CN111259080A - Scientific research big data closed-loop information management method - Google Patents
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Abstract
The invention belongs to the technical field of information management, and discloses a scientific research big data closed-loop information management method which comprises the steps of acquiring data information of scientific research equipment, analyzing and summarizing the data information, creating a scientific research database, and managing the scientific research database through a management program; constructing a block chain for the scientific research database, verifying or screening the information records in the blocks, and determining that the information records of the blocks reach consensus; and establishing a corresponding relation between the analysis result and the development decision suggestion, searching at least one piece of first development decision suggestion information corresponding to the analysis result in a scientific research database, and outputting the first development decision suggestion information. The invention establishes the scientific research information table through the SQL Server database, has simple operation, good combination continuity and integration of the information and simple connection method. The invention can realize the improvement of data management and analysis flexibility, has high efficiency and good accuracy of scientific research big data closed-loop information management, and provides policy guidance and suggestion for avoiding risks and providing policy for scientific research.
Description
Technical Field
The invention belongs to the technical field of information management, and particularly relates to a scientific research big data closed-loop information management method.
Background
Currently, the closest prior art: with the increasing popularity and rapid development of internet technology applications, people have been moving from the information technology age (IT) to the data technology age (DT), and people have been around the technological revolution of "big data", an "information age". The big data not only brings great challenges to the storage and management of data information, but also brings great values to human beings in data information mining and utilization. Big data technology is a process of extracting implicit, unknown and potentially useful information from data, and is recognized as a new field of great application prospect in database research. For scientific research information management workers, how to use scientific research data to discover important information therein is an important basis for improving scientific and technological management decision level, and a management service mode is continuously innovated, which is a problem worthy of thinking and exploration. However, the scientific research data management of the current scientific research units also has the problems of non-uniform system, ineffective data utilization, insufficient simplification of management specifications and inefficient supply.
In summary, the problems of the prior art are as follows: at present, scientific research data management of scientific research units has the problems of non-uniform system, ineffective data utilization, insufficient simplification of management specifications and inefficient supply.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a scientific research big data closed-loop information management method.
The invention is realized in this way, a scientific research big data closed-loop information management method, which comprises the following steps:
acquiring time sequence data information of scientific research electrical equipment, analyzing the scientific research time sequence data information and acquiring an analysis result; and summarizing the analysis result, and establishing a scientific research information table by using an SQL Server database.
Step two, selecting the scientific research information table created in the step one, and creating a scientific research database and a relation chart thereof and a scientific research information view; and designing a main form by using Visual Basic, and connecting the main form with the SQL Server database.
And step three, generating a management program corresponding to the scientific research database, and generating a management program corresponding to the subdata of the database in the process of spreading scientific research data.
Detecting the state information of the database and all subdata of the database through a management program; and managing the database and all the subdata of the database according to the state information of the database and all the subdata of the database.
And step five, constructing a block chain for the scientific research databases, wherein each block of the block chain comprises part of or one or more information records of the scientific research databases.
And step six, the block chain constructed in the step five is sent to one or more corresponding nodes, and verification or screening of information records in each block is obtained at each node.
And seventhly, when the calculation simulation data and the experimental data in the information record of the block are verified mutually, determining that the information record of the block achieves consensus.
And step eight, establishing a corresponding relation between the analysis result and the development decision suggestion by utilizing the information agreed in the step seven according to the analysis result obtained in the step one, and searching and outputting at least one piece of first development decision suggestion information corresponding to the analysis result in a scientific research database.
Further, in the first step, the method for analyzing the scientific research time series data information comprises:
acquiring time series data information including M or more pieces of third information in which first information on the work of the scientific research electrical equipment and second information indicating a time observation point of the first information are associated with each other, wherein M is a natural number of three or more;
calculating an absolute value of a time difference between the observation points using the second information included in each of N pieces of the third information included in the time-series data information, where N is a natural number of three or more, and generating a set of the calculated time differences as a first set;
calculating, for each group of the third information for which the absolute value of the time difference is calculated, an autocorrelation coefficient indicating a correlation between a value of the first information at a first time and a value of the first information at a second time when a predetermined time has elapsed since the first time, and generating a set of the calculated autocorrelation coefficients as a second set;
calculating an autocorrelation function representing a relationship between the set of time differences and the set of autocorrelation coefficients based on the first set and the second set;
analyzing the first information chronologically based on the autocorrelation function;
outputting fourth information on the analysis result;
further generating a third set of said time differences with duplicates deleted in said first set;
generating the second set, based on the third set, by using the set of autocorrelation coefficients corresponding to the third set as the second set;
and calculating the autocorrelation function based on the third set and the second set.
