CN115858829A - Multi-source heterogeneous environment data asset construction method based on computational power network - Google Patents
Multi-source heterogeneous environment data asset construction method based on computational power network Download PDFInfo
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Abstract
The invention relates to the technical field of environmental management big data, and discloses a multi-source heterogeneous environment data asset construction method based on a computational power network, which comprises the following steps of S1, multi-source heterogeneous environment data processing; s2, constructing data warehouse in a classified manner; s3, constructing a theme data mart; s4, constructing a knowledge query graph; and S5, cross-media retrieval application. The method comprises the steps of multi-source heterogeneous environment data processing, data warehouse classification construction, topic data mart construction knowledge query map construction and cross-media retrieval application; the problems that environment management data are poor in general standardization, data among different business departments are lack of correlation and integration, and the application degree is low in actual business application are solved, preprocessing and accurate classification of various environment management data on a computational power network are efficiently completed, the treatment and application requirements of the environment protection work informatization construction on mass data at the present stage are met, and the environment protection informatization is changed into digital environment protection and intelligent environment protection.
Description
Technical Field
The invention relates to the technical field of environment management big data, in particular to a multi-source heterogeneous environment data asset construction method based on a computational power network.
Background
With the popularization of the application of new-generation information technologies such as big data, artificial intelligence, cloud computing and the like, the requirements of the whole society on data storage, computation, transmission and application are greatly improved, and the computing power requirement on strong industry permeability and wide social applicability is higher and higher; an algorithm network taking the algorithm as a carrier is rapidly developed, the radiation of the environment-friendly industry is not exceptional, the environment data source has various sources such as various environment-friendly business systems, remote sensing images, thematic maps, social information, GPS positioning tracking and the like, and various data are obvious in difference on the data structure, so that the characteristic of multi-source and heterogeneous environment data is formed. The computing power network is a deepening and upgrading technology for the integration of the environmental management cloud network, in multi-source heterogeneous environmental data on the computing power network, single-dimensional data resources in various environmental protection fields such as water, atmosphere, soil, pollution sources and the like cannot meet application requirements of environmental protection personnel, the computing requirements of the computing power network cannot be guaranteed, and the application requirements of the environmental protection personnel cannot be met.
The 'big data' era has no previous access amount and calculation amount to the data center on the computing power network. Anything may happen when the data is "large" to some extent. With the continuous and deep development of various information-based constructions of environmental management, the data center faces not only the access amount of a base point but also the access amounts of environmental protection departments of the whole province or even the whole country, and at the moment, the pressure faced by the data center is hard to imagine; in addition, the content in the environment database is not only abundant, but also the structure is changed, the content is not only stored in a standard structure of a two-dimensional table, but also non-structured data standard is standardized to store non-uniform office documents, texts, pictures, audio and video, XML, HTML, various reports and the like, and all data are massive and grow rapidly; in the face of such a large amount of data, the reading efficiency of the data is lower and lower, so that the standardization of the current environmental data and the data warehouse architecture cannot adapt to the computational network requirement of high-speed reaction; in addition, various data systems of current environment management are numerous and have different data sources, various data have obvious difference on data structures, the data volume is huge and reaches TB magnitude and even PB magnitude, but the environment data is generally poor in standardization, data among different business departments are lack of association and integration, and the application degree in actual business application is low. And the construction of the environmental data assets spans a plurality of fields such as environment, computer science, software and hardware technology and the like, and the current technology does not fully utilize the research and development results of machine learning and other related fields, so the requirement of actual environmental protection work cannot be completely met on the service efficiency of the construction of the data assets, and the intelligent level of the construction of the data assets also has a great space.
