Data dictionary implementation method and system based on standard or technical document and medium

Abstract

The invention relates to the technical field of data dictionaries, in particular to a data dictionary implementation method and system based on standards or technical documents and a medium, which comprise data classification, data standards, data elements and data sets, and solves the problems of different standards, standard missing and the like of multi-source data fusion in the prior art. Standardized and normalized management of contents such as standard texts, terms, metadata, code sets, data elements, data sets, data models and data rules is realized by taking'data element fields' as a core, and a set of national transverse and longitudinal integrated standard data dictionary system is gradually formed, so that the complexity and the treatment cost of historical stock data treatment are reduced; the standardization and standardization level of a new system and data in the future is improved, and credible data with higher quality and lower cost is provided in public data authorization operation in the future.

Description

Technical Field

[0001] The present invention relates to the technical field of data dictionaries, and in particular to a method, system and medium for realizing a data dictionary based on standards or technical documents. Background Art

[0002] In the current digital construction, a series of data standards related to digital construction have been formulated. However, in the actual information operation process, there are still problems such as insufficient systematicness of data standards, difficulties in testing, evaluation and governance, and low data quality, which have become prominent problems restricting the in-depth development of digitalization.

[0003] Due to the lack of a unified organizational and management mechanism and a lack of unified data standards, confusion has arisen in system initialization, operation and maintenance, analysis, and utilization, resulting in poor data quality, deviations in statistical analysis and management work, and the need to clean and integrate data before it can be used across departments, levels, and fields. This has raised the technical threshold for data governance and increased the workload and financial investment in data governance.

[0004] Therefore, it is necessary to design a data dictionary implementation method, system and medium based on standards or technical documents to solve problems such as inconsistent standards and lack of standards in multi-source data fusion. Through object management and query capabilities, it can help users build a unified standard system, improve the standardization level of data, promote the sharing of data resources among various departments, and give full play to the value of data. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a data dictionary implementation method, system and medium based on standards or technical documents to solve the problems of inconsistent standards and lack of standards in multi-source data fusion. Through the management and query capabilities of objects, it helps users build a unified standard system, improve the standardization level of data, promote the sharing of data resources among various departments, and give full play to the value of data.

[0006] In order to achieve the above object, the present invention provides a data dictionary implementation method based on standards or technical documents:

[0007] Includes data classification, data standards, data elements and data sets;

[0008] S1, data classification includes the following:

[0009] S1-1, data classification management function: supports the maintenance of data classification tree structure and data classification node attributes;

[0010] S1-2, data classification nodes are data classifications from standard documents or user-defined data classifications;

[0011] S1-3, data classification maintenance: supports the management and maintenance of the multi-level tree structure of data classification, as well as the names, classification codes, and reference standard document attributes of nodes at each level;

[0012] S1-4, Statistics and display of data classification-related data standards: View the statistical data and detailed tables of standard documents, terms, data elements, code sets, and data model data standard objects belonging to the specified data classification node;

[0013] S1-5, Data classification application: Standard documents, terminology, data elements, code sets, and data model data standard objects use a unified data classification tree to maintain and filter and display the data classification attributes of the object;

[0014] S2, data standards include the following:

[0015] Support online maintenance of standard documents and standard terminology, structured management of unstructured data, and support each node to report the data standards maintained in the node to the upper node to achieve horizontal sharing between different nodes;

[0016] S2-1, Standard Document Management: Online management of standard documents, maintenance of standard classification and applicable scope attributes, and support for attachment upload and online preview;

[0017] S2-2, statistics and display of related objects: The system provides statistics and viewing of related data in the standard document dimension, and views the statistical information and list display of data elements, terms, code sets, and data models associated with the standard document;

[0018] S2-3, rapid identification of data elements: The system supports rapid identification of standard documents in specific formats. By parsing the configuration of identification parameters such as page range, attribute list and separator, the objects to be stored are selected and attribute mapping is performed. The unstructured data in the document can be quickly converted into structured data, and data element objects can be generated in the system.

