A method for calculating a comprehensive evaluation coefficient of urban water digital asset data quality

Abstract

The application provides a kind of urban water digital asset data quality comprehensive evaluation method, from multiple aspects, data quality evaluation calculation is carried out, finally, the weighted calculation of each evaluation obtained sub-item is carried out, and the comprehensive evaluation coefficient is obtained.The urban water digital asset data quality comprehensive evaluation method provided by the application is investigated from multiple aspects, the original water digital asset data is comprehensively sorted and calculated, the performance in each aspect is determined, and finally a comprehensive evaluation is obtained, which can provide a basis for subsequent data compilation and cleaning, can greatly improve the cleaning efficiency and cleaning effect of water digital asset data, and provide a data basis for informatization water management.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information-based water management, and in particular to a method for calculating a comprehensive evaluation coefficient of data quality of urban water digital assets. BACKGROUND

[0002] Water data in a large area is very complex and huge, and the water data is distributed in different sub-areas, including real-time, non-real-time, valid, invalid and other complex data forms, which brings great difficulty to the design of a smart water information platform. At the same time, since the current smart water application is still in the exploratory stage, there are uncertain factors in data demand, which makes higher requirements for the water data model framework. Therefore, how to effectively concentrate and integrate the water data of each sub-area and solve the large amount and complexity of water data is a problem to be solved.

[0003] At present, in the field of water information construction, there is no unified water facility data standard, resulting in various data formats obtained by water management departments in different places, which is not conducive to unified and standardized management. Therefore, for water information management, the quality of water digital asset data must be evaluated first, and then the data must be compiled and cleaned. Quality evaluation is particularly important as the first step. SUMMARY

[0004] In order to solve the problems in the prior art, the present application provides a method for calculating a comprehensive evaluation coefficient of data quality of urban water digital assets, which can determine the quality of the original water digital asset data and provide a basis for subsequent data compilation and cleaning.

[0005] The technical solution adopted by the present application to solve the technical problem is to provide a method for calculating a comprehensive evaluation coefficient of data quality of urban water digital assets, comprising the following steps:

[0006] S1, input water digital asset data, which includes data of each water entity, and is stored in each table according to water body type, and the fields in each table are set according to the type of water entity;

[0007] S2, perform basic data quality evaluation on the water digital asset data;

[0008] S3, perform associated data quality evaluation on the water digital asset data;

[0009] S4, perform topological data quality evaluation on the water digital asset data;

[0010] S5, perform running data quality evaluation on the water digital asset data;

[0011] S6, the evaluation of each step S2 to S5 is weighted and calculated, and the comprehensive evaluation coefficient is obtained.

[0012] The water digital asset data in step S1 includes the following data of water entities:

[0013] Sewage treatment plant station data, including sewage treatment plant station spatial position and station code;

[0014] Drainage pipe network pipeline data, including pipeline spatial position, starting point code, ending point code, starting point depth, ending point depth, pipe diameter, pipe material, buried method and pipeline rain and sewage attribute;

[0015] Drainage pipe network well point data, including well point spatial position, well point code, elevation, well point depth, well point rain and sewage attribute and category;

[0016] River water body data, including water body spatial position, blue line width, management line width, upstream water body and downstream water body.

[0017] The basic data quality evaluation of water digital asset data in step S2 includes the following processes:

[0018] S2.1, calculate the data integrity rate P1 according to the following formula:

[0019]

[0020] Wherein is the number of null values in the i-th field of the j-th table, R j is the total number of records in the j-th table, L j is the total number of statistical fields in the j-th table;

[0021] S2.2, calculate the data accuracy rate P2 according to the following formula:

[0022]

[0023] Wherein is the number of error data in the i-th field of the j-th table, R j is the total number of records in the j-th table, L j is the total number of statistical fields in the j-th table.

[0024] The associated data quality evaluation of water digital asset data in step S3 includes the following processes:

[0025] S3.1, calculate the data consistency P3 according to the following formula:

[0026]

[0027] Wherein is the number of inconsistent i-th repeated fields in different tables, is the total number of i-th repeated fields in different tables;

[0028] S3.2, calculate the logical correctness rate P4 according to the following formula:

[0029]

[0030] wherein is the number of i-th logical rule judgment errors, is the total number of i-th logical rule judgments.