Further, in the first step, the method for creating the scientific research information table by using the SQL Server database comprises the following steps:
aiming at the condition that an SQL Server database is connected with a remote data source to be connected through a link Server, determining parameters required by the SQL Server database to be connected with the remote data source through the link Server, and endowing each required parameter with a corresponding parameter value;
creating a storage process of a link Server for realizing the connection between the SQL Server database and the remote data source to be connected, wherein the link Server comprises a plurality of variables corresponding to the required parameters, calling the parameter values and assigning the parameter values to the corresponding variables in the variables respectively, so as to realize the connection between the SQL Server database and the remote data source to be connected;
setting a plurality of characteristic parameters for realizing integration of a remote data source into an SQL Server database, and setting a corresponding numerical value for each characteristic parameter and corresponding to the numerical value, wherein the numerical value is a characteristic parameter value of the characteristic parameter;
and executing an integrated command, wherein the executed command comprises characteristic variables corresponding to the characteristic parameters, calling the characteristic parameter values and endowing one of the characteristic parameters to the corresponding characteristic variable, and executing integration according to the integrated command, so that the integration of the remote data source to the SQL Server database is realized.
Further, in the second step, the scientific research database comprises specific material physical property data, test data and application data, instrument parameters, use and maintenance data and design and development data of instruments and equipment, and skills, various experiences and experience data of scientific researchers;
by subdividing and integrating the scientific research database, the interaction and relationship among the instrument and equipment database, the research and test database, the material and the preparation database thereof are mapped, and the database is analyzed and sorted, so that the effective supply capacity in the products and skills provided by the user can be screened, and the internally correlated self-consistent matching database is formed; when a user puts forward specific instrument and equipment, test or material requirements, keywords are matched through a neural network algorithm, and detailed descriptions of suppliers capable of providing services instantly and corresponding services are presented for the user.
Further, in step two, the method for connecting the main form with the SQL Server database comprises:
acquiring information of a process to be connected with a database;
according to the information of the process, determining the position information of a database connection set in a database connection set array where required database connection is located, wherein the database connection set array comprises at least two database connection sets; and allocating the free database connection to the process.
Further, in step four, the step of managing the source data and all the sub-data of the source data according to the state information of the source data and all the sub-data of the source data specifically includes:
when detecting that the source data is deleted, applying for new data to network side equipment as the database; if the application of new data to the network side equipment as the database fails, performing data security protection processing on all subdata of the database;
if the management program corresponding to any subdata cannot communicate with the management program corresponding to the source data and cannot communicate with network side equipment, performing data security protection processing on any subdata;
judging whether the quantity of all subdata of the source data reaches a preset value or not;
when the number of all subdata of the source data is judged to reach the preset value, early warning information is sent to network side equipment, so that the network side equipment feeds back whether to perform data safety protection processing or not;
and if receiving an instruction for performing data security protection processing sent by the network side equipment, performing data security protection processing on all subdata of the source data.
Further, in step six, the method for obtaining verification or screening of information records in each of the blocks includes:
acquiring professional audit of one or more auditors of each node on authenticity and value of the information records in each block in sequence, and realizing verification or screening of the information records in each block; or,
and sequentially calculating the value of the information records in each block according to a preset resource value evaluation logic, and verifying or screening the information records in each block according to the value of the information records in each block obtained by calculation.
