Urban resource data general survey processing method driven by block chain

Abstract

The invention discloses a block chain-driven urban resource data general survey processing method, and relates to the technical field of data processing, and the method comprises the steps: defining a multi-layer block chain based on the category of urban resource data, and the multi-layer block chain comprises a block mother chain and a multi-level block sub-chain; and calling urban resource historical data, and constructing a reference resource data block. And interacting a plurality of general survey data sources to obtain urban resource general survey data which comprises data category labels and node labels. And by taking the data category labels and the node labels as index constraints, establishing a mapping relationship between the census data and the multi-layer block chain, and constructing a census data mapping table. And finally, based on the mapping table, mapping the city resource census data to a chain, and generating on-chain city resource census data. Therefore, the technical effects of improving the data integration and management efficiency and improving the data accuracy and consistency are achieved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a blockchain-driven urban resource data census processing method. Background Art

[0002] Urban resource management is an important part of sustainable urban development, involving land, water resources, energy, public facilities and other aspects. The existing census data collection and processing process relies on traditional methods, which makes it difficult to achieve efficient data integration and real-time updates. At the same time, the currently introduced blockchain applications are difficult to cope with the complex urban resource data structure. There are technical problems such as difficulty in data integration, poor data accuracy and consistency. Summary of the invention

[0003] The present invention provides a blockchain-driven urban resource data census processing method to solve the technical problems of difficult data integration, poor data accuracy and consistency in the prior art, and achieve the technical effects of improving data integration and management efficiency and improving data accuracy and consistency.

[0004] The blockchain-driven urban resource data census processing method provided by the present invention includes:

[0005] Based on the data category of urban resource data, a multi-layer blockchain is defined, wherein the multi-layer blockchain includes a block parent chain and a multi-level block child chain.

[0006] The historical data of urban resources is called up, and a benchmark resource data block is constructed based on the multi-layer blockchain.

[0007] Multiple census data sources are interacted to obtain urban resource census data, wherein the urban resource census data is associated and stored with data category labels and data node labels.

[0008] Taking the data category label and the node label as index constraints, a mapping relationship between the urban resource census data and the multi-layer blockchain is established, and a census data mapping table is constructed based on the mapping relationship.

[0009] Based on the census data mapping table, the urban resource census data is mapped onto the chain to generate on-chain urban resource census data.

[0010] In a feasible implementation, a multi-layer blockchain is defined based on the data category of urban resource data, including:

[0011] Based on the census demand information, extract the census indicator set.

[0012] The census indicator set is structured with data category as the first division dimension to obtain a census indicator tree, wherein the census indicator tree has data category as a first-level leaf node and multiple census indicators as child nodes of the first-level leaf node.

[0013] According to the census indicator tree, the parent chain block structure of the block parent chain is defined.

[0014] In a feasible implementation, a multi-layer blockchain is defined based on the data category of urban resource data, and also includes:

[0015] Obtain a census data source library including multiple census entities in the target area.

[0016] A census data source graph network of the census data source library is constructed, wherein the census data source graph network includes multiple data source nodes corresponding to multiple census entities.

[0017] The census data source graph network is subjected to node screening based on data categories as extraction dimensions to obtain multiple classified simplified census data source graph networks of multiple data categories.

[0018] Based on the plurality of classified simplified census data source graph networks, a multi-level sub-chain block structure of multiple levels of the block sub-chains and multiple levels of the block sub-chains is defined.

[0019] The multi-layer blockchain is deployed by combining the parent chain block structure, the multi-level child chain block structure and the census data source graph network.

[0020] In a feasible implementation, multiple census data sources are interacted to obtain urban resource census data, including:

[0021] Analyze the survey task book of the target scenario and identify multiple target data categories.

[0022] Based on the multiple target data categories, multiple corresponding target simplified census data source graph networks are matched and obtained, and based on the multiple target simplified census data source graph networks, the target census subject set is extracted.

[0023] According to the target census subject set, a plurality of census data sources are activated to collect census data and obtain the urban resource census data.