[0031] The topological data quality evaluation of the water digital asset data in step S4 includes the following processes:

[0032] S4.1, calculate the coordinate non-repetition rate P5 according to the following formula:

[0033]

[0034] wherein is the number of i-th point-like water space data repetition, is the total number of i-th point-like water space data;

[0035] S4.2, calculate the spatial non-pressing probability P6 according to the following formula:

[0036]

[0037] wherein is the number of i-th line-like water space data spatial overlay, is the total number of i-th line-like water space data;

[0038] S4.3, calculate the topological non-abnormal rate P7 according to the following formula:

[0039]

[0040] wherein is the number of i-th topological abnormality judgment errors, is the total number of i-th topological abnormality judgments.

[0041] The running data quality evaluation of the water digital asset data in step S5 includes the following processes:

[0042] S5.1, calculate the water level normal rate P8 according to the following formula:

[0043]

[0044] wherein is the number of the i-th pipeline data whose water depth exceeds the design water depth specified in the specification, is the total number of the i-th pipeline data;

[0045] S5.2, calculate the non-reverse slope pipe rate P9 according to the following formula:

[0046]

[0047] wherein is the number of the i-th pipeline data that is a reverse slope pipe, is the total number of the i-th pipeline data;

[0048] S5.3, calculate the non-bottleneck pipe rate P10 according to the following formula:

[0049]

[0050] wherein is the number of the i-th pipeline data that is a bottleneck pipe, is the total number of the i-th pipeline data;

[0051] S5.4, calculate the non-misconnection rate P11 according to the following formula:

[0052]

[0053] wherein is the number of the i-th well point data that is a misconnection point, is the total number of the i-th well point data. Step S6, calculate the comprehensive evaluation coefficient P according to the following formula:

[0054] P = ∑ (Pi*Wi)

[0055] wherein Pi is the i-th sub-item, and Wi is the weight corresponding to the i-th sub-item.

[0056] The present application has the beneficial effects in that:

[0057] The present application provides a kind of urban water digital asset data quality comprehensive evaluation coefficient calculation method, from many aspects, original water digital asset data is fully carded and calculated, determine its performance in each respect, finally obtain a comprehensive evaluation, can provide basis for subsequent data compilation and cleaning, can greatly improve the cleaning efficiency and cleaning effect of water digital asset data, provide data basis for informatization water management. DETAILED DESCRIPTION

[0058] The present application will be further described below in conjunction with examples.

[0059] The application provides a kind of urban water digital asset data quality comprehensive evaluation coefficient calculation method, comprising the following steps:

[0060] S1, input water digital asset data, water digital asset data includes the data of each water entity, according to water body type is stored in each table, the field in each table is set according to water entity type. The water digital asset data includes the following water entity data:

[0061] Sewage treatment plant station data, including sewage treatment plant station spatial position and station code;

[0062] Drainage pipe network pipeline data, including pipeline spatial position, starting point code, end point code, starting point depth, end point depth, pipe diameter, pipe material, buried mode and pipeline rain and sewage attribute;

[0063] Drainage pipe network well point data, including well point spatial position, well point code, elevation, well point depth, well point rain and sewage attribute and category;

[0064] River water body data, including water body spatial position, blue line width, management line width, upstream water body and downstream water body.

[0065] S2, basic data quality evaluation is carried out to water digital asset data. Mainly check the completeness and accuracy of each water digital asset attribute filling, including the following process:

[0066] S2.1, calculate data completeness P1 according to the following formula:

[0067]

[0068] Wherein is the number of null values in the i th field in the j th table, R j is the total number of records in the j th table, L j is the total number of statistical fields in the j th table;

[0069] S2.2, calculate data accuracy P2 according to the following formula:

[0070]

[0071] Wherein is the number of error data in the i th field in the j th table, R j is the total number of records in the j th table, L j is the total number of statistical fields in the j th table. The judgment basis of error data is shown in the following table:

[0072]

[0073] Table 1 judgment basis of error data

[0074] S3, correlation data quality evaluation of water digital asset data. Mainly divided into data consistency rate and logical correctness rate.

[0075] Data consistency rate refers to the same data appearing in different tables should be consistent.