Further, in step eight, a plurality of pieces of development decision suggestion information are stored in the local database, the development decision suggestion information includes content information of development decision suggestions and sequence numbers of the content information of the development decision suggestions, and the first development decision suggestion information is a part of the development decision suggestion information;
judging whether the quantity of the first development decision suggestion information is less than the quantity of second development decision suggestion information stored in advance; the second development decision suggestion information is obtained by searching development decision suggestion information stored in the local database according to previous target scientific research data, and is a part of the development decision suggestion information;
if so, judging whether the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same one by one, and acquiring the quantity that the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same;
and determining whether to alarm or not according to the quantity and the quantity of the second development decision suggestion information.
Another object of the present invention is to provide a computer program product stored on a computer readable medium, which includes a computer readable program for providing a user input interface to implement the method for managing closed-loop scientific big data when the computer program product is executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for managing closed-loop scientific research big data information.
In summary, the advantages and positive effects of the invention are: the invention establishes the scientific research information table through the SQL Server database, has simple operation and better combination consistency of information; the SQL Server is good in integration, the visual basic main window is connected with the SQL Server database, the connection method is simple, data management and analysis flexibility can be improved, and the efficiency and accuracy of closed-loop information management of scientific research big data are high.
The invention can manage the data through the management program which is interdependent with the data, thereby effectively restraining the malicious transmission of the data through the network, simultaneously preventing other people from maliciously copying the data information and protecting the confidentiality of scientific research data. According to the method, scientific research data are stored in a distributed mode by adopting a block chain technology, and a distributed consensus mechanism of the block chain technology is fully utilized, so that the scientific research data records in a specific field can obtain professional audit of each node. Aiming at the problem of difficult data verification, each node executes an auditing verification mechanism, the authenticity of the uplink data is ensured to the greatest extent, and professional evaluation and selection are made on the data value to form the most valuable data chain.
According to the scientific research big data analysis result and the decision suggestion, the management decision adjustment scheme is made in time, relevant scientific and technological actions are implemented, and the healthy and sustainable development of the whole unit scientific research is promoted. The invention comprehensively improves the scientific research innovation management capability through an informatization means, realizes the promotion of information resource sharing through data service innovation under the background of big data, and achieves the aims of effective utilization of data, simplified management specification and high-efficiency supply; meanwhile, scientific research data is used as a basis, scientific research results are analyzed and mined, innovative service modes are explored, risks are avoided for scientific research, policy guidance and suggestions are provided, and stable and efficient operation of a management system is guaranteed.
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Fig. 1 is a flowchart of a scientific research big data closed-loop information management method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a scientific research big data closed-loop information management method, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the scientific research big data closed-loop information management method provided by the embodiment of the present invention includes the following steps:
s101, acquiring time sequence data information of scientific research electrical equipment, analyzing the scientific research time sequence data information, and acquiring an analysis result; and summarizing the analysis result, and establishing a scientific research information table by using an SQL Server database.
S102, selecting the scientific research information table created in S101, and creating a scientific research database and a relation chart thereof and a scientific research information view; and designing a main form by using Visual Basic, and connecting the main form with the SQL Server database.
S103, generating a management program corresponding to the scientific research database, and generating a management program corresponding to the subdata of the database in the process of spreading scientific research data.
S104, detecting the state information of the database and all subdata of the database through a management program; and managing the database and all the subdata of the database according to the state information of the database and all the subdata of the database.
And S105, constructing a block chain by the scientific research databases, wherein each block of the block chain comprises part of or information records of one or more scientific research databases.
S106, the block chain constructed in the S105 is sent to one or more corresponding nodes, and verification or screening of information records in each block is obtained at each node.
S107, when the calculation simulation data and the experimental data in the information recording of the block are mutually verified, determining that the information recording of the block achieves consensus.
And S108, establishing a corresponding relation between the analysis result and the development decision suggestion by utilizing the information agreed in S107 according to the analysis result obtained in S101, and searching and outputting at least one piece of first development decision suggestion information corresponding to the analysis result in a scientific research database.