[0024] In a feasible implementation, the census data source graph network is subjected to node screening based on data categories as extraction targets to obtain multiple classified simplified census data source graph networks of multiple data categories, and then further includes:

[0025] Traverse multiple classified simplified census data source graph networks and divide the census data sources into levels from top to bottom.

[0026] Based on the hierarchical division result and in combination with the preset minimum hierarchical threshold, the aggregation level of the plurality of block subchains is determined and output as an aggregation strategy.

[0027] In a feasible implementation, according to the target census subject set, activating a plurality of census data sources to collect census data and obtaining the urban resource census data also includes:

[0028] The original urban resource census data collected by the plurality of census data sources are obtained.

[0029] Based on the aggregation strategy, the original urban resource census data is fused from bottom to top with the data category label as the first aggregation factor and the data node label as the second aggregation factor.

[0030] The output data fusion result is the urban resource census data.

[0031] In a feasible implementation, the data category label and the node label are used as index constraints to establish a mapping relationship between the urban resource census data and the multi-layer blockchain, and a census data mapping table is constructed based on the mapping relationship, including:

[0032] Based on the data category label, the target block subchain of the urban resource census data is matched to obtain the subchain mapping relationship.

[0033] According to the plurality of the classifications, the census data source graph network is simplified, and the plurality of data source node clusters corresponding to the multi-level block sub-chains are extracted to obtain the node mapping relationship.

[0034] The census data mapping table is constructed by combining the sub-chain mapping relationship and the node mapping relationship.

[0035] In a feasible implementation, the parent chain block structure of the block parent chain is defined, and then it also includes: determining the parent chain node set of the block parent chain, and the parent chain node set includes multiple parent chain nodes selected based on the node authority information of multiple data source nodes in the census data source library.

[0036] The present invention discloses a blockchain-driven urban resource data census processing method, including: based on the data category of urban resource data, defining a multi-layer blockchain, wherein the multi-layer blockchain includes a block parent chain and a multi-level block sub-chain; calling urban resource historical data, and constructing a benchmark resource data block based on the multi-layer blockchain; interacting with multiple census data sources to obtain urban resource census data, wherein the urban resource census data is associated with and stored with data category labels and data node labels; using the data category labels and node labels as index constraints, establishing a mapping relationship between urban resource census data and multi-layer blockchains, and constructing a census data mapping table based on the mapping relationship; based on the census data mapping table, mapping the urban resource census data to the chain, and generating the urban resource census data on the chain. The blockchain-driven urban resource data census processing method disclosed by the present invention solves the technical problems of data integration difficulties, poor data accuracy and consistency, and achieves the technical effects of improving data integration and management efficiency, and improving data accuracy and consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Process 1 of the blockchain-driven urban resource data census processing method of the present invention

[0038] Figure 2 This is a schematic diagram of the process of constructing a census data mapping table in the blockchain-driven urban resource data census processing method of the present invention. DETAILED DESCRIPTION

[0039] The technical solution provided in the embodiments of the present invention is to solve the technical problems of data integration difficulties, poor data accuracy and consistency in the prior art. The overall idea adopted is as follows:

[0040] Firstly, based on the data category of urban resource data, a multi-layer blockchain is defined, which includes a block parent chain and a multi-level block sub-chain; then, the urban resource historical data is called to build a benchmark resource data block based on the multi-layer blockchain; then, multiple census data sources are interacted to obtain urban resource census data, wherein the data is associated with and stored with data category labels and data node labels; then, with the data category labels and node labels as index constraints, a mapping relationship between the urban resource census data and the multi-layer blockchain is established, and a census data mapping table is constructed based on the mapping relationship; then, based on the census data mapping table, the urban resource census data is mapped onto the chain to generate on-chain urban resource census data.

[0041] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0042] Embodiment 1

[0043] Figure 1 The flowchart of the blockchain-driven urban resource data census processing method of the present invention is as follows:

[0044] Based on the data category of urban resource data, a multi-layer blockchain is defined, wherein the multi-layer blockchain includes a block parent chain and a multi-level block child chain.

