CN114911782B - Data analysis method suitable for environment law enforcement - Google Patents
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Abstract
The invention discloses a data analysis method suitable for environment law enforcement, which comprises the following steps: s1, establishing a label system by a central database; s2, acquiring and preprocessing environmental protection data, and storing metadata obtained after preprocessing into a central database; s3, correspondingly identifying at least one sub-feature tag for each metadata, and establishing data association of any two metadata based on the correlation degree of any two metadata under the same dimension feature; s4, setting geographic region information or time period information as search source information; extracting corresponding metadata and other metadata which are associated with the corresponding metadata and establish a corresponding relation of the search source information based on a matching relation between the sub-feature tags of the metadata and the search source information, and generating a data analysis result; and S5, visually presenting the result. By adopting the method, the environment in the area can be visually and intelligently monitored, so that law enforcement personnel can accurately study and judge the current environmental problems.
Description
Technical Field
The invention relates to the technical field of environment law enforcement, in particular to a data analysis method suitable for environment law enforcement.
Background
At present, the analysis and query of law enforcement efficiency by domestic environmental monitoring departments still stay on paper law enforcement records, manual document record arrangement or simple information query systems. On one hand, the mode of paper recording is not beneficial to the persistence and data mining of the law enforcement data, and the law enforcement situation is manually recorded on site in the paper mode, so that the data persistence and data mining are not beneficial;
on the other hand, the original information is simply inquired on the information system, environment law enforcement personnel cannot obtain more effective and deeper data information from the original information, and meanwhile, other environmental protection data information about pollution source enterprises is lacked to be used as auxiliary decision making and reference. The original law enforcement situation data of simple inquiry on the information system at present, data are too big and mixed and disorderly, and environment law enforcement personnel can't obtain more deep law enforcement data, law enforcement service information from it fast, can't go to the law enforcement efficiency of overall jurisdiction region more comprehensively, make important decision-making, and the law enforcement personnel also can't utilize the big data of environmental protection, find the key concern pollution sources enterprise of relevant suspicion fast, utilize the environmental protection data of a plurality of dimensions, provide supplementary law enforcement means.
Therefore, in the face of numerous law enforcement objects and industrial parks, an environmental regulatory department currently extracts a batch of enterprises or industrial parks for field inspection and assault inspection according to law enforcement manual data, business experience of law enforcement personnel and business rules of law enforcement of double random extraction. To a certain extent, a large amount of manpower and material resources are consumed, and how to accurately and effectively find out a real problem-existing supervision object becomes a big problem of the current environment law enforcement.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a data analysis method suitable for environment law enforcement, so that effective data analysis and management of massive environment-friendly data are realized, and the application value of the environment-friendly data in the aspect of environment law enforcement is improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
a data analysis method suitable for environmental law enforcement, comprising the steps of:
s1, a central database establishes a label system, wherein the label system at least sets three types of dimensional characteristics of time data, space data and law enforcement data, and each dimensional characteristic is provided with at least one sub-characteristic label;
s2, acquiring environmental protection data acquired by an external system, preprocessing the acquired environmental protection data, and storing metadata obtained after preprocessing into a central database;
s3, correspondingly identifying at least one sub-feature tag for each metadata based on the matching relation between different types of dimensional features and each metadata in a pre-established tag system, and establishing data association of any two metadata based on the correlation degree of any two metadata under the same dimensional feature;
s4, setting geographic region information or time period information as search source information; extracting corresponding metadata and other metadata related to the corresponding metadata based on a matching relation between a sub-characteristic label of each metadata in a pre-established label system and the search source information, establishing a corresponding relation of the search source information, and generating a data analysis result based on the law enforcement data dimensional characteristic display;
and S5, carrying out visual presentation on the data analysis result.
According to the method, the environmental protection data is classified and integrated by utilizing a pre-established label system, and a data analysis result taking the dimensional characteristics of the law enforcement data as display information is generated and visually presented according to the geographical region position or time period required by a user, so that the environment in the region is visually and intelligently monitored, law enforcement personnel can be effectively helped to determine the environmental problems, data support is provided for adopting a targeted management means, and the environmental protection law enforcement personnel can accurately study and judge the current environmental problems.
Further, in the step S1, the sub-feature label of the time data dimension feature includes law enforcement time of the law enforcement object; the sub-feature tag of the spatial data dimensional feature comprises the geographic location of the law enforcement object; sub-feature labels of the dimensional features of the law enforcement data include environmental credit, law enforcement marks, industrial parks, pollution source enterprises, total pollutant emission, administrative penalties, law enforcement efficacy, town law enforcement, law enforcement personnel.