[0019] S2-4, Standard terminology management: Supports the maintenance of standard terminology, including the management of term names, English names, definitions, data classifications, and reference standard attributes;

[0020] S3, data elements include the following:

[0021] Including data meta-fields and code sets, which are standard specifications implemented on specific data models and specific data value domains. They support each node to report the data standards maintained in the node to the upper-level node to achieve horizontal sharing between different nodes.

[0022] S3-1, Data element management: By managing the business attributes, technical attributes, and management attributes of data element fields and maintaining the association between data elements and standard documents and code sets, it provides a field-level foundation for standardized modeling, data standard detection, and data standardization conversion tools;

[0023] S3-2, data element original text browsing: the system supports browsing the original text of the standard document page number where the data element is located;

[0024] S3-3, Data element version management: The system supports version management of data element fields and version comparison to view the differences between different versions;

[0025] S3-4, code set management: supports the maintenance of reference standards, data classification, and code item list attributes of code sets; S4, data model includes the following:

[0026] By associating the data model table with the standard data elements, the knowledge of the data model table is accumulated, providing standard support for data modeling, data standard detection and other tasks. In addition to supporting the association of standard data elements, the fields in the model table also support user-defined settings to increase the flexibility and versatility of the functions, and support each node to report the data standards maintained in the node to the upper-level node to achieve horizontal sharing between different nodes.

[0027] S4-1, basic information maintenance: supports the maintenance and management of data model names, data classifications, and reference standard attributes;

[0028] S4-2, Field Maintenance: Supports maintenance of the fields included in the data model, as well as the field's related type, length, precision, primary key, non-null, default value technical metadata, and supports association between fields and standard data elements and code sets;

[0029] S4-3, Index Maintenance: Supports maintenance of indexes and index member fields of data models;

[0030] S4-4, constraint maintenance: supports maintenance of constraint names, constraint types, and constraint member fields of the data model.

[0031] The present invention also provides a computer system, which is used to run the data dictionary implementation method based on standards or technical documents of the present invention.

[0032] A storage medium is used to store a computer system running the data dictionary implementation method based on standard or technical documents of the present invention.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] Anchoring standards and other public documents make the main contents of the data dictionary, such as data elements, standard codes, and data models, easily accessible, making it easier to enrich the dictionary in a short period of time and to mobilize more editors to simultaneously enrich the data dictionary content.

[0035] Anchoring standards and other authoritative documents provide a basis for the definitions of data elements and data sets, which helps to enhance the authority of the data dictionary.

[0036] Structuring and organizing data specifications makes it easier to find differences or conflicts between data format specifications in different files, and makes it possible to automate the task of detecting these differences.

[0037] Performing data testing or evaluation against structured data specifications will significantly reduce the cost of evaluating data quality or identifying data quality risk points. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a business process diagram of the present invention;

[0039] Figure 2 The data classification management flow chart of the present invention;

[0040] Figure 3 The data standard management flow chart of the present invention;

[0041] Figure 4 The data standard terminology management flow chart of the present invention;

[0042] Figure 5 It is a data element management flow chart of the present invention;

[0043] Figure 6 is a code set management flow chart of the present invention;

[0044] Figure 7 A data model management flow chart of the present invention; DETAILED DESCRIPTION

[0045] The present invention will now be further described with reference to the accompanying drawings.

