification analysis value and the parameter of the cache request time length of the multi-modal scientific and technological resource identification monitored by the timer are combined and substituted into the preset cache window related list to output the preset cache window adjustment value; based on the preset cache window adjustment value, the cache window of the blockchain storage is decremented; the cache window decrement operation means that the amplitude corresponding to the preset cache window adjustment value is taken as the adjustment step, and the cache window is gradually decreased based on the primary cache window of the blockchain storage, which helps to improve the real-time and freshness of the blockchain storage data, and avoid the problem of storage data lag caused by too large cache window; further, the accurate matching of the blockchain storage and the latest state of the multi-modal scientific and technological resource is realized, the consistency of data hash in node consensus verification is ensured, and the credibility of the storage link is strengthened, which provides reliable storage support for the identification management full link; and after each decrement, if the newly obtained identification analysis value is greater than the preset identification analysis value, the on-chain identification deviation analysis is started; if the cache window of the blockchain storage reaches the minimum cache window during the execution of the cache window decrement operation, and the identification analysis value is still not greater than the preset identification analysis value, the identification analysis warning prompt is sent.

[0046] The specific process of the uplink identifier deviation analysis is as follows: the identifier resolution analysis value obtained after triggering the identifier resolution optimization is marked as an optimized identifier resolution analysis value; the deviation degree quantification is carried out based on the optimized identifier resolution analysis value and the preset optimized identifier resolution analysis value, and the identifier resolution deviation representation value is output; the identifier resolution deviation representation value is represented by the difference between the optimized identifier resolution analysis value and the preset optimized identifier resolution analysis value, and is used to reflect the improvement degree of the identifier resolution analysis value after triggering the identifier resolution optimization; the identifier resolution deviation representation value is classified based on the identifier resolution deviation representation value; the identifier resolution deviation representation value is input into the preset resolution deviation level related table, and the identifier resolution deviation degree level value is output; based on the identifier resolution deviation degree level value, if the identifier resolution deviation degree level value is not greater than the preset identifier resolution deviation degree level value, a resolution deviation first-level prompt is sent, and identifier resolution improvement optimization is started in the preset time period corresponding to the next adjacent uplink identifier deviation analysis, otherwise a resolution deviation second-level prompt is sent, and the corresponding blockchain node consensus verification data is archived, wherein the preset identifier resolution deviation degree level value is represented by the average value of the historical time period identifier resolution deviation degree level value; the identifier resolution improvement optimization is used to make the resolution service query the source more frequently, and ensure that the most time-optimal resource address and metadata are returned to the user.

[0047] It should be noted that the specific process of the identifier resolution improvement optimization is as follows: in the preset range corresponding to the resolution result cache time, the identifier resolution deviation degree level value and the access frequency of the multi-modal technological resource identifier monitored by the full-stack performance monitoring tool (such as Dynatrace) are input into the preset cache time reading table, the output preset cache time adjustment value corresponding to the amplitude is obtained, which is used as the adjustment step, and based on the initial resolution result cache time of the multi-modal technological resource identifier, the decrement operation of the resolution result cache time is triggered, the synchronization update of the resolution result and the actual state of the multi-modal technological resource is ensured, the user request is accurately fed back, the service quality of the resolution link is maintained, and the efficient and reliable cross-domain multi-modal technological resource identifier is supported; after each execution of the decrement operation of the resolution result cache time, if the newly obtained identifier resolution deviation degree level value is greater than the preset identifier resolution deviation degree level value, the corresponding blockchain node consensus verification data is archived; when the resolution result cache time of the modal technological resource identifier is reduced to the preset minimum resolution result cache time set by the preset personnel, if the identifier resolution deviation degree level value is still not greater than the preset identifier resolution deviation degree level value, a warning prompt of identifier resolution improvement optimization is sent.

