CN113487443A - Agricultural data credible circulation platform based on data model - Google Patents
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Abstract
The invention relates to the technical field of agricultural digitization, in particular to an agricultural data credible circulation platform based on a data model, which comprises a plurality of data stations which are communicated with each other, wherein the data stations are respectively connected with agricultural participants, the agricultural participants access agricultural data of the agricultural participants into the data stations, the data stations encrypt, store and verify the agricultural data, data demand parties of the agricultural participants formulate the data model, submit the data model to corresponding data stations for execution to obtain model data, and the model data is associated with agricultural participant identifications, data model identifications and standard time and then serve as credible circulation data circulation. The substantial effects of the invention are as follows: the agricultural data of the agricultural participants are stored in the data station in an encrypted mode, circulation is carried out after data model conversion, isolation is achieved between the agricultural data and the outside, privacy and safety of original agricultural data are guaranteed, the data models are various in types, diversified data requirements are met, and development of agricultural informatization is promoted.
Description
Technical Field
The invention relates to the technical field of agricultural digitization, in particular to an agricultural data credible circulation platform based on a data model.
Background
The digital construction of the rural area is relatively backward, the information is not smooth, and the management is weak. And thus agricultural data is generally not highly reliable. Agriculture is a large and complex industry with diverse and large numbers of participants. For agricultural participants in different geographical areas, different crop types and different roles, the generated data and the required data are complex and various, and a large amount of information islands are formed. The poor circulation of agricultural data seriously hinders the cooperation among agricultural related participants and limits the development of agricultural productivity. Agriculture is an important industry in China and is related to civil life and social stability. Therefore, research on a technical scheme which can enable agricultural data to flow reliably and smoothly is urgently needed.
Chinese patent CN106934526A, published as 2017, 7.7.discloses an agricultural production information management system, which includes: a unit information management module for managing the basic information of the user, a base management module for managing the basic information of the base, a label management module for consulting the distribution and activation conditions of the user labels and carrying out statistical analysis, a data analysis module for looking up the records of the two-dimension code labels accessed by the consumers and carrying out statistical analysis on the access records, a farming management module for managing the purchasing farming information of the user, a farming operation management module for managing the farming operation flow information of the user, a quality management module for managing the agricultural product production system information of the user, a processing and packaging module for managing the agricultural product processing and packaging information of the user, a sales and circulation management module for managing the agricultural product logistics and sales information of the user, and the like, effectively help enterprises, specialized farmers' cooperatives and growers to record all information of agricultural products, and realize the electronization and comprehensive management of agricultural production information files. Although the technical scheme recorded in the method electronizes part of agricultural data, thereby facilitating the circulation of the agricultural data to a certain extent, the method cannot guarantee the safety and privacy of the data circulation process, cannot meet diversified data requirements, and is still insufficient for solving the problem of insufficient agricultural data circulation degree.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the problem of the lack of a technical scheme for credible circulation of agricultural data at present. The agricultural data credible circulation platform based on the data model can meet diversified data requirements and is convenient to circulate data under the condition that the agricultural data privacy is guaranteed.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: the agricultural data credible circulation platform based on the data model comprises a plurality of data stations which are communicated with each other, wherein the data stations are respectively connected with agricultural participants, the agricultural participants access agricultural data of the agricultural participants into the data stations, the data stations encrypt, store and verify the agricultural data, data demand parties of the agricultural participants formulate data models, submit the data models to corresponding data stations for execution, obtain model data, and the model data are communicated as credible circulation data after being associated with agricultural participant identifications, data model identifications and standard time.
Preferably, the data model is established by the following method: according to the types of the agricultural participants, the data circulation requirements among the agricultural participants are exhausted; acquiring data and a data format of a data source party and acquiring data and a data format required by a data demand party; the data model is a model for converting the data and the data format of the data source side into the data and the data format required by the data demand side.
Preferably, the data station makes desensitization data of agricultural data of a plurality of agricultural participants, a data demand party in the agricultural participants formulates a data model according to self data demand and the desensitization data, the data model is a mapping and calculation combination for converting desensitization data and formats into required data and formats, the data model is submitted to any one data station, the data station substitutes the desensitization data into the data model, if the data and the formats required by the data demand party are obtained, the data model is given with a unique identification and associated with an abstract, the data model is put on line, according to the agricultural participants appointed by the data demand party, the data station sends the data model which is put on line to other data stations where the appointed agricultural participants are located, the data stations call out the agricultural data required by the data model of the appointed agricultural participants and substitutes the data model, and obtaining model data, associating the model data with the agricultural participant identification, the data model identification and the standard time, and circulating as credible data.
