An automated data element governance method

Abstract

This invention discloses an automated data element governance method, relating to the field of data governance technology. The method involves: organizing the data element list of a logical model, obtaining information items defining the data elements, organizing a list of basic English word roots based on these information items, obtaining basic English word roots, organizing a list of English phrases, and obtaining information items defining the English phrases; during data modeling, obtaining a row of attributes from the logical model, matching the attributes against the data element list in full text, modifying the attributes using the data element standards of the data element list if a match is successful, and segmenting the English text within the attributes into words, sequentially matching the segmented English text according to the priority order of professional phrases, public phrases, and basic word roots, and cyclically obtaining the remaining attributes in the logical model until the matching of all attributes in the logical model is completed.

Description

Technical Field

[0001] This invention discloses a method relating to the field of data governance technology, specifically an automated data element governance method. Background Technology

[0002] A data element, also known as a data unit, is a data unit whose definition, identification, representation, and allowed values ​​are described by a set of attributes. In a given context, it is typically used to construct a semantically correct, independent, and unambiguous information unit representing a specific concept. A data element can be understood as the basic unit of data; arranging several related data elements in a certain order to form a holistic structure constitutes a data model.

[0003] Data modeling is the process of discovering, analyzing, and defining data requirements, which are then represented and communicated through data models. In the context of data warehousing, relational schemas and multidimensional schemas are commonly used for modeling. Each schema consists of three layers: a conceptual model, a logical model, and a physical model.

[0004] During data modeling, if an attribute cannot be matched with an existing data element, expansion is required. Expanding data elements involves translating their English names and short English names. Differences in business understanding and English proficiency among different personnel can easily lead to confusion in data element naming, which can then extend to confusion in model attribute names, causing numerous application problems. Furthermore, relying on manual operations to organize the logical model is inefficient, error-prone, and detrimental to improving the efficiency of matching data elements. Summary of the Invention

[0005] This invention addresses the problems of existing technologies by providing an automated data element governance method, which solves the problems of low efficiency and error-proneness in the process of matching data elements in logical models.

[0006] The specific solution proposed in this invention is as follows:

[0007] This invention provides an automated data element governance method that organizes the data element list of a logical model and obtains the information items defining the data elements.

[0008] Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots.

[0009] Organize a list of English phrases, obtain the information items defining the English phrases, and divide the English phrases into professional phrases and general phrases based on the information items defining the English phrases. The professional phrases are used only in the specified professional fields, while the general phrases are applicable to all fields.

[0010] During data modeling, a row of attributes is obtained from the logical model. The entire text of the attribute is matched against a list of data elements. If a match is successful, the attribute is modified using the data element standards of the aforementioned list. If a match fails, the English text within the attribute is segmented and matched in the following order: professional phrases, common phrases, and basic word roots. If a match is successful, the lower priority list is skipped; otherwise, the segmented text is added to the pending processing list.

[0011] After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards.

[0012] Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

[0013] Furthermore, the automated data element governance method described above, which involves sorting out the data element list of the logical model and obtaining information items defining the data elements, includes:

[0014] The information item includes a number, grouping information, name, English name, short English name, type, and length. The number represents the data element number, the grouping information represents the data element grouping information, the name represents the Chinese name of the data element, the English name and short English name both represent the English name of the data element, the type represents the data element type, and the length represents the data element length.

[0015] Furthermore, the method for automating data meta-governance, which involves compiling a list of basic English word roots, includes:

[0016] The information items for obtaining the list of basic English word roots include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English word root number, the English name represents the English word root, the English abbreviation represents the abbreviation of the English word root, the Chinese name represents the Chinese name corresponding to the English word root, and the Chinese synonym represents the Chinese synonym of the English word root.

[0017] Furthermore, the automated data meta-governance method described above, which involves sorting through a list of English phrases to obtain information items defining the English phrases, includes:

[0018] The information items obtained include a number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English phrase number, the English name represents the English phrase, the English abbreviation represents the abbreviation of the English phrase, the Chinese name represents the Chinese equivalent of the English phrase, and the Chinese synonym represents the Chinese equivalent of the English phrase.

[0019] Furthermore, in the automated data element governance method described above, the data element list, the English basic word root list, and the English phrase list are initialized during the data modeling process, and a row of attributes in the logical model is obtained, including:

[0020] The data element list is matched against the full text of the attribute. If a match is found, the attribute is modified using the data element criteria in the data element list. If a match fails, the English text within the attribute is segmented into words.

