CN113780767B - General survey data acquisition and quality evaluation coupling system - Google Patents
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Abstract
The invention discloses a general survey data acquisition and quality evaluation coupling system, which comprises: the data acquisition module is used for acquiring census data; the quality evaluation module is used for evaluating the census data, and if the census data are unqualified, the quality evaluation module returns to the data acquisition module for re-acquisition or processing; and the data uploading module uploads the qualified data which is evaluated by the quality evaluation module. The invention not only adopts a qualitative and quantitative combined method to carry out data quality evaluation, but also can ensure that the census data collected at each level can be timely evaluated and corrected in time, thereby realizing high-efficiency coupling of data collection and quality evaluation, ensuring the scientificity and accuracy of census data and improving the confidence coefficient.
Description
Technical Field
The invention relates to the technical field of data statistics, in particular to a coupling system for census data acquisition and quality evaluation.
Background
The statistical data is a 'sunny rain gauge' which objectively reflects the economic and social development, and is an important reference and support for scientific decision making and accurate construction. In recent years, the statistical system of China is continuously perfected, the data production flow is continuously standardized, and the idea of data-aided decision making is increasingly deep. More and more departments begin to organize data census work regularly, and attempt to find out the construction base number in the field through census, so that an important basis is provided for planning the next development.
Conventional data statistics methods typically perform evaluation and analysis together after all data acquisition is completed. This method is applicable to statistics of simple data items in a small range. However, when the method is used for large-scale general investigation with wide coverage, multiple levels and complex statistical items, the problem that a great deal of time is consumed, and the data are all counted by teachers and students, so that the overall quality of the data is not high is often found.
In this case, reorganizing one census is generally unacceptable due to time and labor costs, and processing existing low quality data by only data cleansing techniques can only marginally improve the data quality, which results in census data obtained in a time-consuming and labor-consuming manner not fully playing the intended role. The problem of data quality occurs, and besides the factors of statistics system, tool means and personnel literacy, the fact that the data quality evaluation is not fully performed in the data acquisition stage is an important cause which cannot be ignored.
Disclosure of Invention
According to an embodiment of the present invention, there is provided a census data acquisition and quality evaluation coupling system, including:
the data acquisition module is used for acquiring census data;
the quality evaluation module is used for evaluating the census data, and if the census data are unqualified, the quality evaluation module returns to the data acquisition module for re-acquisition or processing;
and the data uploading module uploads the qualified data which is evaluated by the quality evaluation module.
Further, the data acquisition module comprises a data acquisition organization module and a plurality of data acquisition sub-modules, the plurality of data acquisition sub-modules are divided into N levels, each level comprises a plurality of data acquisition sub-modules, each data acquisition sub-module of the previous level corresponds to the data acquisition sub-module of the next level, and the data uploading module uploads the census data step by step until the data acquisition organization module.
Further, the quality evaluation module comprises a quality evaluation total module and a plurality of quality evaluation sub-modules, the quality evaluation sub-modules are in one-to-one correspondence with the data acquisition sub-modules, the quality evaluation total module corresponds to the data acquisition organization module, each quality evaluation sub-module evaluates the census data uploaded by the data uploading module acquired and/or received by the corresponding data uploading module, and the quality evaluation total module evaluates the census data received by the data acquisition organization module.
Further, the data uploading module comprises a plurality of data uploading sub-modules, the data uploading sub-modules are in one-to-one correspondence with the quality evaluation sub-modules and the data acquisition sub-modules, and the data uploading sub-modules are used for uploading the census data qualified by the mass transfer quantity evaluation sub-modules.
Further, the quality assessment module assesses the census data using a quality assessment model that includes a data production environment dimension, a data production process dimension, and a data product dimension.
Further, the data production environment dimensions include: the soundness of the screening system, the independence of screening institutions, the expertise of screening personnel and the advancement of screening tool means; the data production environment dimension is a qualitative dimension.