[0048] In the embodiment, the identification resolution accuracy analysis value is obtained by performing identification resolution accuracy analysis, when the monitored identification resolution analysis value is greater than the preset identification resolution analysis value, the corresponding qualified blockchain node consensus verification data is archived, otherwise identification resolution optimization is performed, which helps to realize accurate screening and quality control of identification resolution results, retain credible resolution data meeting the requirements, and timely correct resolution deviation; after triggering identification resolution optimization, when the re-obtained identification resolution analysis value is greater than the preset identification resolution analysis value, the uplink identification deviation analysis is started to obtain the identification resolution deviation degree level value, and when the identification resolution deviation degree level value is not greater than the preset identification resolution deviation degree level value, identification resolution improvement optimization is performed, which helps to realize deep traceability and fine improvement of resolution deviation, continuously improve the accuracy and stability of identification resolution, and ensure that the resolution log and other data relied on in the evaluation stage are real and reliable, and consolidate the resolution foundation of cross-domain multi-modal scientific and technological resource life cycle credible management.

[0049] As an embodiment of the second aspect, the specific process of identification resolution accuracy analysis is as follows: an identification resolution analysis model is obtained, which is used to reflect the resolution accuracy degree when the qualified blockchain node consensus verification data is resolved; the value output by the identification resolution analysis model is judged: if the value output by the identification resolution analysis model is within the preset qualified resolution range set in advance by the preset personnel, the corresponding qualified blockchain node consensus verification data is archived, otherwise an identification resolution warning prompt is sent.

[0050] The identification resolution analysis model is obtained by the following method:

[0051] ;

[0052] In the formula, indicates the identification resolution analysis model in the tth time window, t=1, 2, 3, …, n, t indicates the total number of time windows, and n indicates the number of time windows, indicates an initial value, indicates a natural decay rate, indicates the resolution abnormality density in the tth time window, indicates an abnormality influence weight.

[0053] Wherein, In this embodiment, the initial value is 1, which is set by the preset personnel based on historical experience, which is set by the preset personnel based on historical experience, which is represented by the ratio of the number of multi-modal scientific and technological resource identification resolution failures and the total number of resolutions counted in the tth time window.

[0054] In the embodiment, by verifying data at nodes in different regions, the multi-modal technology resource identification life cycle gradually enters the decay stage, and in the case that some unstable network nodes cannot provide accurate verification results, the identification analysis accuracy is analyzed to obtain the value output by the identification analysis model, and if the value is within the preset qualified analysis qualified range, the corresponding qualified blockchain node consensus verification data is archived, otherwise, an identification analysis warning prompt is sent, which helps to realize accurate identification and risk warning of the decay stage identification analysis result, filter invalid or incorrect verification data caused by node network instability and identification life cycle decay, retain consensus verification records that meet the credibility requirements, and at the same time, timely find analysis abnormalities and trigger intervention mechanism, avoid invalid identification or incorrect analysis results to interfere with subsequent services such as correlation discovery and traceability visualization, and ensure the standardization and data credibility of the identification life cycle decay stage management.

[0055] In summary, the embodiments of the present application monitor the update of multi-modal technology resources, which helps to realize real-time perception of full update of cross-domain multi-modal technology resources, accurately capture the iterative changes of original data updates and derived forms (such as visual images and videos), capture and synchronize analysis of multi-modal technology resource identification based on the monitoring results, and determine whether to perform identification evidence storage and analysis according to the analysis results, which helps to realize the accuracy and consistency of blockchain evidence storage data, prevents the mismatch between evidence hash and actual resources caused by identification synchronization deviation, and if it is determined to perform, performs identification evidence storage and analysis based on the received analysis results, determines whether to trigger identification analysis optimization according to the identification evidence storage and analysis results, and if it is determined not to perform, performs the incremental operation of the internal queue processing rate, which helps to realize efficient flow of identification processing tasks, quickly digest the identification tasks accumulated due to failed verification, avoid synchronization lag accumulation, ensure smoothness of the identification management process closed loop, and further improve the identification synchronization accuracy of cross-domain multi-modal technology resources in the update and derived form generation process, and solve the problem of low identification synchronization accuracy of cross-domain multi-modal technology resources in the update and derived form generation process in the prior art.