Preferably, when the input data required by the data model is located in a plurality of data stations, the plurality of data stations construct a secure multiparty computation, and the output of the data model, namely model data, is obtained.
Preferably, the data model is associated with an authority identifier, the authority identifier defines an agricultural participant list capable of obtaining the output of the data model, when the data station provides model data, the data station verifies whether an agricultural participant requesting to obtain the model data meets the authority identifier, if so, the data station provides the model data to the agricultural participant, otherwise, the data station refuses to provide the model data.
Preferably, each time the data station executes the data model, an execution record is established, the called agricultural data is packaged and a hash value is extracted, the execution record comprises an execution time, an identification of the data model, a designated agricultural participant, the hash value of the called agricultural data and the hash value of the model data, and the newly added execution record is packaged and stored periodically.
The substantial effects of the invention are as follows: agricultural data of an agricultural participant are encrypted, stored and certified in a data station, and are circulated after being converted through a data model, so that the agricultural data are isolated from the outside, the privacy and the safety of original agricultural data are guaranteed, and the agricultural data cannot be leaked; the data models are various in types and are just matched with diversified data requirements; the data model is set by the data demand party, and after the data model is on line by the data station, the data demand party designates the data source party, so that the data representation of the data source party under the data model can be obtained under the condition that the original data of the data source party is unknown, and the cooperation service can be developed; the data in the data station is stored through the block chain, and the execution of the data model is recorded and stored, so that the credibility of the data is ensured; therefore, the agricultural data credible circulation platform which can meet diversified data requirements and effectively protect the safety and privacy of agricultural data is provided, and the development of agricultural informatization is promoted.
Drawings
Fig. 1 is a schematic structural diagram of an agricultural data trusted circulation platform according to an embodiment.
Fig. 2 is a schematic diagram illustrating a general data model building method according to an embodiment.
FIG. 3 is a schematic diagram illustrating an implementation of a data model submitted by an agricultural product acquirer in accordance with the second embodiment.
FIG. 4 is a schematic diagram of the implementation of a data model submitted by the agricultural regulatory agency according to the second embodiment.
Fig. 5 is an implementation diagram of a data model of a three-bank submission according to an embodiment.
Wherein: 10. the system comprises a data demand party, 20, a data station, 30, a data source party, 201, planting data, 202, a data model, 203, quality, 204, yield, 205, safe multi-party calculation, 206, total yield of a producing area, 207, real estate data, 208, movable estate data, 209, asset data, 210 and credit line.
Detailed Description
The following provides a more detailed description of the present invention, with reference to the accompanying drawings.
The first embodiment is as follows:
an agricultural data credible circulation platform based on a data model 202, please refer to fig. 1, and includes a plurality of data stations 20 which are mutually communicated, wherein the plurality of data stations 20 are respectively connected with agricultural participants, the agricultural participants access agricultural data of the agricultural participants to the data stations 20, the data stations 20 encrypt, store and verify the agricultural data, data demanders 10 of the agricultural participants formulate the data model 202, submit the data model 202 to corresponding data stations 20 for execution, obtain model data, and circulate as credible circulation data after associating the model data with identification of the agricultural participants, identification of the data model 202 and standard time.
The embodiment provides a general data model 202 establishing method, and specific data and data formats are nested according to the method, so that the mapping relation or the calculation relation among the data can be established. If a certain data from the data source 30 has a limited value, a mapping table between the limited value and the data required by the data demander 10 can be directly established. If the values of the crop planting mode include: open planting, cold-shed planting, warm-shed planting and glass greenhouse planting. The data required by the data demander 10 is the resistance of the farmer against low temperature disasters. The four values and the corresponding low-temperature disaster resistance can be directly graded, and the mapping relation is established. Namely, the outdoor planting and cold shed planting mapping low-temperature disaster resistance is weak, the warm shed planting mapping low-temperature disaster resistance is strong, and the glass greenhouse planting mapping low-temperature disaster resistance is strong. Namely, the specific planting mode of the peasant household can not be disclosed, and the agricultural disaster prevention department can know the resistance of the local peasant household to the low-temperature disaster.
Referring to FIG. 2, the data model 202 is built as follows: step A1) exhausting data circulation requirements among the agricultural participants according to the types of the agricultural participants; step A2) obtaining data and data format of the data source side 30; step A3) obtaining data and data format required by the data demander 10; step a 4) the data model 202 is a model for converting the data and data format of the data source 30 into the data and data format required by the data consumer 10.