Disclosure of Invention
The invention aims to provide a multi-source heterogeneous environment data asset construction method based on a computational power network, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a multi-source heterogeneous environment data asset construction method based on a computational power network comprises the following steps:
s1, processing multi-source heterogeneous environment data: performing hybrid processing on multi-source heterogeneous original environment data on a computing power network, wherein the multi-source heterogeneous original environment data comprises structured environment data, unstructured environment data and real-time environment data;
s2, establishing data warehouse classification: extracting, converting and cleaning the processed multi-source heterogeneous environment data, and establishing a data warehouse based on content, associability, production standardization and time tags to realize the classified construction of the data warehouse; then, performing classified storage conversion processing on the user history and newly input structured and unstructured environment data through a classified data warehouse;
s3, theme data mart construction: according to the data warehouse constructed by classification, keywords and keywords are intelligently extracted from closely related environmental data through an environmental management object extraction, conversion and loading tool, and a theme data mart is constructed so as to meet the requirements of environmental protection business management analysis and prediction decision making;
s4, establishing a knowledge query graph: extracting syntax trees and semantic triples in semantic analysis, applying query sentences of a user to a data warehouse, and solving the problem that different entity identifiers in multi-source heterogeneous environment data represent the same entity object; then, one or more relation phrases are formed by utilizing entity extraction, relation extraction and attribute extraction modes, and a knowledge query graph with object entities and a relation network as a core structure is constructed through reference resolution;
s5, cross-media retrieval application: establishing a media similarity measure of a multi-source heterogeneous environment through semantic association and bottom layer characteristics among multi-source heterogeneous media data; meanwhile, according to the characteristics of environmental data, local typical correlation analysis and multi-view learning technology are applied, and a multi-source heterogeneous media unified expression model is realized by combining the similarity measurement of the multi-source heterogeneous media on the semantic level; and then, applying a multi-source heterogeneous media information sorting algorithm to perform structured analysis and management on the multi-source heterogeneous media, and realizing seamless identification and retrieval among the multi-source heterogeneous environment management media.
As a still further scheme of the invention: the processing method of the structured environment data in the step S1 comprises the following steps: the MPP distributed relational database is used for storing, a Share-Nothing architecture is adopted for the MPP distributed relational database, a host, an operating system, a memory and storage are respectively controlled, and segments are interconnected through an IP network; the structured environment data includes database data and formatted data.
As a still further scheme of the invention: the processing method of the unstructured environment data in the step S1 comprises the following steps: the Hadoop cluster is adopted for data storage and calculation, the HDFS provides a distributed storage function, the Map-Reduce provides an offline batch calculation function, the processing speed is increased through parallel processing, and the reliability of the platform is guaranteed; the unstructured environmental data includes picture data, audio data, and video data.
As a still further scheme of the invention: the processing method of the real-time environment data in the step S1 comprises the following steps: processing by adopting a memory database + Storm flow type calculation framework; the message data or the real-time interactive data can be processed with extremely low delay, and the processed result is stored in a persistent medium; the real-time environmental data includes space-time remote sensing data.
As a still further scheme of the invention: in the step S2, a corresponding data warehouse may be customized for the user according to the user' S preference and usage logic.
As a still further scheme of the invention: and the data warehouse in the step S2 comprises a basic data warehouse, a configuration data warehouse, a business data warehouse and a data warehouse.
As a still further scheme of the invention: and in the step S3, corresponding theme data marts can be custom-built for users according to the building classification of the data warehouse so as to form flexible control on environment management activities and provide environment management decision issuing for the users in a theme mart mode.
As a still further scheme of the invention: and the theme data mart in the step S3 comprises an environment management object data mart, an environment management activity data mart and an environment management decision application data mart.
As a still further scheme of the invention: the method for solving the problem that different entity identifiers in the multi-source heterogeneous environment data represent the same entity object in the step S4 comprises the following steps: the entity identifiers are fused in the entity alignment processes of data preprocessing, partition indexing and feature matching, and the identification and combination, multi-dimensional similarity comparison and entity equivalence judgment of the same entity are realized; and starting from the existing entity relation data in the data warehouse, establishing new association between entities through background computational reasoning.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of multi-source heterogeneous environment data processing, data warehouse classification construction, topic data mart construction knowledge query map construction and cross-media retrieval application; the problems that environment management data are poor in general standardization, data among different business departments are lack of correlation and integration, and the application degree is low in actual business application are solved, preprocessing and accurate classification of various environment management data on a computational power network are efficiently completed, the treatment and application requirements of the environment protection work informatization construction on mass data at the present stage are met, and the environment protection informatization is changed into digital environment protection and intelligent environment protection.
Drawings
FIG. 1 is a functional architecture diagram of a multi-source heterogeneous environment data asset construction method based on a computational power network;
FIG. 2 is a hardware topology diagram of a multi-source heterogeneous environment data asset construction method based on a computational power network;
fig. 3 is a technical architecture diagram of a multi-source heterogeneous environment data asset construction method based on a computational power network.