[0056] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A cross-domain multi-modal technology resource identification life cycle management system, characterized in that, The application relates to a multi-modal scientific resource management system and a multi-modal scientific resource management method. The resource update management module is used for monitoring the update situation of the multi-modal scientific resource in the update and derivative form generation process of the cross-domain multi-modal scientific resource, evaluating the multi-modal scientific resource update delay situation, and transmitting the corresponding monitoring result to the capture and synchronization management module after monitoring. The capture and synchronization management module is used for capturing and synchronizing the multi-modal scientific resource identification based on the received monitoring result, evaluating the multi-modal scientific resource identification capture and synchronization qualification, judging whether to perform identification storage and analysis based on the analysis result, reflecting the storage qualification of the multi-modal scientific resource identification in the blockchain storage process, transmitting the corresponding analysis result to the storage and analysis management module if the judgment is to perform, and executing the incremental operation of the internal queue processing rate to avoid synchronization lag accumulation if the judgment is not to perform. The storage and analysis management module is used for performing identification storage and analysis based on the received analysis result, judging whether to trigger identification analysis optimization according to the identification storage and analysis result, and accelerating the identification update chain. The monitoring of the multi-modal scientific resource update situation comprises the following steps: 2.The cross-domain multi-modal scientific and technological resource identification life cycle management system according to claim 1, characterized in that, The update request sending time of the obtained multi-modal scientific resource and the time when the corresponding update signal is captured by the system are quantitatively processed to output the multi-modal scientific resource update interference value for quantifying the multi-modal scientific resource update delay situation. According to the multi-modal scientific resource update interference value, whether the identification capture and synchronization process is triggered is judged. Specifically, the multi-modal scientific resource update interference value is substituted into the preset resource update interference degree table. If the output preset update interference degree data is within the qualified range of the preset update interference degree, the obtained multi-modal scientific resource identification is subjected to identification capture and synchronization analysis. Otherwise, a feedback prompt for reacquiring the multi-modal scientific resource is sent to the preset personnel. The identification capture and synchronization analysis comprises one-round capture verification for evaluating the multi-modal scientific resource identification capture situation and two-round synchronization verification for evaluating the multi-modal scientific resource identification synchronization situation. 3.The cross-domain multi-modal scientific resource identification life cycle management system of claim 2, wherein, The specific process of the one-round capture verification is as follows: The actual update times of the multi-modal scientific resource are quantitatively processed to obtain one-round capture verification quantitative values for quantifying the multi-modal scientific resource identification capture accuracy. Based on the one-round capture verification quantitative value, whether the two-round synchronization verification is triggered is judged. Specifically, if the one-round capture verification quantitative value is greater than the preset one-round capture verification quantitative value, the two-round synchronization verification is triggered. Otherwise, the corresponding one-round capture verification quantitative value is marked as a to-be-optimized capture verification quantitative value, the multi-modal scientific resource identification is fed back to the preset personnel in the preset time period of the present multi-modal scientific resource update monitoring, and the capture verification management optimization is performed in the preset time period of the next adjacent multi-modal scientific resource update monitoring to ensure the synchronization of the identification and the resource state. The specific process of the capture verification management optimization is as follows: 4.The cross-domain multi-modal scientific resource identification life cycle management system of claim 3, wherein, ​ An optimization level judgment of the capture verification management optimization is performed based on the to-be-optimized capture verification quantitative value and the preset to-be-optimized capture verification value: When the to-be-optimized capture verification quantitative value is greater than the preset to-be-optimized capture verification value, the corresponding to-be-optimized capture verification quantitative value is marked as a first-level capture verification quantitative value, and vice versa, the corresponding to-be-optimized capture verification quantitative value is marked as a second-level capture verification quantitative value; When the first-level capture verification quantitative value is monitored, a first-level capture verification correlation analysis is triggered, and the analysis process