The data station 20 makes desensitization data of agricultural data of a plurality of agricultural participants, a data demand party 10 in the agricultural participants prepares a data model 202 according to own data demand and contrasts the desensitization data, the data model 202 is a mapping and calculation combination for converting the desensitization data and a format into required data and a format, the data model 202 is submitted to any one data station 20, the data station 20 substitutes the desensitization data into the data model 202, if the data and the format required by the data demand party 10 are obtained, the data model 202 is given a unique identification and is associated with an abstract, the data model 202 is online, according to the agricultural participants appointed by the data demand party 10, the data station 20 sends the online data model 202 to other data stations 20 where the appointed agricultural participants are located, and the data station 20 calls the agricultural data required by the data model 202 of the appointed agricultural participants, and substituting the model data into the data model 202 to obtain model data, and associating the model data with the agricultural participant identification, the data model 202 identification and the standard time to be used as credible data for circulation. When the input data required by the data model 202 is located at multiple data stations 20, the multiple data stations 20 construct a secure multi-party computation 205, obtaining the output of the data model 202, i.e. the model data.
The data model 202 is associated with an authority identifier, the authority identifier defines a list of agricultural participants capable of obtaining the output of the data model 202, when the data station 20 provides model data, the data station verifies whether the agricultural participants requesting to obtain the model data meet the authority identifier, if so, the model data is provided to the agricultural participants, otherwise, the model data is refused to be provided. The data station 20 establishes an execution record every time the data model 202 is executed, packages the called agricultural data and extracts the hash value, the execution record comprises the execution time, the identification of the data model 202, the designated agricultural participant, the hash value of the called agricultural data and the hash value of the model data, and periodically packages and stores the newly added execution record.
The beneficial effect of this embodiment is: agricultural data of the agricultural participants are stored in the data station 20 in an encrypted mode and are certified, circulation is carried out after the agricultural data are converted through the data model 202, isolation is achieved between the agricultural data and the outside, privacy and safety of original agricultural data are guaranteed, and leakage of the agricultural data cannot occur. The data models 202 are of various types, just matching the diverse data requirements. The data model 202 is formulated by the data demander 10, and after the data station 20 puts the data model 202 on line, the data demander 10 designates the data source 30, so that the data representation of the data source 30 under the data model 202 can be obtained without knowing the original data of the data source 30, and the cooperation business can be developed. The data in the data station 20 is stored through the block chain, and the execution of the data model 202 is recorded and stored, so that the credibility of the data is ensured; therefore, the agricultural data credible circulation platform which can meet diversified data requirements and effectively protect the safety and privacy of agricultural data is provided, and the development of agricultural informatization is promoted.
Example two:
in the embodiment, the agricultural data credible circulation platform based on the data model 202 is used for pre-purchasing agricultural products, so that field purchasing of the agricultural products is realized. In the embodiment, a plurality of data stations 20 are established, the data stations 20 are distributed in the agricultural production area, each village maintains one data station 20, and farmers in the village access the planting data 201 of the farmers into the data station 20. Referring to fig. 3, if the farmer uses a planting greenhouse with a high degree of automation, the controller of the planting greenhouse is connected to the data station 20. If a common greenhouse or open air planting is adopted, sensors including an environment temperature and humidity sensor, an illumination sensor, a rainfall sensor, a wind speed sensor, an insect pest sensor and a growth sensor are installed, and the variety, planting area, geographical position, water and fertilizer, planting area and the farmer of the planted seeds need to be input into the data station 20 through a data input device. The data station 20 synchronizes the data of the meteorological department and obtains weather data. Some farming areas have gradually begun to build informatization systems from which seed data, meteorological monitoring data, and soil monitoring data can be obtained. The data model 202 in this embodiment is a model of crop growth for field crop quality 203 and yield 204 estimation. Agricultural scientific institutions have promulgated more growth models, i.e., growth models are known in the art. Such as: [1] senkymin, yangchengyu, Tatan, etc. the formation of biological yield 204304 of high-quality protein corn was predicted using a CERES corn growth model 302 [ J ]. proceedings of the southwest university of agriculture, 2001, 23(1):1-3. Jilin province spring corn yield 204304 potential and yield 204304 difference based on corn growth model 302 study [ D ]. jilin university, 2016. "provided growth model 302 predicting yield 204304. Other agricultural products, such as soybean, peanut, rice, wheat, etc., are also disclosed to predict the yield 204 and quality 203.