[0045] Specifically, the multi-layer blockchain is a blockchain architecture for urban resource data, including a block parent chain and multiple levels of block sub-chains. The block parent chain is the core of the entire multi-layer blockchain, which is used to record the status and data summary of all sub-chains, ensure the security of data interaction between different sub-chains, and determine the consensus mechanism and data integrity of the overall blockchain network. In other words, the block parent chain contains a more streamlined data structure and smaller data content. The multi-level block sub-chain is an independent blockchain built around a specific data category or function, and different levels of block sub-chains correspond to different types of urban resource data.

[0046] In some embodiments, based on the data category of the urban resource data, a multi-layer blockchain is defined, including:

[0047] Based on the census demand information, a census indicator set is extracted; with the data category as the first division dimension, the census indicator set is structured to obtain a census indicator tree, wherein the census indicator tree has the data category as the first-level leaf node and multiple census indicators as child nodes of the first-level leaf node; according to the census indicator tree, the parent chain block structure of the block parent chain is defined.

[0048] Specifically, first, collect information on urban census needs, including infrastructure, environment, transportation and other fields, and extract specific indicators related to the census to form a census indicator set; then, according to the characteristics of the census indicators, divide the census indicators into different data categories, and use the data category as the first-level leaf node to define child nodes of different categories. Each child node corresponds to a specific census indicator, forming a census indicator tree.

[0049] For example, for the infrastructure category, it includes the number of roads, the number of parks, the number of schools, the number of hospitals, the number of public transportation stations, etc. For the environment category, it includes the air quality index, the green coverage rate, the noise pollution level, etc.; for the traffic category, it includes the road congestion level, the frequency of public transportation operation, the traffic accident rate, etc.

[0050] Specifically, according to the census indicator tree, the parent chain block structure of the block parent chain is defined, including: data structure, that is, the fields contained in each block, such as block number, timestamp, census data summary (organized according to the census indicator tree), hash value of the previous block, hash value of the current block, block height, etc.; encryption method, used to protect data security, such as SHA-256, used to calculate the hash value of the block. Consensus mechanism, preferably, through Proof of Stake, Delegated Proof of Stake, Proof of Authority, to ensure that data is consistent in the blockchain network.

[0051] Furthermore, based on the data categories of urban resource data, a multi-layer blockchain is defined, which also includes:

[0052] Acquire a census data source library including multiple census subjects in the target area; construct a census data source graph network of the census data source library, wherein the census data source graph network includes multiple data source nodes corresponding to the multiple census subjects; perform node screening on the census data source graph network based on data category as the extraction dimension, and obtain multiple classified simplified census data source graph networks of multiple data categories; define multi-level block sub-chains and multi-level sub-chain block structures of multi-level block sub-chains based on the multiple classified simplified census data source graph networks; and deploy the multi-layer blockchain by combining the parent chain block structure, the multi-level sub-chain block structure and the census data source graph network.

[0053] Specifically, the census subject in the target area is identified, multiple census subjects in the target area are obtained, such as public service agencies, communities, enterprises, departments, etc., and the name, category, contact information, address and superior-subordinate relationship of each census subject are determined to form a complete census data source library. In other words, the census subject is the execution unit of the census task in the target area, and multiple census subjects can be in a superior-subordinate relationship.

[0054] Specifically, based on the census data source library, a census data source graph network is constructed. The census data source graph network consists of multiple data source nodes, each of which corresponds to a census subject. The direct relationship edges between data source nodes are based on the relationship between census subjects, such as data sharing, data dependency, and upper and lower hierarchical determination. The generated census data source graph network is used to intuitively reflect the subordinate relationship between multiple census subjects, that is, the data circulation relationship, and thus provide a basis for subsequent data processing and analysis.

[0055] Optionally, the weights of the relationship edges in the census data source graph network can be set based on factors such as the frequency of data circulation, data importance, and the number of indicator types of data circulation, to help better understand the strength of relationships between census subjects in subsequent analysis.