Further, in step S2, the preprocessing the acquired environmental protection data includes: judging whether the environmental protection data is complete or not, cleaning the environmental protection data, checking the consistency of the environmental protection data, and processing invalid values, missing values and repeated values. The method has the advantages that the environmental protection data are preprocessed, so that the problems caused by a paper edition recording mode are solved, the usability and the accuracy of the environmental protection data are improved, invalid data deviating from the actual business meaning are eliminated, the data quality of the environmental protection data is improved, and a solid foundation is provided for subsequent data analysis.
Further, in step S4, after the corresponding metadata and the associated metadata are extracted, based on a matching relationship between different types of sub-feature tags in a pre-established tag system and metadata, a law enforcement object tag matched based on the currently extracted metadata and the associated metadata and at least one remaining sub-feature tag under the dimensional feature of the law enforcement data are obtained from the tag system, and the remaining sub-feature tags are assigned with values based on a preset algorithm, so as to generate a tag ranking taking the law enforcement object tag as a display object. In the step S5, the tag ranking of the display object is visually presented in a chart form. Through the label ranking of the display objects presented in the form of the chart, law enforcement personnel can visually see law enforcement objects with more environmental problems and presume a sensitive law enforcement object list with high suspicion degree, so that the law enforcement efficiency is improved.
Further, in step S4, it is set that geographic area information is used as search source information, metadata that matches the search source information and is identified with a law enforcement object tag is searched, and target object data associated with the metadata is obtained; based on the frequency of occurrence of the target object data, a visualized image is generated, which presents the frequency of occurrence of the data in a color shade variation. The hotspot aggregation degree of the dimensional features of the law enforcement data is judged according to the color depth, the aggregation area of the dimensional features of the law enforcement data can be visually inquired, and the aggregated illegal area is locked for law enforcement departments.
Further, the step S4 includes the following steps: setting time period information as search source information; acquiring metadata which is matched with the search source information and is marked with a law enforcement object label from the data analysis result; selecting any metadata marked with a law enforcement object label as target data, acquiring the rest metadata associated with the target data, and generating a data evolution diagram which takes a set time period as an evolution direction and records other metadata associated with the target data and belonging to the dimensional characteristics of the law enforcement data. Historical changes of metadata associated with the law enforcement object in a set time period can be observed through the data evolution diagram, the law enforcement situation of the law enforcement object in the time period is mastered, and visual monitoring is achieved.
Further, the step S4 includes the following steps: setting time period information as search source information; acquiring metadata which is matched with the search source information and is marked with a law enforcement officer tag from the data analysis result; selecting any metadata marked with a law enforcement officer label as target data, acquiring the rest metadata associated with the target data, and generating a law enforcement road map which takes a set time period as an evolution direction and records other metadata associated with the target data and belonging to the dimensional characteristics of the law enforcement data. The law enforcement circuit diagram of the law enforcement personnel is convenient for a manager to inquire past law enforcement traces of the law enforcement personnel, and the manager can master the law enforcement situation of the law enforcement personnel conveniently.
Further, the method also comprises a step S6 of pushing the data analysis result to an environment law enforcement officer through a remote communication system, so that the law enforcement officer can know the environment condition of the supervised area in real time and timely make law enforcement response to the law enforcement object with the environment problem.
Further, in step S4, a data management platform and an intermediate database are established, the data management platform and the central database form data interaction through the intermediate database and generate the data analysis result, and the data management platform is in communication connection with an external terminal. Law enforcement personnel can check the data analysis result generated by the data management platform in real time at an external terminal.
The invention has the beneficial effects that:
1. according to the method, the environmental protection data is classified and integrated by utilizing a pre-established label system, and a data analysis result taking the dimensional characteristics of the law enforcement data as display information is generated and visually presented according to the geographical region position or time period required by a user, so that the environment in the region is visually and intelligently monitored, law enforcement personnel can be effectively helped to determine the environmental problems, data support is provided for adopting a targeted management means, and the environmental protection law enforcement personnel can accurately study and judge the current environmental problems.
2. The data analysis result comprises the steps of generating a label ranking taking a law enforcement object label as a display object, generating a visual image showing the data appearance frequency by the color depth change, generating a data evolution diagram and generating a law enforcement line diagram, and performing data comparison and analysis according to different environmental protection data classifications and different management angles, so that environmental protection law enforcement personnel can accurately study and judge the current environmental problems and achieve accurate law enforcement, intelligent law enforcement and high-efficiency law enforcement.