In S101 provided by the embodiment of the present invention, the method for analyzing the scientific research timing data information includes:
acquiring time series data information including M or more pieces of third information in which first information on the work of the scientific research electrical equipment and second information indicating a time observation point of the first information are associated with each other, wherein M is a natural number of three or more;
calculating an absolute value of a time difference between the observation points using the second information included in each of N pieces of the third information included in the time-series data information, where N is a natural number of three or more, and generating a set of the calculated time differences as a first set;
calculating, for each group of the third information for which the absolute value of the time difference is calculated, an autocorrelation coefficient indicating a correlation between a value of the first information at a first time and a value of the first information at a second time when a predetermined time has elapsed since the first time, and generating a set of the calculated autocorrelation coefficients as a second set;
calculating an autocorrelation function representing a relationship between the set of time differences and the set of autocorrelation coefficients based on the first set and the second set;
analyzing the first information chronologically based on the autocorrelation function;
outputting fourth information on the analysis result;
further generating a third set of said time differences with duplicates deleted in said first set;
generating the second set, based on the third set, by using the set of autocorrelation coefficients corresponding to the third set as the second set;
and calculating the autocorrelation function based on the third set and the second set.
In S101 provided by the embodiment of the present invention, a method for creating a scientific research information table using an SQL Server database includes:
aiming at the condition that an SQL Server database is connected with a remote data source to be connected through a link Server, determining parameters required by the SQL Server database to be connected with the remote data source through the link Server, and endowing each required parameter with a corresponding parameter value;
creating a storage process of a link Server for realizing the connection between the SQL Server database and the remote data source to be connected, wherein the link Server comprises a plurality of variables corresponding to the required parameters, calling the parameter values and assigning the parameter values to the corresponding variables in the variables respectively, so as to realize the connection between the SQL Server database and the remote data source to be connected;
setting a plurality of characteristic parameters for realizing integration of a remote data source into an SQL Server database, and setting a corresponding numerical value for each characteristic parameter and corresponding to the numerical value, wherein the numerical value is a characteristic parameter value of the characteristic parameter;
and executing an integrated command, wherein the executed command comprises characteristic variables corresponding to the characteristic parameters, calling the characteristic parameter values and endowing one of the characteristic parameters to the corresponding characteristic variable, and executing integration according to the integrated command, so that the integration of the remote data source to the SQL Server database is realized.
In S102 provided in the embodiment of the present invention, the scientific research database includes specific material physical property data, test data, and application data, instrument parameters, use and maintenance data, design and development data of instruments and equipment, and skills, various experiences, and experience data of scientific researchers;
by subdividing and integrating the scientific research database, the interaction and relationship among the instrument and equipment database, the research and test database, the material and the preparation database thereof are mapped, and the database is analyzed and sorted, so that the effective supply capacity in the products and skills provided by the user can be screened, and the internally correlated self-consistent matching database is formed; when a user puts forward specific instrument and equipment, test or material requirements, keywords are matched through a neural network algorithm, and detailed descriptions of suppliers capable of providing services instantly and corresponding services are presented for the user.
In S102 provided in the embodiment of the present invention, a method for connecting a main window to an SQL Server database includes:
acquiring information of a process to be connected with a database;
according to the information of the process, determining the position information of a database connection set in a database connection set array where required database connection is located, wherein the database connection set array comprises at least two database connection sets; and allocating the free database connection to the process.
In S104 provided in the embodiment of the present invention, the step of managing the source data and all the sub-data of the source data according to the state information of the source data and all the sub-data of the source data specifically includes:
when detecting that the source data is deleted, applying for new data to network side equipment as the database; if the application of new data to the network side equipment as the database fails, performing data security protection processing on all subdata of the database;
if the management program corresponding to any subdata cannot communicate with the management program corresponding to the source data and cannot communicate with network side equipment, performing data security protection processing on any subdata;
judging whether the quantity of all subdata of the source data reaches a preset value or not;
when the number of all subdata of the source data is judged to reach the preset value, early warning information is sent to network side equipment, so that the network side equipment feeds back whether to perform data safety protection processing or not;
and if receiving an instruction for performing data security protection processing sent by the network side equipment, performing data security protection processing on all subdata of the source data.