[0021] The system matches English professional phrases based on word segmentation. If a match is successful, it skips the matching of common phrases and basic word roots. If a match fails, it matches English common phrases based on word segmentation. If a match is successful, it skips the matching of basic word roots. If a match fails, it matches English basic word roots based on word segmentation. If a match is successful, the word segmentation matching is completed. If no match can be found, the word segmentation is added to the pending list.

[0022] This invention also provides an automated data element governance device, comprising a sorting module and a matching module.

[0023] The sorting module sorts out the list of data elements in the logical model and obtains the information items defining the data elements.

[0024] Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots.

[0025] Organize a list of English phrases, obtain the information items defining the English phrases, and divide the English phrases into professional phrases and general phrases based on the information items defining the English phrases. The professional phrases are used only in the specified professional fields, while the general phrases are applicable to all fields.

[0026] During data modeling, the matching module retrieves a row of attributes from the logical model and performs a full-text matching of the attribute against a list of data elements. If a match is successful, the attribute is modified using the data element standards of the aforementioned list. If a match fails, the English text within the attribute is segmented and matched in the following order: specialized phrases, general phrases, and basic word roots. If a match is successful, the lower priority list is skipped; otherwise, the segmented text is added to the pending processing list.

[0027] After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards.

[0028] Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

[0029] Furthermore, in the automated data element governance device, the sorting module sorts the data element list of the logical model and obtains the information items defining the data elements, including:

[0030] The information item includes a number, grouping information, name, English name, short English name, type, and length. The number represents the data element number, the grouping information represents the data element grouping information, the name represents the Chinese name of the data element, the English name and short English name both represent the English name of the data element, the type represents the data element type, and the length represents the data element length.

[0031] Furthermore, the sorting module in the automated data element governance device sorts out a list of basic English word roots, including:

[0032] The information items for obtaining the list of basic English word roots include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English word root number, the English name represents the English word root, the English abbreviation represents the abbreviation of the English word root, the Chinese name represents the Chinese name corresponding to the English word root, and the Chinese synonym represents the Chinese synonym of the English word root.

[0033] Furthermore, in the automated data element governance device, the sorting module sorts the list of English phrases and obtains information items defining the English phrases, including:

[0034] The information items obtained include a number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English phrase number, the English name represents the English phrase, the English abbreviation represents the abbreviation of the English phrase, the Chinese name represents the Chinese equivalent of the English phrase, and the Chinese synonym represents the Chinese equivalent of the English phrase.

[0035] Furthermore, in the automated data element governance device, the matching module initializes the data element list, the English basic word root list, and the English phrase list during the data modeling process, and obtains a row of attributes in the logical model, including:

[0036] The data element list is matched against the full text of the attribute. If a match is found, the attribute is modified using the data element criteria in the data element list. If a match fails, the English text within the attribute is segmented into words.

[0037] The system matches English professional phrases based on word segmentation. If a match is successful, it skips the matching of common phrases and basic word roots. If a match fails, it matches English common phrases based on word segmentation. If a match is successful, it skips the matching of basic word roots. If a match fails, it matches English basic word roots based on word segmentation. If a match is successful, the word segmentation matching is completed. If no match can be found, the word segmentation is added to the pending list.

[0038] The advantages of this invention are:

[0039] This invention provides an automated data element governance method, extending a reverse-engineering approach. During the data modeling phase, it automatically derives data element definitions from model attributes, significantly reducing the workload of data element standard governance, improving translation quality, and minimizing the possibility of incorrect matching. It achieves automated model attribute matching of data elements, allowing modelers to focus solely on the Chinese business meaning of model attributes, improving modeling quality and efficiency. The root words, word segmentation, and other content in the data element definition process have the characteristics of accumulation and reuse, avoiding the need to start the governance work from scratch when integrating new industry or business data. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the initialization process of the method of the present invention.

[0041] Figure 2 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0042] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0043] The word segmentation involved in this invention is the process of recombinizing a continuous sequence of characters into a sequence of words according to certain rules. Chinese word segmentation refers to word segmentation that exists due to the special characteristics of Chinese basic grammar.

[0044] A root word is the most basic part that makes up a word; it is the common etymology of many words and has a basic lexical meaning. Root words generally have the following characteristics:

[0045] 1. It exists independently and is the smallest morpheme component of a word.