3. The invention provides comprehensive data support for environment management work, promotes ecological environment big data innovation application and service, further optimizes environment management flow and improves ecological environment management capability.
Detailed Description
In order to make the technical solution, objects and advantages of the present invention more apparent, the present invention will be further explained with reference to the following embodiments.
The embodiment provides a data analysis method suitable for environment law enforcement, which is matched with units and devices such as a central database, a data platform and an external connection terminal to provide reference for environment law enforcement manual judgment of law enforcement objects and patrol objects so as to improve the law enforcement efficiency of current environment law enforcement personnel. The data analysis method comprises the following steps:
s1, a label system is established in a central database, three types of dimensional characteristics of time data, space data and law enforcement data are set in the label system, and each dimensional characteristic is provided with at least one sub-characteristic label.
The sub-feature tag set by the tag system can set the specific attribute of the sub-feature tag according to the information recorded in the actual law enforcement action of law enforcement officers and law enforcement departments, for example, in the embodiment, the sub-feature tag of the time data dimensional feature comprises the law enforcement time of a law enforcement object; the sub-feature tag of the spatial data dimensional feature comprises the geographic location of the law enforcement object; sub-feature labels for the dimensional features of law enforcement data include environmental credits, law enforcement marks, industrial parks, pollution source enterprises, total pollutant emissions, administrative penalties, law enforcement efficacy, town law enforcement, and the like.
S2, acquiring environmental protection data acquired by an external system, preprocessing the acquired environmental protection data, if judging whether the environmental protection data is complete or not, cleaning the environmental protection data, checking the consistency of the environmental protection data, and processing an invalid value, a missing value and a repeated value; and storing the metadata obtained after preprocessing into a central database.
The environmental protection data can be acquired by regularly acquiring each service system of the environmental protection department. In this embodiment, the acquired environmental protection data includes pollution source enterprise basic information, environmental law enforcement inspection, environmental impact evaluation, environmental technology evaluation, pollution discharge license, completed environmental protection acceptance, pollutant emission total amount control, administrative approval, environmental credit, environmental administrative penalty, pollution source statistical data, document data, industrial park, and the like. And synchronously arranging the acquired environmental protection data and storing the environmental protection data to the central database by using ETL operation and a mode of butt joint with the central database, and meanwhile, setting the authority for the central database and creating an authority table provided with an account number and a password. And setting a data interface of the central database based on the authority table, and acquiring the access authority of the data interface through the account number and the password to ensure the safety of the environmental protection data.
And S3, correspondingly marking at least one sub-feature tag for each metadata based on the matching relation between different types of dimensional features in a pre-established tag system and each metadata, and establishing data association of any two metadata based on the correlation degree of any two metadata under the same dimensional feature.
In this embodiment, after the metadata is stored in the central database, the metadata is set to the corresponding sub-feature tag through the ETL batch process. For example, the central database stores the industrial wastewater discharge amount and the industrial waste gas discharge amount of an enterprise in 1 month and 1 day in 2021 year, the enterprise is identified as a law enforcement object label based on a pre-established label system, the enterprise is identified as a sub-feature label of a time data dimensional feature in 1 month and 1 day in 2021 year, the geographic location of the enterprise is identified as a sub-feature label of a spatial data dimensional feature, the industrial wastewater discharge amount and the industrial waste gas discharge amount are identified as a pollutant discharge total amount label, and the industrial wastewater discharge amount and the industrial waste gas discharge amount are subjected to data association based on the law enforcement data dimensional feature.
S4, setting geographic region information or time period information as search source information; and extracting corresponding metadata and other metadata related to the corresponding metadata based on the matching relationship between the sub-characteristic labels of the metadata in the pre-established label system and the search source information, establishing the corresponding relationship of the search source information, and generating a data analysis result based on the law enforcement data dimensional characteristic display.
In this embodiment, in the step S4, after the corresponding metadata and the associated metadata are extracted, based on a matching relationship between different types of sub-feature tags in a pre-established tag system and metadata, a law enforcement object tag matched based on the currently extracted metadata and the associated metadata and at least one other sub-feature tag under the dimensional feature of the law enforcement data are obtained from the tag system, and a tag ranking taking the law enforcement object tag as a display object is generated by assigning values to the other sub-feature tags based on a preset algorithm.