Further, the data production process dimensions include: a data conciseness index, a data repeatability index and a data acquisition automation ratio index; the data conciseness index includes: the necessary statistics term proportion P and the invalid data rate Q; p=1-P 0 /P 1 ，P 0 For the number of data items counted by other relevant departments, P 1 Counting the number of data items to be counted; q=q 0 /Q 1 ，Q 0 For the number of data items which do not need to be filled but are actually filled, Q 1 Is the number of data items actually filled.
Further, the data product dimensions include: integrity index, accuracy index, timeliness index, ease of use index, maintainability index.
Further, the integrity indicator comprises: fill rate, single field fill rate, and a particular series of associated field fill rates.
Further, the filling rate includes: fill data fill rate B, b=b 0 /B 1 ，B 0 Number of necessary field for value, B 1 To fill the total number of fields.
According to the general survey data acquisition and quality assessment coupling system provided by the embodiment of the invention, the data quality assessment is carried out by adopting a qualitative and quantitative combination method, the timely quality assessment and timely correction of the general survey data acquired at each level can be ensured, the efficient coupling of the data acquisition and the quality assessment is realized, the scientificity and the accuracy of the general survey data are ensured, and the confidence is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and are intended to provide further explanation of the technology claimed.
Drawings
FIG. 1 is a system schematic diagram of a coupling system for census data collection and quality assessment according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the attached drawings, which further illustrate the present invention.
First, a coupling system for census data collection and quality evaluation according to an embodiment of the present invention will be described with reference to fig. 1, and is used for comprehensive census of economy, population, etc., and has a wide application scenario.
As shown in FIG. 1, the general survey data acquisition and quality evaluation coupling system of the embodiment of the invention is provided with a data acquisition module, a quality evaluation module and a data uploading module. The data acquisition module is used for acquiring census data; the quality evaluation module is used for evaluating the census data, and if the census data are unqualified, the quality evaluation module returns to the data acquisition module for re-acquisition or processing; the data uploading module uploads the qualified data which is evaluated by the quality evaluation module.
Specifically, as shown in fig. 1, the data acquisition module includes a data acquisition organization module 11 and a plurality of data acquisition sub-modules 12, the plurality of data acquisition sub-modules 12 are divided into N levels, each level includes a plurality of data acquisition sub-modules 12, the data acquisition sub-modules 12 of each previous level correspond to the data acquisition sub-modules 12 of a plurality of next levels, and the data uploading module uploads the census data step by step until the data acquisition organization module 11.
Specifically, as shown in fig. 1, the quality evaluation module includes a quality evaluation total module 21 and a plurality of quality evaluation sub-modules 22, the plurality of quality evaluation sub-modules 22 are in one-to-one correspondence with the plurality of data acquisition sub-modules 12, the quality evaluation total module 21 corresponds to the data acquisition organization module 11, each quality evaluation sub-module 22 evaluates the census data uploaded by the data uploading module acquired and/or received by the corresponding data uploading module, and the quality evaluation total module 21 evaluates the census data received by the data acquisition organization module 11, so that the quality evaluation is completed in time by each stage of data acquisition sub-modules 12, the accuracy and the timely correction of the data are ensured, the efficient coupling of the data acquisition and the quality evaluation is realized, the scientificity and the accuracy of the census data are ensured, and the confidence is improved.
Further, the quality assessment module assesses the census data using a quality assessment model that includes a data production environment dimension, a data production process dimension, and a data product dimension.
Further, the data production environment dimensions include: the soundness of the screening system, the independence of screening institutions, the expertise of screening personnel and the advancement of screening tool means; the data production environment dimension is a qualitative dimension.
The soundness of the general investigation system is whether the permission of the statistical data production and the release activities is definitely regulated in the relevant laws or systems, and in the embodiment, the soundness of the general investigation system adopts 'soundness', 'basic soundness', 'soundness' as an evaluation grade; the census mechanism independence is the independence of the statistics mechanism and all levels of statistics personnel in the production and release processes of the statistics data and is used for measuring whether the statistics activities are susceptible to the influence of external pressure, and in the embodiment, the census mechanism independence adopts 'independent', 'basic independent', 'independent' as an evaluation grade; the expertise of the census staff is the expertise of the statistical activity organisers, the statistical form designer, the statistical data filler and the statistical system developer, and in the embodiment, the expertise of the census staff adopts 'professional', 'basic specialty', 'non-professional' as the evaluation grade; the method advancement of the census tool is the usability and advancement of the filling system used in statistics in links of data acquisition, data submission, data summarization, data analysis and the like, and in the embodiment, the method advancement of the census tool adopts 'advanced', 'basic advanced', 'non-advanced' as an evaluation grade.