According to planting data 201 accessed by farmers, the growth model calculates crop quality 203 and yield 204 of each planting area of each farmer, and after associating the quality 203 and the yield 204 with the farmers and the planting areas, the quality and the yield are used as credible data to be circulated in the limited agricultural product trading market. The buyer of the agricultural product can search the farmers meeting the requirements of the quality 203 according to the information and the self requirements to bid and buy by registering an account number and purchasing authority to the agricultural product trading market.
Referring to fig. 4, a plurality of data stations 20 in the crop production area execute the data model 202, and obtain model data, namely quality 203 and yield 204, through multi-party safety calculation, to obtain total production 206 in the production area. The total yield 204 is circulated to the agricultural regulatory department. The agricultural supervision department can estimate the market supply condition according to the credible circulation information. If the yield 204 is too much, whether the purchase is achieved by the government can be decided as early as possible so as to stabilize the price of the agricultural products. If the yield 204 is low, the reserved agricultural products can be prepared to be delivered to the market as soon as possible according to the credible circulation data so as to prevent the market from being too short of supply and demand.
In this embodiment, although the planting data 201, such as the seed variety, the water and fertilizer condition, the temperature and humidity, the plant diseases and insect pests, used by each farmer does not leave the data station 20 all the time, is not disclosed to the outside, and has a strong privacy. But other agricultural participants obtain the required data, thereby facilitating the development of the business.
By adopting the agricultural data credible circulation platform, all the participants can obtain the essential data, the data of all the participants can keep privacy, and the flooding and real and false distinguishing of the data are avoided.
Example three:
with the development of agricultural production to mechanization, modernization and intellectualization, agricultural equipment used in the agricultural production process is more advanced and more abundant in function. But at the same time the capital investment in the earlier stages is also increased. Resulting in the need for some farmers to debit the bank.
In the conventional loan method, a farmer needs to fill in loan application data, and a bank needs to verify the asset condition recorded in the application data. If the verification is wrong, the bank may be put at risk. If a farmer wants to apply for a loan from multiple banks, the farmer needs to fill in the same application data for many times, which is very inefficient.
In the agricultural data trusted circulation platform based on the data model 202 in this embodiment, the user accesses the data station 20 for more than a preset time period, for example, 2 years. Over a2 year period, the user's planting data 201, the planting area per year, the yield 204, the quality 203, and the final profit are stored in the data station 20. When the farmer needs to apply for the loan, the bank is informed. The bank then sends the trust model it has created, i.e. the data model 202 used in this embodiment, to the data station 20 to which the farmer is connected. Referring to fig. 5, the data station 20 retrieves basic data of farmers including real estate, car production, forest production, crops in the current field, agricultural implements, livestock farming, farm land area, deposits, annual income and securities, wherein the real estate, car production, forest production, agricultural implements, livestock farming and farm land area are written into the data station 20 by the village committee organization and provide verification and guarantee, or provide relevant documents issued by the government or public certificate. The best mode is a block chain-based agricultural big data system established by villages and small towns, and the information is directly synchronized. However, since most agricultural regions have not established a big data system, the method still needs to be realized by means of traditional public confidence providing mode. The bank can also verify the property by itself, and after verification, the bank should submit the verification result to the data station 20 where the farmer is located with a named verification report. Therefore, other banks do not need to check, or the bank can determine the bank according to whether the assets are easy to change or not at the next loan, and the check is not carried out any more as appropriate.
After the credit model of the bank is executed by the data station 20, the credit amount 210 under the credit model is obtained. If the loan amount applied by the farmer is not higher than the credit line 210, the bank can directly inform the farmer of the business of signing and issuing the loan contract in the future, and the method is very efficient and simple. In the process, the bank does not know which real property data 207 or dynamic property data 208 the farmer specifically has, does not know the deposit and security asset data 209 condition of the farmer, only knows the asset data 209 condition of the farmer, and can obtain the credit line 210 under the rule set by the bank. The credit line 210 is a trusted circulation data.
Similarly, if a farmer applies for a loan from multiple banks at the same time, the credit limit that the farmer can obtain may be different in the credit model of the multiple banks. The farmer also selects the most favorable bank to carry out loan transaction.
In this embodiment, the farmer has successfully applied for a loan, and the bank has also released the fund. But during this process, the farmer's asset data 209, not leaving the data station 20, remains private to the bank. But the bank can be confident of the line of credit that the farmer's assets can give. The trust problem of both parties is solved, and the development of agriculture is promoted.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (6)
1. An agricultural data credible circulation platform based on a data model is characterized in that,
the agricultural data communication system comprises a plurality of data stations which are communicated with each other, wherein the data stations are respectively connected with agricultural participants, the agricultural participants access agricultural data of the data stations, the data stations encrypt and store the agricultural data and verify the agricultural data, data demand parties of the agricultural participants formulate data models, submit the data models to corresponding data stations for execution, model data are obtained, and the model data are associated with agricultural participant identifications, data model identifications and standard time and then serve as credible circulation data for circulation.