[0046] See also Figure 1 The present invention provides a data dictionary implementation method based on standards or technical documents:

[0047] Includes data classification, data standards, data elements and data sets;

[0048] S1, data classification includes the following (such as Figure 2 shown):

[0049] S1-1, data classification management function: supports the maintenance of data classification tree structure and data classification node attributes;

[0050] S1-2, data classification nodes are data classifications from standard documents or user-defined data classifications;

[0051] S1-3, data classification maintenance: supports the management and maintenance of the multi-level tree structure of data classification, as well as the names, classification codes, and reference standard document attributes of nodes at each level;

[0052] S1-4, Statistics and display of data classification-related data standards: View the statistical data and detailed tables of standard documents, terms, data elements, code sets, and data model data standard objects belonging to the specified data classification node;

[0053] S1-5, Data classification application: Standard documents, terminology, data elements, code sets, and data model data standard objects use a unified data classification tree to maintain and filter and display the data classification attributes of the object;

[0054] S2, data standards include the following (such as Figure 3 shown):

[0055] Support online maintenance of standard documents and standard terminology, structured management of unstructured data, and support each node to report the data standards maintained in the node to the upper node to achieve horizontal sharing between different nodes;

[0056] S2-1, Standard Document Management: Online management of standard documents, maintenance of standard classification and applicable scope attributes, and support for attachment upload and online preview;

[0057] S2-2, statistics and display of related objects: The system provides statistics and viewing of related data in the standard document dimension, and views the statistical information and list display of data elements, terms, code sets, and data models associated with the standard document;

[0058] S2-3, rapid identification of data elements: The system supports rapid identification of standard documents in specific formats. By parsing the configuration of identification parameters such as page range, attribute list and separator, the objects to be stored are selected and attribute mapping is performed. The unstructured data in the document can be quickly converted into structured data, and data element objects can be generated in the system.

[0059] S2-4, Standard terminology management (such as Figure 4 (shown): Supports maintenance of standard terms, including the name, English name, definition, data classification, and management of reference standard attributes of terms;

[0060] S3, data elements include the following:

[0061] Including data meta-fields and code sets, which are standard specifications implemented on specific data models and specific data value domains. They support each node to report the data standards maintained in the node to the upper-level node to achieve horizontal sharing between different nodes.

[0062] S3-1, data element management (such as Figure 5 As shown in Figure 1), it manages the business attributes, technical attributes, and management attributes of data element fields, and maintains the association between data elements and standard documents and code sets, providing a field-level foundation for standardized modeling, data standard detection, and data standardization conversion tools;

[0063] S3-2, data element original text browsing: the system supports browsing the original text of the standard document page number where the data element is located;

[0064] S3-3, Data element version management: The system supports version management of data element fields and version comparison to view the differences between different versions;

[0065] S3-4, code set management (such as Figure 6 (as shown): supports maintenance of reference standards, data classification, and code item list attributes of code sets;

[0066] S4, the data model includes the following contents (such as Figure 7 shown):

[0067] By associating the data model table with the standard data elements, the knowledge of the data model table is accumulated, providing standard support for data modeling, data standard detection and other tasks. In addition to supporting the association of standard data elements, the fields in the model table also support user-defined settings to increase the flexibility and versatility of the functions, and support each node to report the data standards maintained in the node to the upper-level node to achieve horizontal sharing between different nodes.

[0068] S4-1, basic information maintenance: supports the maintenance and management of data model names, data classifications, and reference standard attributes;

[0069] S4-2, Field Maintenance: Supports maintenance of the fields included in the data model, as well as the field's related type, length, precision, primary key, non-null, default value technical metadata, and supports association between fields and standard data elements and code sets;

[0070] S4-3, Index Maintenance: Supports maintenance of indexes and index member fields of data models;

[0071] S4-4, constraint maintenance: supports maintenance of constraint names, constraint types, and constraint member fields of the data model.

[0072] The present invention also provides a computer system, which is used to run the data dictionary implementation method based on standards or technical documents of the present invention.

[0073] A storage medium is used to store a computer system running the data dictionary implementation method based on standard or technical documents of the present invention.