Further, the data production process dimensions include: a data conciseness index, a data repeatability index and a data acquisition automation ratio index. The data conciseness is that ready-made available data which can be obtained from other channels is not organized to be repeatedly filled as much as possible, and the filled data which can be completed by a certain unit is prevented from being repeatedly filled by a plurality of units as much as possible; the data repeatability is a measurement standard for accidentally repeating a specific field, record or data set, the index needs to definitely judge the rule of data repetition according to actual conditions, and then a corresponding tool is adopted for statistical analysis; the data acquisition automation ratio is the ratio of records capable of being automatically acquired and filled by a machine to the total number of records in all data items.
In this embodiment, the data conciseness index includes: the necessary statistics term proportion P and the invalid data rate Q; wherein p=1 to P 0 /P 1 ，P 0 For the number of data items counted by other relevant departments, P 1 Counting the number of data items to be counted; q=q 0 /Q 1 ，Q 0 For the number of data items which do not need to be filled but are actually filled, Q 1 Is the number of data items actually filled.
Further, the data product dimensions include: integrity index, accuracy index, timeliness index, ease of use index, maintainability index. Wherein the integrity is a measure of the existence, validity, structure, content and other characteristics of the data, in this embodiment the integrity indicator comprises: the method comprises the steps of filling rate, single field filling rate and a specific series of associated field filling rates, wherein the filling rate is the ratio of the number of fields containing values to the total number of fields, the single field filling rate is the ratio of the number of records containing values in a certain field to the total number of records, and the specific series of associated field filling rate is the ratio of the number of records containing values in a series of associated fields to the total number of records; the accuracy is a measurement standard of data accuracy, and in this embodiment, two methods are adopted for evaluating the accuracy, one is based on statistical data itself for comparison analysis. The other is to acquire an authoritative reference source, and then compare and analyze the data with the authoritative reference source; timeliness is measured by freshness, namely, measured by frequency distribution of the recorded update time; the usability is a measurement standard of the degree to which data can be accessed and used, and in this embodiment, "easy-to-use", "basically easy-to-use", "not easy-to-use" is adopted as an evaluation level; maintainability is a measure of the extent to which data can be updated, maintained and managed, with "maintainable", "basic maintainable", "non-maintainable" being used as an evaluation scale.
Further, the filling rate includes: fill data fill rate B, b=b 0 /B 1 ，B 0 Number of necessary field for value, B 1 To fill the total number of fields. In the evaluation, when the data analysis is performed on the filling rate, the analysis is particularly required to analyze the filling rate B of the necessary filling data, and if the filling rate B of the necessary filling data is less than 100%, the filling rate of a single field and the filling rate of a specific series of associated fields can be further analyzed.
Specifically, as shown in fig. 1, the data uploading module includes a plurality of data uploading sub-modules 31, and the plurality of data uploading sub-modules 31 are in one-to-one correspondence with the quality evaluation sub-module 22 and the data acquisition sub-module 12, and the data uploading sub-modules 31 are used for uploading the mass transfer amount evaluation sub-module 22 to evaluate qualified census data.
When general investigation is performed, the data acquisition organization module 11 distributes data items to be counted to a plurality of data acquisition sub-modules 12 at the highest level, and then sequentially and gradually distributes the data items to all the data acquisition sub-modules 12; after the data acquisition sub-module 12 acquires the census data, the corresponding quality evaluation sub-module 22 evaluates the census data to be qualified, and the corresponding data uploading sub-module 31 uploads the census data to the upper-level data acquisition sub-module 12; the lowest-level data acquisition sub-modules 12 perform quality assessment on the census data acquired by the lowest-level data acquisition sub-modules through the corresponding quality assessment sub-modules 22, any other data acquisition sub-module 12 should perform quality assessment on the census data acquired by the lowest-level data acquisition sub-modules and the census data uploaded by the next-level data acquisition sub-modules through the corresponding quality assessment sub-modules 22, and the data acquisition organization module 11 performs quality assessment on all census data through the quality assessment total module 21.