[0076] Logical correctness rate refers to the absence of logical conflicts when multiple data appear in the same table or different tables.

[0077] Specifically includes the following process:

[0078] S3.1, calculate data consistency P3 according to the following formula:

[0079]

[0080] Wherein is the number of inconsistent i-th repeated fields in different tables, is the total number of i-th repeated fields appearing in different tables;

[0081] S3.2, calculate logical correctness rate P4 according to the following formula:

[0082]

[0083] Wherein is the number of i-th logical rule judgment errors, is the total number of i-th logical rule judgment. The logical error judgment is shown in the following table:

[0084] No. Logic rule description 1 Well depth < Well surface elevation - Well bottom hole elevation 2 Pipe Burial Depth < Pipe Surface Elevation - Pipe Bottom Elevation 3 Pipe burial depth < well burial depth 4 Pipe burial depth < pipe diameter 5 Outlet elevation < bed elevation 6 (Well point surface elevation - topographic map elevation) / topographic map elevation > 0.2 7 Pump station operating water level > elevation of intake pipe

[0085] Table 2 judgment basis of logical data

[0086] S4, topological data quality evaluation of water digital asset data. Mainly includes coordinate repetition rate, spatial overlay rate and topological abnormality rate.

[0087] Coordinate non-repetition rate: spatial repetition rate of water data represented by spatial points.

[0088] Spatial non-overlay rate: spatial overlay rate of water data represented by spatial lines.

[0089] Topological non-exception rate: point-line relationship topological non-strict rate. Including the following process:

[0090] S4.1, calculate coordinate non-repetition rate P5 according to the following formula:

[0091]

[0092] Wherein is the number of the i-th point-like water spatial data duplication, is the total number of the i-th point-like water spatial data;

[0093] S4.2, calculate the spatial non-pressure probability P6 according to the following formula:

[0094]

[0095] wherein is the number of the i-th linear water spatial data spatial overlay, is the total number of the i-th linear water spatial data;

[0096] S4.3, calculate the topological non-anomaly rate P7 according to the following formula:

[0097]

[0098] wherein is the number of the i-th topological anomaly judgment error, is the total number of the i-th topological anomaly judgment. The topological anomaly judgment is based on the following table:

[0099]

[0100] Table 3 Topological anomaly judgment basis

[0101] S5, evaluate the operation data quality of water digital assets data. The operation data quality evaluation is based on the complete data topology, and analyzes the comprehensive operation condition of water digital assets from the business angle. Including the following processes:

[0102] S5.1, calculate the water level normal rate P8 according to the following formula:

[0103]

[0104] wherein is the number of the i-th pipeline data water depth exceeding the specified design water depth, is the total number of the i-th pipeline data;

[0105] S5.2, calculate the non-reverse slope pipe rate P9 according to the following formula:

[0106]

[0107] wherein is the number of the i-th pipeline data as reverse slope pipe, is the total number of the i-th pipeline data;

[0108] S5.3, calculate the non-bottleneck pipe rate P10 according to the following formula:

[0109]

[0110] wherein is the number of the i-th pipe data being a bottleneck pipe, is the total number of the i-th pipe data;

[0111] S5.4, calculate the non-misconnection rate P11 according to the following formula:

[0112]

[0113] wherein is the number of the i-th well point data being a misconnection point, is the total number of the i-th well point data.

[0114] S6, weight the sub-items obtained in steps S2 to S5, and calculate the comprehensive evaluation coefficient P according to the following formula:

[0115] P = ∑(Pi*Wi)

[0116] wherein Pi is the i-th sub-item, and Wi is the weight corresponding to the i-th sub-item. The weight can be set according to the following table:

[0117]

[0118] Table 4 weight of sub-item

[0119] The comprehensive evaluation coefficient calculation method for urban water digital asset data quality provided by the present application is examined from multiple aspects, the original water digital asset data is comprehensively sorted and calculated, the performance of the original water digital asset data in various aspects is determined, and finally a comprehensive evaluation is obtained, which can provide a basis for subsequent data compilation and cleaning, can greatly improve the cleaning efficiency and cleaning effect of the water digital asset data, and provides a data basis for informatization water management.