[0074] The above are only preferred embodiments of the present invention, which are only used to help understand the method and core idea of ​​the present application. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the idea of ​​the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

[0075] The present invention solves the problems of inconsistent standards and lack of standards in multi-source data fusion in the prior art. By taking "data element fields" as the core, it realizes the standardization and normalized management of "standard texts, terminology, metadata, code sets, data elements, data sets, data models, data rules" and other contents, and gradually forms a national horizontally and vertically integrated standard data dictionary system, thereby reducing the complexity and cost of historical stock data governance, improving the standardization and standardization level of new systems and data in the future, and providing higher quality and lower cost trusted data in future public data authorization operations.

Claims

1. A method for implementing a data dictionary based on a standard or technical document, characterized in that: Includes data classification, data standards, data elements and data sets; S1, data classification includes the following: S1-1, data classification management function: supports the maintenance of data classification tree structure and data classification node attributes; S1-2, data classification nodes are data classifications from standard documents or user-defined data classifications; S1-3, data classification maintenance: supports the management and maintenance of the multi-level tree structure of data classification, as well as the names, classification codes, and reference standard document attributes of nodes at each level; S1-4, Statistics and display of data classification-related data standards: View the statistical data and detailed tables of standard documents, terms, data elements, code sets, and data model data standard objects belonging to the specified data classification node; S1-5, Data classification application: Standard documents, terminology, data elements, code sets, and data model data standard objects use a unified data classification tree to maintain and filter and display the data classification attributes of the object; S2, data standards include the following: Support online maintenance of standard documents and standard terminology, structured management of unstructured data, and support each node to report the data standards maintained in the node to the upper node to achieve horizontal sharing between different nodes; S2-1, Standard Document Management: Online management of standard documents, maintenance of standard classification and applicable scope attributes, and support for attachment upload and online preview; S2-2, statistics and display of related objects: The system provides statistics and viewing of related data in the standard document dimension, and views the statistical information and list display of data elements, terms, code sets, and data models associated with the standard document; S2-3, rapid identification of data elements: The system supports rapid identification of standard documents in specific formats. By parsing the configuration of identification parameters such as page range, attribute list and separator, the objects to be stored are selected and attribute mapping is performed. The unstructured data in the document can be quickly converted into structured data, and data element objects can be generated in the system. S2-4, Standard terminology management: Supports the maintenance of standard terminology, including the management of term names, English names, definitions, data classifications, and reference standard attributes; S3, data elements include the following: Including data meta-fields and code sets, which are standard specifications implemented on specific data models and specific data value domains. They support each node to report the data standards maintained in the node to the upper-level node to achieve horizontal sharing between different nodes. S3-1, Data element management: By managing the business attributes, technical attributes, and management attributes of data element fields and maintaining the association between data elements and standard documents and code sets, it provides a field-level foundation for standardized modeling, data standard detection, and data standardization conversion tools; S3-2, data element original text browsing: the system supports browsing the original text of the standard document page number where the data element is located; S3-3, Data element version management: The system supports version management of data element fields and version comparison to view the differences between different versions; S3-4, Code Set Management: Supports maintenance of code set reference standards, data classification, and code item list attributes; S4, the data model includes the following: By associating the data model table with the standard data element, the knowledge accumulation of the data model table is formed, providing standard support for data modeling, data standard detection and other work; in addition to supporting the association of standard data elements, the fields in the model table also support user-defined settings to increase the flexibility and versatility of the functions, and support each node to report the data standards maintained in the node to the upper node to achieve horizontal sharing between different nodes; S4-1, basic information maintenance: supports the maintenance and management of data model names, data classifications, and reference standard attributes; S4-2, Field Maintenance: Supports maintenance of the fields included in the data model, as well as the field's related type, length, precision, primary key, non-null, default value technical metadata, and supports association between fields and standard data elements and code sets; S4-3, Index Maintenance: Supports maintenance of indexes and index member fields of data models; S4-4, constraint maintenance: supports maintenance of constraint names, constraint types, and constraint member fields of the data model.

2. A computer system, characterized in that: The system is used to run the data dictionary implementation method based on standards or technical documents as described in claim 1.

3. A storage medium, characterized in that: The storage medium is used to store the computer system according to claim 2.

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