[0056] Specifically, each node in the census data source graph network is traversed, and the predefined data category to which each data source node belongs is determined based on the attribute information of the urban resource data involved. If the node belongs to a certain data category, it is retained. If the node does not belong to any predefined data category, it is marked as to be removed, thereby generating a more streamlined census data source graph network corresponding to each data category, and outputting it as multiple classified simplified census data source graph networks. In other words, each classified simplified census data source graph network only contains data source nodes and data source node relationships based on one data category, representing a specific data category. Through the above steps, the multiple classified simplified census data source graph networks formed can intuitively reflect the relationship between different data categories, which helps to improve the efficiency and effectiveness of subsequent sub-chain configuration.

[0057] Specifically, based on the principle of similar parent chain block structure of the above-mentioned construction block parent chain, the subchain block structure of the block subchain corresponding to the census data source graph network is defined according to the classification of each data category, and a block subchain is constructed to ensure the classification management and circulation of data and facilitate the independent operation of different categories of data. Exemplarily, the subchain block structure of the block subchain includes a block header (including metadata of the block, such as block ID, previous block hash, timestamp, etc.), a transaction list (recording all data operations performed in the block, such as data entry, update, deletion, etc.), and status information (indicating any relevant data of the block status to ensure data integrity).

[0058] Optionally, under each first-level blockchain subchain, more specific secondary blockchain subchains can be subdivided according to specific projects or regions. For example, the water resource subchain can be subdivided into "urban water supply", "rural water source", etc.

[0059] Furthermore, sub-chain links are established, that is, the block parent chain references all block sub-chains, to ensure that the parent chain can effectively manage the status of the sub-chains. At the same time, the status and audit information about data compliance are recorded to ensure that all data operations comply with preset rules. Smart contracts are deployed on the parent chain and sub-chains to automate data operations and circulation management, such as data entry, access control, compliance checks, etc., to ensure that all sub-chains can link with the parent chain and exchange data, ultimately forming a multi-layer blockchain.

[0060] The above-mentioned deployment method combining the parent chain block structure, the multi-level sub-chain block structure and the census data source graph network can build a flexible and efficient multi-layer blockchain, which will help provide an efficient and clear technical path for the processing and management of urban resource data.

[0061] In some implementations, the census data source graph network is subjected to node screening based on data categories as extraction targets to obtain multiple classified simplified census data source graph networks of multiple data categories, and then further comprising:

[0062] Traversing multiple classified simplified census data source graph networks, hierarchical division of the census data sources is performed from top to bottom; based on the hierarchical division results, combined with a preset minimum hierarchical threshold, the convergence levels of the multiple block subchains are determined, and the output is a convergence strategy.

[0063] Optionally, the relationship directions of the relationship edges in the census data source graph network are simplified based on multiple classifications, and multiple census data sources are divided into levels. For example, the direct superior of the current node is the parent node, the direct subordinate of the current node is the child node, and the node without a parent is the root node. Based on the above relationship, the depth of each node in the graph network can be defined, with the root node as depth 0, the first-level node as depth 1, and so on. Finally, the census data sources at each level are summarized to form a clear hierarchical structure.

[0064] Optionally, the minimum level threshold is a minimum level threshold (such as depth 1, depth 2, etc., corresponding to the zoning level of the target area) set according to the census needs and data management strategies of the target area, which is used to determine at which levels data is aggregated and integrate all relevant data at that level, thereby reducing the number of nodes that need to interact with the blockchain for data, reducing the burden on the blockchain network, and improving the efficiency of the above-mentioned multi-layer blockchain.

[0065] Optionally, different classifications of simplified census data source graph networks correspond to different minimum level thresholds, thereby ensuring that the data aggregation process is more consistent with the census characteristics of different data categories.

[0066] The historical data of urban resources is called up, and a benchmark resource data block is constructed based on the multi-layer blockchain.