In S106 provided in the embodiment of the present invention, the method for obtaining verification or screening of information records in each block includes:
acquiring professional audit of one or more auditors of each node on authenticity and value of the information records in each block in sequence, and realizing verification or screening of the information records in each block; or,
and sequentially calculating the value of the information records in each block according to a preset resource value evaluation logic, and verifying or screening the information records in each block according to the value of the information records in each block obtained by calculation.
In S108 provided in the embodiment of the present invention, a plurality of pieces of development decision suggestion information are stored in a local database, where the development decision suggestion information includes content information of development decision suggestions and sequence numbers of the content information of the development decision suggestions, and the first development decision suggestion information is a part of the development decision suggestion information;
judging whether the quantity of the first development decision suggestion information is less than the quantity of second development decision suggestion information stored in advance; the second development decision suggestion information is obtained by searching development decision suggestion information stored in the local database according to previous target scientific research data, and is a part of the development decision suggestion information;
if so, judging whether the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same one by one, and acquiring the quantity that the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same;
and determining whether to alarm or not according to the quantity and the quantity of the second development decision suggestion information.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A closed-loop information management method for scientific research big data is characterized by comprising the following steps:
acquiring time sequence data information of scientific research electrical equipment, analyzing the scientific research time sequence data information and acquiring an analysis result; summarizing the analysis result, and establishing a scientific research information table by using an SQL Server database;
step two, selecting the scientific research information table created in the step one, and creating a scientific research database and a relation chart thereof and a scientific research information view; designing a main form by using visual basic, and connecting the main form with an SQL Server database;
generating a management program corresponding to the scientific research database, and generating a management program corresponding to the subdata of the database in the process of spreading scientific research data;
detecting the state information of the database and all subdata of the database through a management program; managing the database and all subdata of the database according to the state information of the database and all subdata of the database;
constructing a block chain for the scientific research databases, wherein each block of the block chain comprises part of or one or more information records of the scientific research databases;
step six, the block chain constructed in the step five is sent to one or more corresponding nodes, and verification or screening of information records in each block is obtained at each node;
step seven, when the calculation simulation data and the experimental data in the information record of the block are verified mutually, determining that the information record of the block achieves consensus;
and step eight, establishing a corresponding relation between the analysis result and the development decision suggestion by utilizing the information agreed in the step seven according to the analysis result obtained in the step one, and searching and outputting at least one piece of first development decision suggestion information corresponding to the analysis result in a scientific research database.
2. The scientific research big data closed-loop information management method according to claim 1, wherein in the first step, the method for analyzing the scientific research time series data information comprises the following steps:
acquiring time series data information including M or more pieces of third information in which first information on the work of the scientific research electrical equipment and second information indicating a time observation point of the first information are associated with each other, wherein M is a natural number of three or more;
calculating an absolute value of a time difference between the observation points using the second information included in each of N pieces of the third information included in the time-series data information, where N is a natural number of three or more, and generating a set of the calculated time differences as a first set;
calculating, for each group of the third information for which the absolute value of the time difference is calculated, an autocorrelation coefficient indicating a correlation between a value of the first information at a first time and a value of the first information at a second time when a predetermined time has elapsed since the first time, and generating a set of the calculated autocorrelation coefficients as a second set;
calculating an autocorrelation function representing a relationship between the set of time differences and the set of autocorrelation coefficients based on the first set and the second set;
analyzing the first information chronologically based on the autocorrelation function;
outputting fourth information on the analysis result;
further generating a third set of said time differences with duplicates deleted in said first set;
generating the second set, based on the third set, by using the set of autocorrelation coefficients corresponding to the third set as the second set;
and calculating the autocorrelation function based on the third set and the second set.