[0046] 2. It carries a fixed meaning and represents a word or concept.

[0047] 3. It cannot be broken down into smaller morphemes.

[0048] 4. As an affix or prefix, it combines with other affixes to form words.

[0049] 5. A single root word can give rise to multiple related words.

[0050] Synonyms are two or more words that have the same or similar meanings. Synonyms have the following main characteristics:

[0051] 1. Words with the same or similar meanings can be used interchangeably without affecting the main meaning of the sentence. For example, "beautiful" and "pretty" are synonyms.

[0052] 2. They have the same part of speech, namely nouns, verbs, etc.

[0053] 3. The style or emotional connotation may differ. For example, "see" and "observe" are synonyms, but their styles are different.

[0054] 4. The scope can be different. For example, "animal" and "beast" are synonyms, but "animal" has a broader scope.

[0055] 5. A word can have multiple synonyms.

[0056] A phrase is a grammatical combination of words, and its main characteristics are:

[0057] 1. Consists of two or more words, generally not exceeding five words.

[0058] 2. There are grammatical relationships between words, and they conform to a certain syntactic structure.

[0059] 3. A phrase cannot stand alone as a sentence; it needs to be combined with other components of the sentence.

[0060] 4. A phrase has a relatively complete semantic meaning, expressing a concept or meaning.

[0061] This invention provides an automated data element governance method that organizes the data element list of a logical model and obtains the information items defining the data elements.

[0062] Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots.

[0063] Organize a list of English phrases, obtain the information items defining the English phrases, and divide the English phrases into professional phrases and general phrases based on the information items defining the English phrases. The professional phrases are used only in the specified professional fields, while the general phrases are applicable to all fields.

[0064] During data modeling, a row of attributes is obtained from the logical model. The entire text of the attribute is matched against a list of data elements. If a match is successful, the attribute is modified using the data element standards of the aforementioned list. If a match fails, the English text within the attribute is segmented and matched in the following order: professional phrases, common phrases, and basic word roots. If a match is successful, the lower priority list is skipped; otherwise, the segmented text is added to the pending processing list.

[0065] After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards.

[0066] Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

[0067] The method of this invention enables automatic mapping of attributes to associated data elements in the logical model and automatic supplementation of missing data elements, which greatly reduces the workload of manually defining and matching data elements, reduces omissions, duplicate definitions, and incorrect definitions caused by manual matching, and improves the quality of work.

[0068] In specific applications, in some embodiments of the method of the present invention, the following can be referred to when performing automated data element governance:

[0069] Step 1: Organize the data element list of the logical model and obtain the information items defining the data elements.

[0070] Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots.

[0071] By compiling a list of English phrases and obtaining the information items defining the English phrases, the English phrases are divided into professional phrases and general phrases based on the information items defining the English phrases. The professional phrases are used only in the specified professional fields, while the general phrases are applicable to all fields.

[0072] Furthermore, the process of sorting out the data element list of the logical model and obtaining the information items defining the data elements includes:

[0073] Obtain information items, which include number, grouping information, name, English name, short English name, type, and length. The number represents the data element number, the grouping information represents the data element grouping information, the name represents the Chinese name of the data element, the English name and short English name both represent the English name of the data element, the type represents the data element type, and the length represents the data element length. Refer to Table 1.

[0074] Table 1

[0075] serial number Data element number Grouping information Data element grouping information can contain multiple levels. name Data element Chinese naming English name Data element English naming English short name Data element English naming type Data Metatype length Data element length (some types allow null values) Related Dictionaries

[0076] Furthermore, the aforementioned list of basic English word roots includes:

[0077] The information items for obtaining the list of basic English word roots include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English word root number, the English name represents the English word root, the English abbreviation represents the abbreviation of the English word root, the Chinese name represents the Chinese name corresponding to the English word root, and the Chinese synonym represents the Chinese synonym of the English word root. See Table 2 for reference.

[0078] Table 2

[0079] serial number English word root numbering English English word roots English abbreviations Abbreviations of English word roots Chinese Chinese translations of English word roots Chinese synonyms The number of Chinese synonyms corresponding to English word roots can be zero or more. Remark

[0080] Furthermore, the process of sorting through the list of English phrases and obtaining information items defining the English phrases includes:

[0081] The information items obtained include number, English, English abbreviation, Chinese and Chinese synonyms. The number represents the English phrase number, the English represents the English phrase, the English abbreviation represents the abbreviation of the English phrase, the Chinese represents the Chinese corresponding to the English phrase, and the Chinese synonyms represent the Chinese synonyms corresponding to the English phrases, as shown in Table 3.