[0067] Specifically, the historical data of urban resources is called, and the corresponding benchmark resource data blocks are constructed according to the architecture of the multi-layer blockchain. The data sources of historical data of urban resources include urban management departments, sensor networks, public service platforms, etc.

[0068] Optionally, after obtaining the historical data of urban resources, the historical data of urban resources is cleaned and standardized to ensure the consistency and accuracy of the data. Then, the processed historical data of urban resources is parsed, multiple block fields corresponding to the block structure are constructed, and the benchmark resource data block is generated. The above process is conducive to the standardization and consistency of the data, and provides a reliable basis for subsequent data processing and management.

[0069] Multiple census data sources are interacted to obtain urban resource census data, wherein the urban resource census data is associated and stored with data category labels and data node labels.

[0070] In some embodiments, multiple census data sources are interacted to obtain urban resource census data, including:

[0071] Parse the census task book of the target scenario and determine multiple target data categories; based on the multiple target data categories, match and obtain the corresponding multiple target simplified census data source graph networks, and extract the target census subject set based on the multiple target simplified census data source graph networks; based on the target census subject set, activate the multiple census data sources to collect census data and obtain the urban resource census data.

[0072] Specifically, first, parse the census task book of the target scenario, clarify the target, scope and purpose of the census, and then extract the resource categories that need to be census, such as water resources, land use, transportation facilities, etc., and output them as target data categories; then, based on the target data categories, call the corresponding target simplified census data source graph network, and extract the census subjects related to the census task, and store them as the target census subject set, which defines the specific objects for executing urban resource census data collection. Finally, according to the extracted target census subject set, start the relevant data source, conduct a census of urban resources, and obtain urban resource census data.

[0073] The above data acquisition path based on the clear target data category in the task book improves the quality and accuracy of data collection, while optimizing the efficiency of data collection.

[0074] In some implementations, activating a plurality of census data sources to collect census data and obtaining the urban resource census data according to the target census subject set further includes:

[0075] The original urban resource census data collected by the plurality of census data sources are obtained; based on the aggregation strategy, the original urban resource census data are fused from bottom to top with the data category label as the first aggregation factor and the data node label as the second aggregation factor; and the data fusion result is output as the urban resource census data.

[0076] Specifically, after obtaining the original urban resource census data from multiple target census subjects in the target census subject set, the original urban resource census data is fused based on the above-mentioned aggregation strategy, wherein the first aggregation factor is the data category label, which is used to preliminarily classify the original urban resource census data according to different categories of urban resources; the second aggregation factor is the data node label, which is used to determine the corresponding depth according to the data node labels of each data source for more detailed judgment.

[0077] Specifically, the original urban resource census data of the target census subject whose second aggregation factor is less than the aggregation level is aggregated from bottom to top to the corresponding parent node whose second aggregation factor is equal to the aggregation level, and data fusion is performed to solve the problems of redundancy, conflict and missing values, thereby improving data quality and reducing data volume. The data after fusion processing is the final urban resource census data.

[0078] Optionally, data fusion methods include statistics, summation, average, etc., depending on the data type and management requirements.

[0079] Through the above bottom-up data aggregation and fusion process, the consistency and accuracy of urban resource census data are ensured. The process of integrating data from multiple data sources also helps to reduce duplication of work and improve data processing efficiency.

[0080] Taking the data category label and the node label as index constraints, a mapping relationship between the urban resource census data and the multi-layer blockchain is established, and a census data mapping table is constructed based on the mapping relationship.

[0081] Specifically, the census data mapping table is used to define the mapping relationship between the urban resource census data and the multi-level block sub-chains in the multi-layer blockchain, thereby helping to improve the processing efficiency of subsequent urban resource census data.

[0082] In some embodiments, Figure 2 As shown, the data category label and the node label are used as index constraints to establish a mapping relationship between the urban resource census data and the multi-layer blockchain, and a census data mapping table is constructed based on the mapping relationship, including:

[0083] Based on the data category label, the target block subchain of the urban resource census data is matched to obtain the subchain mapping relationship; according to the multiple classifications, the census data source graph network is simplified, and multiple data source node clusters corresponding to the multi-level block subchains are extracted to obtain the node mapping relationship; the subchain mapping relationship and the node mapping relationship are combined to construct the census data mapping table.