is as follows: the first-level capture verification quantitative value and the query request number of the multi-modal scientific resource identifier are substituted into a preset first-level polling frequency correlation comparison list, the corresponding preset first-level polling frequency optimization degree value is queried, and the corresponding amplitude is taken as an adjustment step, the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier; When the second-level capture verification quantitative value is monitored, a second-level capture verification correlation analysis is triggered, and the analysis process is as follows: the second-level capture verification quantitative value and the query request number of the multi-modal scientific resource identifier are substituted into a preset second-level polling frequency correlation comparison list, the corresponding preset second-level polling frequency optimization degree value is queried, and the corresponding amplitude is taken as an adjustment step, the polling frequency of the multi-modal scientific resource identifier is gradually increased on the basis of the initial polling frequency of the multi-modal scientific resource identifier; The first-level capture verification correlation analysis and the second-level capture verification correlation analysis further include: after the polling frequency of the multi-modal scientific resource identifier is increased once, if the re-acquired one-round capture verification quantitative value is greater than the preset one-round capture verification quantitative value, a two-round synchronous verification is started, if it is monitored that the polling frequency reaches the maximum value of the corresponding preset range, the one-round capture verification quantitative value is still not greater than the preset one-round capture verification quantitative value, and a capture verification management optimization warning prompt is sent. 5.The cross-domain multi-modal scientific resource identification life cycle management system of claim 4, wherein, The specific process of the two-round synchronous verification is as follows: Based on the time when the acquired metadata bound to the multi-modal scientific resource identifier is completed and the time when the metadata is written into the distributed registration center, quantitative processing is performed to obtain a two-round synchronous verification quantitative value representing the different step degree of the multi-modal scientific resource identifier; Based on the two-round synchronous verification quantitative value, a judgment is performed: if the two-round synchronous verification quantitative value is not greater than a preset two-round synchronous verification quantitative value, the corresponding result is marked as being subjected to identifier storage and analysis, and an identifier storage and analysis process is started, otherwise, the corresponding result is marked as not being subjected to identifier storage and analysis, the multi-modal scientific resource identifier acquired in the preset time period corresponding to the present multi-modal scientific resource update monitoring is fed back to preset personnel, and in the next adjacent multi-modal scientific resource update monitoring corresponding to the preset time period, the amplitude corresponding to the preset queue processing rate adjustment value of the multi-modal scientific resource identifier is taken as an adjustment step, and the initial queue processing rate of the multi-modal scientific resource identifier is used as a basis to perform an incremental operation on the internal queue processing rate; The preset queue processing rate adjustment value is obtained by inputting the two-round synchronous verification quantitative value and the network capacity corresponding to the multi-modal scientific resource identifier into a preset synchronous verification correlation comparison list. The value synchronization verification of the two-round synchronization verification quantization value is triggered once every time the increment operation of the internal queue processing rate is performed, that is, when the reacquired two-round synchronization verification quantization value is not greater than the preset two-round synchronization verification quantization value, the identification storage and analysis are started; The value synchronization verification further includes: if the internal queue processing rate increases to the maximum value of the corresponding preset range and the two-round synchronization verification quantization value is still greater than the preset two-round synchronization verification quantization value, a two-round synchronization verification alarm prompt is sent. 6.The cross-domain multi-modal technology resource identification life cycle management system of claim 5, wherein, The specific process of the identification storage and analysis is as follows: Perform storage qualification determination: input the obtained storage qualification determination value into a preset storage qualification degree related list, and output a preset storage qualification degree score; The storage qualification determination value is used to reflect the storage qualification degree in the process of blockchain storage based on multi-modal technology resource identification; If the preset storage qualification degree score is within the pre-set storage qualification range, the corresponding blockchain node consensus verification data is marked as qualified blockchain node consensus verification data, and identification analysis accuracy analysis is started, otherwise an identification analysis accuracy analysis start failure prompt is sent.