[0082] Table 3

[0083] serial number English phrase number English English phrases English abbreviations Abbreviations of English phrases Chinese English phrases and their corresponding Chinese translations Chinese synonyms The number of Chinese synonyms for an English phrase can be zero or more. Remark

[0084] Step 2: During data modeling, initialize the data element list, the English basic word root list, and the English phrase list. Obtain one row of attributes from the logical model. Match the full text of the attributes against the data element list. If a match is successful, modify the attribute using the data element standards of the data element list. If a match fails, segment the English text within the attribute. Perform word segmentation and matching in the order of priority: professional phrases, general phrases, and basic word roots. If a match is successful, skip the lower priority list. If no match is found, add the segmented text to the pending list. Specifically:

[0085] The data element list is matched against the full text of the attribute. If a match is found, the attribute is modified using the data element criteria in the data element list. If a match fails, the English text within the attribute is segmented into words.

[0086] The system matches English professional phrases based on word segmentation. If a match is successful, it skips the matching of common phrases and basic word roots. If a match fails, it matches English common phrases based on word segmentation. If a match is successful, it skips the matching of basic word roots. If a match fails, it matches English basic word roots based on word segmentation. If a match is successful, the word segmentation matching is completed. If no match can be found, the word segmentation is added to the pending list.

[0087] After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards.

[0088] Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

[0089] This invention also provides an automated data element governance device, comprising a sorting module and a matching module.

[0090] The sorting module sorts out the list of data elements in the logical model and obtains the information items defining the data elements.

[0091] Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots.

[0092] Organize a list of English phrases, obtain the information items defining the English phrases, and divide the English phrases into professional phrases and general phrases based on the information items defining the English phrases. The professional phrases are used only in the specified professional fields, while the general phrases are applicable to all fields.

[0093] During data modeling, the matching module retrieves a row of attributes from the logical model and performs a full-text matching of the attribute against a list of data elements. If a match is successful, the attribute is modified using the data element standards of the aforementioned list. If a match fails, the English text within the attribute is segmented and matched in the following order: specialized phrases, general phrases, and basic word roots. If a match is successful, the lower priority list is skipped; otherwise, the segmented text is added to the pending processing list.

[0094] After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards.

[0095] Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

[0096] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0097] Similarly, the device of this invention extends the reverse processing flow. During the data modeling stage, it automatically derives data element definitions based on model attributes, significantly reducing the workload of data element standardization, improving translation quality, and reducing the possibility of incorrect matching. It achieves automated model attribute matching of data elements, allowing modelers to focus solely on the Chinese business meaning of model attributes, improving modeling quality and efficiency. The root words, word segmentation, and other content in the data element definition process have the characteristics of accumulation and reuse, avoiding the need to start the process from scratch when integrating new industry or business data.

[0098] It should be noted that not all steps and modules in the above processes and device structures are mandatory; some steps or modules can be omitted as needed. The execution order of each step is not fixed and can be adjusted as required. The system structure described in the above embodiments can be a physical structure or a logical structure. That is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or they may be jointly implemented by certain components in multiple independent devices.

[0099] The above-described embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. The scope of protection of the present invention is defined by the claims.