[0084] Specifically, first, identify the specific data categories related to the urban resource census data, match the corresponding block subchains, and thus determine the mapping relationship between the data categories and the multi-level block subchains, and output them as subchain mapping relationships. In other words, the subchain mapping relationship is used to determine the block subchain to which the urban resource census data should be linked. Then, analyze the classified simplified census data source graph network, determine the relationship between the data source node and multiple block subchains, extract each node cluster, and form a node mapping relationship. In other words, the same data source node can be included in multiple classified simplified census data source graph networks, that is, one data source node can be used for the collection of data of multiple data categories. Finally, the obtained subchain mapping relationship is combined with the node mapping relationship to form a census data mapping table. The header of the census data mapping table includes the data category label, the corresponding block subchain, and the data source node. Each row in the table contains a subchain and data source node corresponding to a specific data category label.

[0085] By constructing a mapping table, we can clearly understand the correspondence between different data categories and blockchains, thereby providing a convenient data processing and access path, enhancing the systematic and logical nature of data processing, and improving response speed.

[0086] Based on the census data mapping table, the urban resource census data is mapped onto the chain to generate on-chain urban resource census data.

[0087] Specifically, according to the census data mapping table, the corresponding urban resource census data and its classification information are extracted, and the extracted data is formatted into a standard format that meets the requirements of the blockchain, including necessary metadata such as timestamp, data source, etc.; then, the formatted urban resource census data is encapsulated into a blockchain transaction data packet, and the previously deployed smart contract is called to send the data transaction to the blockchain network; then, confirm whether the transaction is successfully packaged into the block, generate a block hash, and verify the integrity and correctness of the urban resource census data on the chain to ensure data consistency; finally, generate a unique identifier (such as a transaction ID) for each piece of data successfully uploaded to the chain.

[0088] Through the above steps, urban resource census data can be processed efficiently and accurately, and on-chain data can be generated, thereby improving the security and reliability of the data.

[0089] In some implementations, the parent chain block structure of the block parent chain is defined, and then the method further includes: determining a parent chain node set of the block parent chain, wherein the parent chain node set includes multiple parent chain nodes selected based on node authority information of multiple data source nodes in the census data source library.

[0090] Specifically, based on the node authority information of multiple data source nodes in the census data source library, multiple data source nodes with higher authority levels are screened as multiple parent chain nodes, and output as a parent chain node set, where the parent chain node has the accounting power of the block parent chain. The parent chain node set constructed according to the above screening criteria helps to ensure that the multi-layer blockchain has good decentralization characteristics and data processing capabilities, improve the overall security of the blockchain, reduce the risk of data tampering, and provide support for subsequent data audits.

[0091] In summary, the blockchain-driven urban resource data census processing method provided by the present invention has the following technical effects:

[0092] Based on the data category of urban resource data, a multi-layer blockchain is defined, wherein the multi-layer blockchain includes a block parent chain and a multi-level block sub-chain; historical urban resource data is called, and a benchmark resource data block is constructed based on the multi-layer blockchain; multiple census data sources are interacted to obtain urban resource census data, wherein the urban resource census data is associated with and stored with data category labels and data node labels; the mapping relationship between urban resource census data and multi-layer blockchain is established with data category labels and node labels as index constraints, and a census data mapping table is constructed based on the mapping relationship; based on the census data mapping table, the urban resource census data is mapped to the chain, and the urban resource census data on the chain is generated. Thus, the technical effect of improving data integration and management efficiency, and improving data accuracy and consistency is achieved.