Claims

1. A method for calculating a comprehensive evaluation coefficient of urban water digital asset data quality, characterized in that The method comprises the following steps: S1, input water digital asset data, the water digital asset data includes data of each water entity, and the data is stored in each table according to water body types, and fields in each table are set according to water entity types; S2, basic data quality evaluation is performed on the water digital asset data; S3, associated data quality evaluation is performed on the water digital asset data; S4, topological data quality evaluation is performed on the water digital asset data, including the following processes: S4.1, the coordinate non-repetition rate P5 is calculated according to the following formula: ， wherein is the number of repetitions of the i-th point-like water spatial data, is the total number of point-like water spatial data of the i-th type; S4.2, the spatial non-overlapping rate P6 is calculated according to the following formula: ， wherein is the number of spatial overlays of the i-th linear water spatial data spatial overlay, is the total number of the i-th linear water spatial data; S4.3, the topological non-abnormal rate P7 is calculated according to the following formula: ， wherein is the number of errors of the i-th topological anomaly judgment, is the total number of judgments of the i-th topological anomaly. S5, running data quality evaluation is performed on the water digital asset data; S6, the sub-items obtained in steps S2 to S5 are weighted and calculated to obtain a comprehensive evaluation coefficient.

2. The urban water digital asset data quality comprehensive evaluation coefficient calculation method according to claim 1, characterized in that: The water digital asset data in step S1 includes the following water entity data: Sewage treatment plant station data, including spatial positions of sewage treatment plants and station codes; Drainage pipe network pipeline data, including spatial positions of pipelines, start point codes, end point codes, start point burial depths, end point burial depths, pipe diameters, pipe materials, burial methods and pipeline rain and sewage properties; Drainage pipe network well point data, including spatial positions of well points, well point codes, elevations, well point burial depths, well point rain and sewage properties and categories; River water body data, including spatial positions of water bodies, blue line widths, management line widths, upstream water bodies and downstream water bodies.

3. The urban water digital asset data quality comprehensive evaluation coefficient calculation method according to claim 1, characterized in that: The basic data quality evaluation of the water digital asset data in step S2 includes the following processes: S2.1, the data completeness rate P1 is calculated according to the following formula: ， wherein is the number of null values in the i-th field in the j-th table, is the total number of records in the j-th table, is the total number of statistical fields in the j-th table; S2.2, the data accuracy rate P2 is calculated according to the following formula: ， wherein is the number of erroneous data in the i-th field in the j-th table, is the total number of records in the j-th table, is the total number of statistical fields in the j-th table.

4. The urban water digital asset data quality comprehensive evaluation coefficient calculation method according to claim 1, characterized in that: The associated data quality evaluation of the water digital asset data in step S3 includes the following processes: S3.1, the data consistency P3 is calculated according to the following formula: ， wherein is the number of different tables in which the ith repeating field does not agree, is the total number of tables in which the ith repeating field appears; S3.2, the logical correctness rate P4 is calculated according to the following formula: ， wherein is the number of errors in the judgment of the i-th logical rule, is the total number of judgments of the i-th logical rule.

5. The urban water digital asset data quality comprehensive evaluation coefficient calculation method according to claim 1, characterized in that: The running data quality evaluation of the water digital asset data in step S5 includes the following processes: S5.1, the water level normal rate P8 is calculated according to the following formula: ， wherein is the number of pipe data water depths exceeding the design water depth specified by the code for the ith pipe data, is the total number of pipe data for the ith pipe data. S5.2, the non-reverse slope pipe rate P9 is calculated according to the following formula: ， wherein is the number of inverse slope pipes for the i-th pipe data, is the total number of the i-th pipe data; S5.3, the non-bottleneck pipe rate P10 is calculated according to the following formula: ， wherein is the number of pipe data of the i-th kind that is a bottleneck pipe, is the total number of pipe data of the i-th kind; S5.4, the non-misconnection rate P11 is calculated according to the following formula: ， wherein is the number of misconnected points for the i-th well point data, is the total number of the i-th well point data.

6. The urban water digital asset data quality comprehensive evaluation coefficient calculation method according to any one of claims 1 to 5, characterized in that: The comprehensive evaluation coefficient P is calculated according to the following formula in step S6: ， wherein is the ith item sub-item, is the weight corresponding to the ith item sub-item.

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