3. The closed-loop information management method for big scientific research data according to claim 1, wherein in the first step, the method for creating the scientific research information table by using the SQL Server database comprises the following steps:
aiming at the condition that an SQL Server database is connected with a remote data source to be connected through a link Server, determining parameters required by the SQL Server database to be connected with the remote data source through the link Server, and endowing each required parameter with a corresponding parameter value;
creating a storage process of a link Server for realizing the connection between the SQL Server database and the remote data source to be connected, wherein the link Server comprises a plurality of variables corresponding to the required parameters, calling the parameter values and assigning the parameter values to the corresponding variables in the variables respectively, so as to realize the connection between the SQL Server database and the remote data source to be connected;
setting a plurality of characteristic parameters for realizing integration of a remote data source into an SQL Server database, and setting a corresponding numerical value for each characteristic parameter and corresponding to the numerical value, wherein the numerical value is a characteristic parameter value of the characteristic parameter;
and executing an integrated command, wherein the executed command comprises characteristic variables corresponding to the characteristic parameters, calling the characteristic parameter values and endowing one of the characteristic parameters to the corresponding characteristic variable, and executing integration according to the integrated command, so that the integration of the remote data source to the SQL Server database is realized.
4. The closed-loop information management method for big scientific research data as claimed in claim 1, wherein in step two, the scientific research database contains physical property data, test data and application data of specific material, instrument parameters, use and maintenance data, design and development data of instruments and equipment, and skills, various experiences and experience data of scientific researchers;
by subdividing and integrating the scientific research database, the interaction and relationship among the instrument and equipment database, the research and test database, the material and the preparation database thereof are mapped, and the database is analyzed and sorted, so that the effective supply capacity in the products and skills provided by the user can be screened, and the internally correlated self-consistent matching database is formed; when a user puts forward specific instrument and equipment, test or material requirements, keywords are matched through a neural network algorithm, and detailed descriptions of suppliers capable of providing services instantly and corresponding services are presented for the user.
5. The closed-loop information management method for big scientific research data according to claim 1, wherein in the second step, the method for connecting the main form with the SQL Server database comprises the following steps:
acquiring information of a process to be connected with a database;
according to the information of the process, determining the position information of a database connection set in a database connection set array where required database connection is located, wherein the database connection set array comprises at least two database connection sets; and allocating the free database connection to the process.
6. The scientific research big data closed-loop information management method according to claim 1, wherein in step four, the step of managing the source data and all the sub-data of the source data according to the state information of the source data and all the sub-data of the source data specifically comprises:
when detecting that the source data is deleted, applying for new data to network side equipment as the database; if the application of new data to the network side equipment as the database fails, performing data security protection processing on all subdata of the database;
if the management program corresponding to any subdata cannot communicate with the management program corresponding to the source data and cannot communicate with network side equipment, performing data security protection processing on any subdata;
judging whether the quantity of all subdata of the source data reaches a preset value or not;
when the number of all subdata of the source data is judged to reach the preset value, early warning information is sent to network side equipment, so that the network side equipment feeds back whether to perform data safety protection processing or not;
and if receiving an instruction for performing data security protection processing sent by the network side equipment, performing data security protection processing on all subdata of the source data.
7. The closed-loop scientific research data information management method according to claim 1, wherein in step six, the method for obtaining verification or screening of information records in each block comprises:
acquiring professional audit of one or more auditors of each node on authenticity and value of the information records in each block in sequence, and realizing verification or screening of the information records in each block; or,
and sequentially calculating the value of the information records in each block according to a preset resource value evaluation logic, and verifying or screening the information records in each block according to the value of the information records in each block obtained by calculation.
8. The scientific research big data closed-loop information management method according to claim 1, wherein in step eight, a plurality of pieces of development decision suggestion information are stored in the local database, the development decision suggestion information includes content information of development decision suggestions and sequence numbers of the content information of the development decision suggestions, and the first development decision suggestion information is a part of the development decision suggestion information;
judging whether the quantity of the first development decision suggestion information is less than the quantity of second development decision suggestion information stored in advance; the second development decision suggestion information is obtained by searching development decision suggestion information stored in the local database according to previous target scientific research data, and is a part of the development decision suggestion information;
if so, judging whether the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same one by one, and acquiring the quantity that the serial numbers of the content information of the first development decision suggestion and the second development decision suggestion are the same;
and determining whether to alarm or not according to the quantity and the quantity of the second development decision suggestion information.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the scientific big data closed-loop information management method according to any one of claims 1 to 8 when executed on an electronic device.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method of closed-loop scientific big data information management according to any one of claims 1 to 8.
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