Of course, when quality evaluation is performed on census data, not all census data collected by the data collection sub-module 12 need to be evaluated on all indexes, and the most focused index should be selected according to actual situations to be evaluated. For example, each level of data acquisition sub-module 12, via quality assessment sub-module 22, may focus on assessing the data product to direct the data replenishment; the data collection and organization module 11 can cover all dimensions of data production environment, data production process, data products and the like through the quality evaluation total module 21, so that not only the quality of census data per se is evaluated, but also prospective proposals can be made on how to organize future data census work.
Above, the coupling system for census data acquisition and quality assessment according to the embodiment of the invention is described with reference to fig. 1, and not only is a qualitative and quantitative combined method adopted to carry out data quality assessment, but also the census data acquired at each level can be timely assessed and timely corrected, so that efficient coupling of data acquisition and quality assessment is realized, the scientificity and accuracy of census data are ensured, and the confidence is improved.
It should be noted that in this specification the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that comprises an element.
While the present invention has been described in detail through the foregoing description of the preferred embodiment, it should be understood that the foregoing description is not to be considered as limiting the invention. Many modifications and substitutions of the present invention will become apparent to those of ordinary skill in the art upon reading the foregoing. Accordingly, the scope of the invention should be limited only by the attached claims.
Claims (1)
1. A census data acquisition and quality assessment coupling system, comprising:
the data acquisition module is used for acquiring census data;
the data acquisition module comprises a data acquisition organization module and a plurality of data acquisition sub-modules, the plurality of data acquisition sub-modules are divided into N levels, each level comprises a plurality of data acquisition sub-modules, each data acquisition sub-module of the previous level corresponds to the data acquisition sub-module of the next level, and the data uploading module uploads general survey data step by step until the data acquisition organization module;
the quality evaluation module is used for evaluating the census data, and if the census data are unqualified, the quality evaluation module returns to the data acquisition module for re-acquisition or processing;
the data uploading module uploads the data which is evaluated to be qualified by the quality evaluation module;
the quality evaluation module comprises a quality evaluation total module and a plurality of quality evaluation sub-modules, wherein the quality evaluation sub-modules are in one-to-one correspondence with the data acquisition sub-modules, the quality evaluation total module corresponds to the data acquisition organization module, each quality evaluation sub-module evaluates the census data which are acquired and/or received by the corresponding data uploading module and are uploaded by the data uploading module, and the quality evaluation total module evaluates the census data which are received by the data acquisition organization module;
the data uploading module comprises a plurality of data uploading sub-modules, the data uploading sub-modules are in one-to-one correspondence with the quality evaluation sub-modules and the data acquisition sub-modules, and the data uploading sub-modules are used for uploading the census data which are qualified by the quality evaluation sub-modules;
the quality evaluation module evaluates the census data by adopting a quality evaluation model, wherein the quality evaluation model comprises a data production environment dimension, a data production process dimension and a data product dimension;
the data production environment dimensions include: the soundness of the screening system, the independence of screening institutions, the expertise of screening personnel and the advancement of screening tool means; the data production environment dimension is a qualitative dimension;
the data production process dimension includes: a data conciseness index, a data repeatability index and a data acquisition automation ratio index; the data conciseness index comprises: the necessary statistics term proportion P and the invalid data rate Q; p=1-P 0 /P 1 ，P 0 For the number of data items counted by other relevant departments, P 1 Counting the number of data items to be counted; q=q 0 /Q 1 ，Q 0 For the number of data items which do not need to be filled but are actually filled, Q 1 The number of the data items actually filled is calculated;
the data product dimensions include: integrity index, accuracy index, timeliness index, usability index, maintainability index;
the integrity indicator comprises: filling rate, single field filling rate and specific series of associated field filling rates;
the filling rate comprises: fill data fill rate B, b=b 0 /B 1 ，B 0 Number of necessary field for value, B 1 To fill the total number of fields.
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