For example, law enforcement requires a tag ranking within a certain town street with the total amount of pollutant emissions as a sub-signature. In this embodiment, environmental data such as industrial wastewater discharge amount, chemical oxygen demand, ammonia nitrogen, total phosphorus, total nitrogen, industrial exhaust emission amount, sulfur dioxide, nitrogen oxide, smoke, VOCS, and the like are all identified as a total pollutant discharge amount label. Setting geographical area information and time period information of a town street as search source information, extracting metadata marked with a pollutant emission total amount label in the geographical area of the town street in the time period, acquiring an enterprise list matched with the pollutant emission total amount label, assigning values to all metadata marked with the pollutant emission total amount label in the enterprise list based on a preset algorithm, and generating a pollutant emission total amount label ranking of the enterprise list.
In this embodiment, in step S4, by setting geographic area information as search source information, metadata that matches the search source information and is identified by a law enforcement object tag is searched for, and target object data associated with the metadata is obtained; based on the frequency of occurrence of the target object data, a visualized image is generated which presents the frequency of occurrence of the data with a change in shade of color. In particular, the visualization is a thermodynamic diagram. Law enforcement personnel may utilize the visual images that present the frequency of occurrence of the data to perform a comparative analysis of the data for the sub-feature tags of any two or more dimensional features of law enforcement data.
For example, law enforcement officers need environmental credit of all law enforcement objects in a certain town as a data comparison analysis graph of a sub-characteristic label and law enforcement traces as a sub-characteristic label, and can set geographical area information of the town street as search source information, search an enterprise list in the geographical area information of the town street, namely metadata which is matched with the search source information and is marked with the law enforcement object label, and acquire the environmental credit data and the law enforcement trace data which are related to the enterprise list as target object data through the characteristics of data association in a central database. And calculating the frequency of the environmental credit and law enforcement trace of each enterprise in the enterprise list according to the historical records stored in the central database, and generating the thermodynamic diagram of the environmental credit and law enforcement trace. The law enforcement officer can visually compare and analyze the environmental interview and law enforcement trace of all law enforcement objects in the area according to the color shade change on the thermodynamic diagram.
In this embodiment, in the step S4, the time period information may be set as the search source information; acquiring metadata which is matched with the search source information and is marked with a law enforcement object label from the data analysis result; selecting any metadata marked with a law enforcement object label as target data, acquiring the rest metadata associated with the target data, and generating a data evolution diagram which takes a set time period as an evolution direction and records other metadata associated with the target data and belonging to the dimensional characteristics of the law enforcement data.
For example, law enforcement personnel require a data evolution of law enforcement data from a certain enterprise in 2021. The data analysis result is given with 2021 year as search source information, metadata which is marked with the business name in 2021 year is obtained as target data, so that the data of the law enforcement data dimensional characteristics related to the business name is obtained, and a data evolution diagram of the law enforcement data of the business in 2021 year is generated.
The data evolution diagram can enable law enforcement officers to view the data evolution diagrams of all law enforcement data of a certain law enforcement object in a set time period, historical changes of metadata related to the law enforcement officer in the set time period can be observed through the data evolution diagrams, law enforcement situations of the law enforcement officer in the time period can be mastered, and visual monitoring is achieved.
In this embodiment, in the step S4, the time period information may be set as the search source information; acquiring metadata which is matched with the search source information and is marked with a label of a law enforcement officer from the data analysis result; selecting any metadata marked with a law enforcement officer label as target data, acquiring the rest metadata associated with the target data, and generating a law enforcement road map which takes a set time period as an evolution direction and records other metadata associated with the target data and belonging to the dimensional characteristics of the law enforcement data.
For example, a law enforcement wiring diagram of a law enforcement officer in 2021 was required. Setting 2021 year as search source information, acquiring metadata which identifies the law enforcement officer in 2021 year as target data in a data analysis result, thereby acquiring data of the dimensional characteristics of the law enforcement data associated with the law enforcement officer, and producing a law enforcement wiring diagram of the law enforcement officer in 2021 year.
The law enforcement circuit diagram of the law enforcement personnel is convenient for a manager to inquire past law enforcement traces of the law enforcement personnel, and the manager can master the law enforcement situation of the law enforcement personnel conveniently.
And S5, performing visual presentation on the data analysis result.
And visually presenting the visual image which is generated in the last step and presents the data appearance frequency by the color depth change, the label ranking which takes the law enforcement object label as the display object, the data evolution diagram and the law enforcement line diagram.