Claims

1. An automated data element governance method, characterized by Organize the data element list of the logical model and obtain the information items defining the data elements. The information items include number, grouping information, name, English name, short English name, type and length. The number represents the data element number, the grouping information represents the data element grouping information, the name represents the Chinese name of the data element, the English name and short English name both represent the English name of the data element, the type represents the data element type, and the length represents the data element length. Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots. Organize the list of English phrases and obtain the information items for the definition of the English phrases. The information items for the definition of the English phrases include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English phrase number, the English name represents the English phrase, the English abbreviation represents the abbreviation of the English phrase, the Chinese name represents the Chinese name corresponding to the English phrase, and the Chinese synonym represents the Chinese synonym corresponding to the English phrase. Based on the information items defined in the English phrase definition, English phrases are divided into professional phrases and general phrases. The professional phrases are used only in specific professional fields, while the general phrases are applicable to all fields. During data modeling, a row of attributes in the logical model is obtained. The entire data element list is matched against the attribute. If a match is successful, the attribute is modified using the data element standards of the data element list. If a match fails, the English text within the attribute is segmented. Segmentation and matching are performed sequentially according to the priority order of professional phrases, common phrases, and basic word roots. If a match is successful, the lower priority list is skipped; if no match is found, the segmented text is added to the pending list. During data modeling, the data element list, the English basic word root list, and the English phrase list are initialized, and a row of attributes in the logical model is obtained, including: The data element list is matched against the full text of the attribute. If a match is found, the attribute is modified using the data element criteria in the data element list. If a match fails, the English text within the attribute is segmented into words. The process involves matching English professional phrases based on word segmentation. If a match is successful, the matching of common phrases and basic word roots is skipped. If a match fails, the process continues to match English common phrases based on word segmentation. If a match is successful, the matching of basic word roots is skipped. If a match fails, the process continues to match English basic word roots based on word segmentation. If a match is successful, the word segmentation matching is completed. If no match can be found, the word segmentation is added to the pending list. After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards. Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

2. The method of claim 1, wherein the method further comprises: The aforementioned list of basic English word roots includes: The information items for obtaining the list of basic English word roots include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English word root number, the English name represents the English word root, the English abbreviation represents the abbreviation of the English word root, the Chinese name represents the Chinese name corresponding to the English word root, and the Chinese synonym represents the Chinese synonym of the English word root.

3. An automated data element governance apparatus, characterized by The sorting module and the matching module, The sorting module sorts out the data element list of the logical model and obtains the information items defining the data elements. The information items include number, grouping information, name, English name, short English name, type and length. The number represents the data element number, the grouping information represents the data element grouping information, the name represents the Chinese name of the data element, the English name and short English name both represent the English name of the data element, the type represents the data element type, and the length represents the data element length. Based on the information items defined in the data element definition, a list of basic English word roots is compiled to obtain the basic English word roots. Organize the list of English phrases and obtain the information items for the definition of the English phrases. The information items for the definition of the English phrases include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English phrase number, the English name represents the English phrase, the English abbreviation represents the abbreviation of the English phrase, the Chinese name represents the Chinese name corresponding to the English phrase, and the Chinese synonym represents the Chinese synonym corresponding to the English phrase. Based on the information items defined in the English phrase definition, English phrases are divided into professional phrases and general phrases. The professional phrases are used only in specific professional fields, while the general phrases are applicable to all fields. During data modeling, the matching module retrieves a row of attributes from the logical model and performs full-text matching of the attribute against the data element list. If a match is successful, the attribute is modified using the data element standards of the data element list. If a match fails, the English text within the attribute is segmented and matched sequentially according to the priority order of professional phrases, common phrases, and basic word roots. If a match is successful, the lower priority list is skipped; if no match is found, the segmented text is added to the pending list. The matching module initializes the data element list, the English basic word root list, and the English phrase list during data modeling and retrieves a row of attributes from the logical model, including: The data element list is matched against the full text of the attribute. If a match is found, the attribute is modified using the data element criteria in the data element list. If a match fails, the English text within the attribute is segmented into words. The process involves matching English professional phrases based on word segmentation. If a match is successful, the matching of common phrases and basic word roots is skipped. If a match fails, the process continues to match English common phrases based on word segmentation. If a match is successful, the matching of basic word roots is skipped. If a match fails, the process continues to match English basic word roots based on word segmentation. If a match is successful, the word segmentation matching is completed. If no match can be found, the word segmentation is added to the pending list. After all word segmentation is matched, each word is generated into its English name and short English name. The type and length are obtained from the logical model, new data element standards are defined, and the English names of attributes in the logical model are updated using the new data element standards. Loop through the remaining attributes in the logical model until the matching of attributes in the logical model is complete.

4. The automated data element governance apparatus of claim 3, wherein The sorting module sorts out a list of basic English word roots, including: The information items for obtaining the list of basic English word roots include number, English name, English abbreviation, Chinese name, and Chinese synonym. The number represents the English word root number, the English name represents the English word root, the English abbreviation represents the abbreviation of the English word root, the Chinese name represents the Chinese name corresponding to the English word root, and the Chinese synonym represents the Chinese synonym of the English word root.

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