Detailed Description
Referring to fig. 1 to 3, in an embodiment of the present invention, a multi-source heterogeneous environment data asset construction method based on a computing power network, as shown in fig. 1, includes the following steps:
s1, processing multi-source heterogeneous environment data: performing hybrid processing on multi-source heterogeneous original environment data on a computing power network, wherein the multi-source heterogeneous original environment data comprises structured environment data, unstructured environment data and real-time environment data; the processing method of the structured environment data in the step S1 comprises the following steps: the MPP distributed relational database is used for storing, a Share-Nothing architecture is adopted for the MPP distributed relational database, a host, an operating system, a memory and storage are respectively controlled, and segments are interconnected through an IP network; the structured environment data comprises database data and format report data; the processing method of the unstructured environment data in the step S1 comprises the following steps: the Hadoop cluster is adopted for data storage and calculation, the HDFS provides a distributed storage function, the Map-Reduce provides an offline batch calculation function, the processing speed is increased through parallel processing, and the reliability of the platform is guaranteed; the unstructured environmental data comprises picture data, audio data and video data; the processing method of the real-time environment data in the step S1 comprises the following steps: processing by adopting a memory database + Storm flow type calculation framework; the message data or the real-time interactive data can be processed with extremely low delay, and the processed result is stored in a persistent medium; the real-time environment data comprises space-time remote sensing data;
by intelligently selecting a reasonable data processing mode for different environmental data, the environmental data on the computational power network can be efficiently stored, managed and analyzed;
s2, classified construction of a data warehouse: extracting, converting and cleaning the processed multi-source heterogeneous environment data, and establishing a data warehouse based on content, associability, production standardization and time tags to realize the classified construction of the data warehouse; the data warehouse comprises a basic data warehouse, a configuration data warehouse, a business data warehouse and a data warehouse; a corresponding data warehouse can be custom-built for the user according to the preference and the use logic of the user; then, classified storage conversion processing is carried out on the user history and newly input structured and unstructured environment data through a classified data warehouse, intelligent data integration is provided for users, and retrieval, query, calling, sharing and distribution of environment data on the computational power network by subsequent users are facilitated;
s3, theme data mart construction: according to the data warehouse constructed by classification, keywords and keywords are intelligently extracted from closely related environmental data through an environmental management object extraction, conversion and loading tool, and a theme data mart is constructed so as to meet the requirements of environmental protection business management analysis and prediction decision making; the theme data mart comprises an environment management object data mart, an environment management activity data mart and an environment management decision application data mart; the corresponding theme data marts can be customized and constructed for the user according to the construction and classification of the data warehouse so as to form flexible management and control on environment management activities, and environment management decision issuing is provided for the user in a theme mart mode, so that customized intelligent service is provided for the user; the whole life cycle management of environmental data on the computing power network can be effectively tracked and guaranteed by a theme market-gathering mode, and standardized services or customized intelligent services are provided for users;
s4, establishing a knowledge query graph: extracting syntax trees and semantic triples in semantic analysis, applying query sentences of a user to a data warehouse, and solving the problem that different entity identifiers in multi-source heterogeneous environment data represent the same entity object; then, one or more relation phrases are formed by utilizing entity extraction, relation extraction and attribute extraction modes, and a knowledge query graph with object entities and a relation network as a core structure is constructed through reference resolution; the knowledge query map provides support for knowledge representation, service relation analysis and relation search of environment management in a visual, browsable and analyzable form;
s5, cross-media retrieval application: establishing a multi-source heterogeneous environment media similarity measure through semantic association and bottom layer characteristics among multi-source heterogeneous media data; meanwhile, according to the characteristics of environmental data, local typical correlation analysis and multi-view learning technology are applied, and a multi-source heterogeneous media unified expression model is realized by combining the similarity measurement of the multi-source heterogeneous media on the semantic level; then, applying a multi-source heterogeneous media information sorting algorithm to perform structured analysis and management on the multi-source heterogeneous media, and realizing seamless identification and retrieval among the multi-source heterogeneous environment management media; therefore, the rapid positioning and searching of the environment management full data information are solved, and multi-source heterogeneous data media identification analysis is performed on the environment multimedia information; the method for solving the problem that different entity identifiers in multi-source heterogeneous environment data represent the same entity object comprises the following steps: the entity identifiers are fused in the entity alignment process of data preprocessing, partition indexing and feature matching, and identification and combination, multi-dimensional similarity comparison and entity equivalence judgment of the same entity are realized; the method is based on the existing entity relation data in the data warehouse, and establishes new association among entities through background calculation reasoning, thereby expanding and enriching the knowledge network, finding new knowledge from the existing knowledge, being more beneficial to analyzing the level of syntactic structures of the environmental data on the user analytic power network, and solving the problem of 'long distance dependency' in natural language processing.