In the above embodiment, the method further includes step S6, pushing the data analysis result to the environment law enforcement officer through the remote communication system, so that the law enforcement officer can know the environment condition of the supervised area in real time, and can make law enforcement response in time to the law enforcement officer with the environmental problem.
In the above embodiment, in step S4, a data management platform and an intermediate database are established, where the data management platform and the central database form data interaction through the intermediate database and generate the data analysis result, and the data management platform is in communication connection with an external terminal.
The above description is only a preferred embodiment of the present invention, and those skilled in the art may still modify the described embodiment without departing from the implementation principle of the present invention, and the corresponding modifications should also be regarded as the protection scope of the present invention.
Claims (6)
1. A data analysis method suitable for environmental law enforcement is characterized by comprising the following steps: the method comprises the following steps:
s1, a central database establishes a label system, wherein the label system at least sets three types of dimensional characteristics of time data, space data and law enforcement data, and each dimensional characteristic is provided with at least one sub-characteristic label;
s2, acquiring environmental protection data acquired by an external system, preprocessing the acquired environmental protection data, and storing metadata obtained after preprocessing into a central database;
s3, correspondingly identifying at least one sub-feature tag for each metadata based on the matching relation between different types of dimensional features and each metadata in a pre-established tag system, and establishing data association of any two metadata based on the correlation degree of any two metadata under the same dimensional feature;
s4, setting geographic region information or time period information as search source information; extracting corresponding metadata and other metadata related to the corresponding metadata based on the matching relationship between the sub-feature tags of the metadata in a pre-established tag system and the search source information, establishing the corresponding relationship of the search source information, and generating a data analysis result based on the dimension feature display of the law enforcement data;
after extracting corresponding metadata and associated metadata, acquiring a law enforcement object label matched based on the currently extracted metadata and the associated metadata and at least one other sub-feature label under the dimensional feature of the law enforcement data from a label system based on the matching relationship between different types of sub-feature labels in the pre-established label system and assigning values to the other sub-feature labels based on a preset algorithm to generate a label rank taking the law enforcement object label as a display object;
when the time period information is set as the search source information, acquiring metadata which is matched with the search source information and is marked with a law enforcement object label from the data analysis result; selecting any metadata marked with a law enforcement object label as target data, acquiring the rest metadata associated with the target data, and generating a data evolution diagram or a law enforcement route diagram which takes a set time period as an evolution direction and is recorded with other metadata associated with the target data and belonging to the dimensional characteristics of the law enforcement data;
when geographical region information is set as search source information, searching metadata which is matched with the search source information and is marked with a law enforcement object label, and acquiring target object data associated with the metadata; generating a visual image presenting the appearance frequency of the data in color depth change based on the appearance frequency of the target object data;
and S5, carrying out visual presentation on the data analysis result.
2. The data analysis method applicable to environmental law enforcement according to claim 1, wherein in the step S1, the sub-feature tag of the time data dimension feature comprises law enforcement time of law enforcement subjects; the sub-feature tag of the spatial data dimensional feature comprises the geographic location of the law enforcement object; sub-feature tags for dimensional features of law enforcement data include environmental interviews, law enforcement marks, industrial parks, pollution source enterprises, total pollutant emission, administrative penalties, law enforcement efficacy, town law enforcement, and law enforcement officers.
3. The data analysis method applicable to environmental law enforcement according to claim 1, wherein in the step S2, the pre-processing of the environmental protection data obtained comprises: judging whether the environmental protection data is complete or not, cleaning the environmental protection data, checking the consistency of the environmental protection data, and processing invalid values, missing values and repeated values.
4. The data analysis method applicable to environmental law enforcement according to claim 1, wherein in the step S5, the tag ranking of the display object is visually presented in a chart form.
5. The method for data analysis applicable to environmental law enforcement according to claim 1, further comprising a step S6 of pushing the data analysis results to environmental law enforcement officers through a telecommunication system.
6. The data analysis method applicable to environmental enforcement according to claim 1, wherein in step S4, a data management platform and an intermediate database are established, the data management platform and the central database form data interaction through the intermediate database and generate the data analysis result, and the data management platform is in communication connection with an external terminal.
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| CN202210398730.6A CN114911782B (en) | 2022-04-15 | 2022-04-15 | Data analysis method suitable for environment law enforcement |
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| CN202210398730.6A CN114911782B (en) | 2022-04-15 | 2022-04-15 | Data analysis method suitable for environment law enforcement |
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