2. The data model-based agricultural data trusted circulation platform of claim 1,
the data model is established by the following method:
according to the types of the agricultural participants, the data circulation requirements among the agricultural participants are exhausted;
acquiring data and a data format of a data source party and acquiring data and a data format required by a data demand party;
the data model is a model for converting the data and the data format of the data source side into the data and the data format required by the data demand side.
3. The data model-based agricultural data trusted circulation platform of claim 1,
the data station makes desensitization data of agricultural data of a plurality of agricultural participants, a data demand party in the agricultural participants makes a data model according to data demand of the data demand party, the data model is a mapping and calculation combination for converting desensitization data and formats into required data and formats, the data model is submitted to any one data station, the data station substitutes the desensitization data into the data model, if the data and the formats required by the data demand party are obtained, the data model is given with a unique identification and associated with an abstract, then the data model is put on line, according to the agricultural participants appointed by the data demand party, the data station sends the data model which is put on line to other data stations where the agricultural appointed participants are located, the data stations call out the agricultural data required by the data model of the appointed agricultural participants and substitute the agricultural data model, and obtaining model data, associating the model data with the agricultural participant identification, the data model identification and the standard time, and circulating as credible data.
4. The data model-based agricultural data trusted circulation platform of claim 3,
when the input data required by the data model are located in a plurality of data stations, the data stations construct a safe multi-party calculation to obtain the output of the data model, namely model data.
5. The data model-based agricultural data trusted circulation platform according to any one of claims 1 to 4,
the data model is associated with authority identification, the authority identification limits an agricultural participant list capable of obtaining the output of the data model, when the data station provides model data, whether the agricultural participant requesting to obtain the model data accords with the authority identification is verified, if so, the model data is provided for the agricultural participant, otherwise, the model data is refused to be provided.
6. The data model-based agricultural data trusted circulation platform according to any one of claims 1 to 4,
and each time the data station executes the data model once, establishing an execution record, packaging the called agricultural data and extracting a hash value, wherein the execution record comprises an execution time, an identifier of the data model, a designated agricultural participant, the hash value of the called agricultural data and the hash value of the model data, and periodically packaging and storing the newly added execution record.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070150856A1 (en) * | 2005-12-22 | 2007-06-28 | Rightnow Technologies, Inc. | Elective data sharing between different implementations of a software product |
| CN107194822A (en) * | 2017-05-25 | 2017-09-22 | 河南嘉禾智慧农业科技有限公司 | A kind of agricultural data shared system and method based on block chain |
| CN107633181A (en) * | 2017-09-12 | 2018-01-26 | 复旦大学 | The data model and its operation system of data-oriented opening and shares |
| CN109729168A (en) * | 2018-12-31 | 2019-05-07 | 浙江成功软件开发有限公司 | A kind of data share exchange system and method based on block chain |
| US20200219172A1 (en) * | 2019-01-07 | 2020-07-09 | Masters Choice | Systems and methods for facilitating agricultural transactions |
| CN112347495A (en) * | 2020-11-15 | 2021-02-09 | 北京物资学院 | Trusted privacy intelligent service computing system and method based on block chain |
-
2021
- 2021-06-29 CN CN202110724882.6A patent/CN113487443B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070150856A1 (en) * | 2005-12-22 | 2007-06-28 | Rightnow Technologies, Inc. | Elective data sharing between different implementations of a software product |
| CN107194822A (en) * | 2017-05-25 | 2017-09-22 | 河南嘉禾智慧农业科技有限公司 | A kind of agricultural data shared system and method based on block chain |
| CN107633181A (en) * | 2017-09-12 | 2018-01-26 | 复旦大学 | The data model and its operation system of data-oriented opening and shares |
| CN109729168A (en) * | 2018-12-31 | 2019-05-07 | 浙江成功软件开发有限公司 | A kind of data share exchange system and method based on block chain |
| US20200219172A1 (en) * | 2019-01-07 | 2020-07-09 | Masters Choice | Systems and methods for facilitating agricultural transactions |
| CN112347495A (en) * | 2020-11-15 | 2021-02-09 | 北京物资学院 | Trusted privacy intelligent service computing system and method based on block chain |
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