As shown in fig. 2, which is presented in a hardware deployment. Computing power service provided by the existing computing center, edge computing nodes and the like is low in efficiency, and a computing power network can better coordinate environment management data resources and provide better service. Computing nodes distributed by 'cloud, pipe, edge and end' are connected through a gigabit network switch in the computing network center hardware deployment, environment data computing resources and network resource states can be sensed in real time, various data computing and service applications are intelligently distributed and scheduled, and a whole multi-source heterogeneous environment data cloud computing network with the sensing, distribution and schedulable computing resources is formed. And the terminal computing node is associated with the regional computing power trading center, energized by a computing power provider, a consumer and an AI, and connected with the environment-friendly private network to provide corresponding environment data sources for all jurisdictions, and each subarea can provide application service for various environment-related workers based on the computing network data resources. Through the iteration of the regional control center layer by layer, the cross-regional mutual-recognition communication of environmental management data analysis can be realized, cross-regional business service is provided, and meanwhile, a safe and reliable environmental management data resource computing service platform is provided for users.
As shown in fig. 3, it is presented in a technical architecture of environment management data parsing on a computing network; environment management data acquisition and migration are realized through technologies such as web crawlers and the like; on a computing network resource layer, computing resources, storage resources, network resources and service resources of environment management data are provided, and multi-level distributed computing resources and environment-friendly network resources of 'cloud, management, edge and end' are provided, so that the intelligent computing power requirement of the environment management data is met; in a computational network control layer, environment data storage is carried out on a distributed file system, a distributed database, a relational database, a memory database and the like, data analysis services of computational network calculation, data collision and statistical analysis of an offline calculation frame, a memory calculation frame, a deep learning calculation frame, a streaming calculation frame and the like are provided for an upper layer, abstract computational network environment data resources are sensed, network and calculation resource conditions are comprehensively considered, and environmental protection services are distributed to different computational nodes according to needs by utilizing technologies such as vertical retrieval, data view, machine data mining, feature modeling and the like; in a computational network service layer, carrying various calculated services and applications such as hybrid data processing, data warehouse classification, topic data market construction, knowledge map construction, cross-media retrieval and the like, and transmitting request parameters such as the computational power of a user on the environmental protection service to a computational power routing layer; the above-mentioned every layer is related to the arrangement management layer of the computational network, and is responsible for the calculation modeling, arrangement, safety, operation, etc., and the management and control of the environment management calculation data resource and network resource.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (9)
1. A multi-source heterogeneous environment data asset construction method based on a computational power network is characterized by comprising the following steps:
s1, processing multi-source heterogeneous environment data: performing hybrid processing on multi-source heterogeneous original environment data on a computing power network, wherein the multi-source heterogeneous original environment data comprises structured environment data, unstructured environment data and real-time environment data;
s2, classified construction of a data warehouse: extracting, converting and cleaning the processed multi-source heterogeneous environment data, establishing a data warehouse based on content, associability, production standardization and time tags, and realizing the classified construction of the data warehouse; then, performing classified storage conversion processing on the user history and newly input structured and unstructured environment data through a classified data warehouse;
s3, theme data mart construction: according to the data warehouse constructed by classification, keywords and keywords are intelligently extracted from closely related environmental data through an environmental management object extraction, conversion and loading tool, and a theme data mart is constructed so as to meet the requirements of environmental protection business management analysis and prediction decision making;
s4, establishing a knowledge query graph: extracting syntax trees and semantic triples in semantic analysis, applying query sentences of a user to a data warehouse, and solving the problem that different entity identifiers in multi-source heterogeneous environment data represent the same entity object; then, one or more relation phrases are formed by utilizing entity extraction, relation extraction and attribute extraction modes, and a knowledge query graph with object entities and a relation network as a core structure is constructed through reference resolution;
s5, cross-media retrieval application: establishing a multi-source heterogeneous environment media similarity measure through semantic association and bottom layer characteristics among multi-source heterogeneous media data; meanwhile, according to the characteristics of environmental data, local typical correlation analysis and multi-view learning technology are applied, and a multi-source heterogeneous media unified expression model is realized by combining the similarity measurement of the multi-source heterogeneous media on the semantic level; and then, applying a multi-source heterogeneous media information sorting algorithm to perform structured analysis and management on the multi-source heterogeneous media, and realizing seamless identification and retrieval among the multi-source heterogeneous environment management media.