[0093] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A blockchain-driven urban resource data census processing method, characterized in that: The method comprises: Based on the data category of the urban resource data, a multi-layer blockchain is defined, wherein the multi-layer blockchain includes a block parent chain and a multi-level block sub-chain; Calling up the historical data of urban resources and constructing a benchmark resource data block based on the multi-layer blockchain; Interact with multiple census data sources to obtain urban resource census data, wherein the urban resource census data is associated with and stored with data category labels and data node labels; Using the data category label and the node label as index constraints, a mapping relationship between the urban resource census data and the multi-layer blockchain is established, and a census data mapping table is constructed based on the mapping relationship; Based on the census data mapping table, the urban resource census data is mapped onto the chain to generate on-chain urban resource census data.

2. The blockchain-driven urban resource data census processing method according to claim 1, characterized in that: Based on the data categories of urban resource data, a multi-layer blockchain is defined, including: Extract census indicator set based on census demand information; Taking data category as the first division dimension, structuring the census indicator set to obtain a census indicator tree, wherein the census indicator tree takes the data category as a first-level leaf node and takes multiple census indicators as child nodes of the first-level leaf node; According to the census indicator tree, the parent chain block structure of the block parent chain is defined.

3. The blockchain-driven urban resource data census processing method according to claim 2, characterized in that: Based on the data categories of urban resource data, a multi-layer blockchain is defined, including: Obtain a census data source library including multiple census subjects in the target area; Constructing a census data source graph network of the census data source library, wherein the census data source graph network includes a plurality of data source nodes corresponding to a plurality of the census subjects; Performing node screening on the census data source graph network based on data categories as extraction dimensions to obtain multiple classified simplified census data source graph networks of multiple data categories; Based on the plurality of classified simplified census data source graph networks, defining a multi-level sub-chain block structure of multi-level sub-chains and multi-level sub-chains; The multi-layer blockchain is deployed by combining the parent chain block structure, the multi-level child chain block structure and the census data source graph network.

4. The blockchain-driven urban resource data census processing method according to claim 3, characterized in that: Interact with multiple census data sources to obtain urban resource census data, including: Analyze the survey task book of the target scenario and determine multiple target data categories; Based on the plurality of target data categories, a plurality of corresponding target simplified census data source graph networks are matched and obtained, and a target census subject set is extracted according to the plurality of target simplified census data source graph networks; According to the target census subject set, a plurality of census data sources are activated to collect census data and obtain the urban resource census data.

5. The blockchain-driven urban resource data census processing method according to claim 4, characterized in that: The census data source graph network is subjected to node screening based on the data category as the extraction target to obtain multiple classified simplified census data source graph networks of multiple data categories, and then further comprising: Traversing a plurality of the classified simplified census data source graph networks, and dividing the census data sources into levels from top to bottom; Based on the hierarchical division result and in combination with the preset minimum hierarchical threshold, the aggregation level of the plurality of block subchains is determined and output as an aggregation strategy.

6. The blockchain-driven urban resource data census processing method according to claim 5, characterized in that: According to the target census subject set, activating a plurality of census data sources to collect census data and obtain the urban resource census data, further comprising: Acquire original urban resource census data collected by a plurality of census data sources; Based on the aggregation strategy, the data category label is used as a first aggregation factor and the data node label is used as a second aggregation factor to perform data fusion on the original urban resource census data from bottom to top; The output data fusion result is the urban resource census data.

7. The blockchain-driven urban resource data census processing method according to claim 4, characterized in that: Taking the data category label and the node label as index constraints, a mapping relationship between the urban resource census data and the multi-layer blockchain is established, and a census data mapping table is constructed based on the mapping relationship, including: Based on the data category label, match the target block subchain of the urban resource census data to obtain a subchain mapping relationship; Simplify the census data source graph network according to the multiple classifications, extract multiple data source node clusters corresponding to the multi-level block subchains, and obtain node mapping relationships; The census data mapping table is constructed by combining the sub-chain mapping relationship and the node mapping relationship.

8. The blockchain-driven urban resource data census processing method according to claim 3, characterized in that: The parent chain block structure of the block parent chain is defined, and then it also includes: determining the parent chain node set of the block parent chain, and the parent chain node set includes multiple parent chain nodes selected based on the node authority information of multiple data source nodes in the census data source library.

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