7. The cross-domain multi-modal technology resource identification life cycle management system according to claim 6, characterized in that, The specific process of the identification analysis accuracy analysis is as follows: Obtain an identification analysis value for reflecting the analysis accuracy degree when analyzing based on qualified blockchain node consensus verification data; If the identification analysis value is greater than the preset identification analysis value, the corresponding qualified blockchain node consensus verification data is archived, otherwise the qualified blockchain node consensus verification data obtained within the preset time period corresponding to the current identification storage and analysis is fed back to the preset personnel, and identification analysis optimization is triggered within the next adjacent preset time period corresponding to the identification storage and analysis; The specific process of triggering identification analysis optimization is as follows: Combine the identification analysis value and the cache request time length parameter of the multi-modal technology resource identification, and substitute it into the preset cache window related list to output a preset cache window adjustment value; Perform a cache window decrement operation of the blockchain storage based on the preset cache window adjustment value; The cache window decrement operation means that the adjustment step is the amplitude corresponding to the preset cache window adjustment value, and the cache window is decremented step by step based on the primary cache window of the blockchain storage, and after each decrement, if the reacquired identification analysis value is greater than the preset identification analysis value, an on-chain identification deviation analysis is started; If the cache window of the blockchain storage reaches the minimum cache window during the execution of the cache window decrement operation, and the identification analysis value is still not greater than the preset identification analysis value, an identification analysis warning prompt is sent. 8.The cross-domain multi-modal technology resource identification life cycle management system of claim 7, wherein, The specific process of the on-chain identification deviation analysis is as follows: Mark the identification analysis value obtained after triggering the identification analysis optimization as an optimized identification analysis value; Based on the optimized identification analysis value and the preset optimized identification analysis value, the deviation degree quantization is carried out to output an identification analysis deviation representation value; Input the identification analysis deviation representation value into a preset analysis deviation level related table to output an identification analysis deviation degree level value; If the identification analysis deviation degree level value is not greater than the preset identification analysis deviation degree level value, a first-level identification analysis deviation prompt is sent, and identification analysis improvement optimization is started in the next adjacent upper chain identification deviation analysis corresponding preset time period; otherwise, a second-level identification analysis deviation prompt is sent, and the corresponding block chain node consensus verification data is archived; The identification analysis improvement optimization is used to ensure that the most time-efficient resource address and metadata are returned to the user. 9.The cross-domain multi-modal technology resource identification life cycle management system of claim 8, wherein, The specific process of the identification analysis improvement optimization is as follows: Within the preset range corresponding to the analysis result cache time, the identification analysis deviation degree level value and the access frequency of the multi-modal scientific resource identification are input into the preset cache time reading table to obtain the amplitude corresponding to the output preset cache time adjustment value, which is used as the adjustment step, and on the basis of the initial analysis result cache time of the multi-modal scientific resource identification, the decrement operation of the analysis result cache time is triggered; After each execution of the decrement operation of the analysis result cache time, if the newly obtained identification analysis deviation degree level value is greater than the preset identification analysis deviation degree level value, the corresponding block chain node consensus verification data is archived; When the analysis result cache time of the modal scientific resource identification is reduced to the preset minimum analysis result cache time, if the identification analysis deviation degree level value is still not greater than the preset identification analysis deviation degree level value, an identification analysis improvement optimization warning prompt is sent. 10.The cross-domain multi-modal technology resource identification life cycle management system of claim 6, wherein, The specific process of the identification analysis accuracy analysis is as follows: An identification analysis model is obtained, which is used to reflect the analysis accuracy degree when the qualified block chain node consensus verification data is analyzed under the condition of effective decay over time; Based on the value output by the identification analysis model, it is judged: if the value output by the identification analysis model is within the preset qualified analysis range, the corresponding qualified block chain node consensus verification data is archived; otherwise, an identification analysis warning prompt is sent.

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