2. The multi-source heterogeneous environment data asset construction method based on the computing power network as claimed in claim 1, wherein the processing method of the structured environment data in the step S1 is as follows: the MPP distributed relational database is used for storing, a Share-Nothing architecture is adopted for the MPP distributed relational database, a host, an operating system, a memory and storage are respectively controlled, and segments are interconnected through an IP network; the structured environment data includes database data and formatted data.
3. The multi-source heterogeneous environment data asset construction method based on the computing power network as claimed in claim 1, wherein the processing method of the unstructured environment data in the step S1 comprises: the Hadoop cluster is adopted for data storage and calculation, the HDFS provides a distributed storage function, the Map-Reduce provides an offline batch calculation function, the processing speed is increased through parallel processing, and the reliability of the platform is guaranteed; the unstructured environmental data includes picture data, audio data, and video data.
4. The multi-source heterogeneous environment data asset construction method based on the computational power network according to claim 1, wherein the processing method of the real-time environment data in the step S1 is as follows: processing by adopting a memory database + Storm flow type calculation framework; the message data or the real-time interactive data can be processed with extremely low delay, and the processed result is stored in a persistent medium; the real-time environmental data includes space-time remote sensing data.
5. The multi-source heterogeneous environment data asset construction method based on the computing power network as claimed in claim 1, wherein in the step S2, a corresponding data warehouse can be custom-constructed for the user according to the user' S preference and use logic.
6. The computing-network-based multi-source heterogeneous environment data asset construction method according to claim 1, wherein the data warehouse in the step S2 comprises a basic data warehouse, a configuration data warehouse, a business data warehouse and a data warehouse.
7. The multi-source heterogeneous environment data asset construction method based on the computing power network as claimed in claim 1, wherein in the step S3, a corresponding theme data mart is custom-constructed for the user according to the construction classification of the data warehouse, so as to form flexible management and control on environment management activities, and provide environment management decision issuing to the user in a theme mart manner.
8. The computing-network-based multi-source heterogeneous environment data asset construction method according to claim 1, wherein the subject data mart in the step S3 comprises an environment management object data mart, an environment management activity data mart and an environment management decision application data mart.
9. The method for constructing the multi-source heterogeneous environment data asset based on the computing power network according to claim 1, wherein the solution to the problem that different entity identifiers in the multi-source heterogeneous environment data represent the same entity object in the step S4 is as follows: the entity identifiers are fused in the entity alignment process of data preprocessing, partition indexing and feature matching, and identification and combination, multi-dimensional similarity comparison and entity equivalence judgment of the same entity are realized; and starting from the existing entity relation data in the data warehouse, establishing new association between entities through background computational reasoning.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116136861A (en) * | 2023-04-18 | 2023-05-19 | 中国电子科技集团公司第十研究所 | Distributed multi-source heterogeneous data management system and method based on knowledge graph |
| CN116340885A (en) * | 2023-04-11 | 2023-06-27 | 太原理工大学 | Multi-source heterogeneous data fusion method based on coal mine information physical system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116340885A (en) * | 2023-04-11 | 2023-06-27 | 太原理工大学 | Multi-source heterogeneous data fusion method based on coal mine information physical system |
| CN116340885B (en) * | 2023-04-11 | 2023-10-03 | 太原理工大学 | Multi-source heterogeneous data fusion method based on coal mine information physical system |
| CN116136861A (en) * | 2023-04-18 | 2023-05-19 | 中国电子科技集团公司第十研究所 | Distributed multi-source heterogeneous data management system and method based on knowledge graph |
| CN116136861B (en) * | 2023-04-18 | 2023-08-15 | 中国电子科技集团公司第十研究所 | Distributed multi-source heterogeneous data management system and method based on knowledge graph |
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