Data classification method and device for surface mine

Abstract

The invention provides a surface mine data classification method and device, and the method comprises the steps: obtaining data classification indication information corresponding to a surface mine, formulating a data checking template according to the data classification indication information, and carrying out the data resource checking of the surface mine according to the data checking template, the method comprises the steps of obtaining metadata information of related data of the surface mine, performing business process carding on the surface mine to determine a plurality of data subject domains, and performing data classification processing according to the metadata information and the plurality of data subject domains to obtain a data classification result. By implementing the method disclosed by the invention, the data sharing of each stage of the surface mine can be realized, the data management is convenient, the data processing efficiency is improved, and reliable guidance information is provided for the design of a data model, the design of a data warehouse and the cleaning and storage of the data.

Description

Technical Field

[0001] The present disclosure relates to the technical field of smart mines, and in particular to a data classification method and device for open-pit mines. Background Art

[0002] With the development of information technology, open-pit coal mining companies are facing the generation and accumulation of massive amounts of data, which has become a key asset and competitive advantage. As a traditional energy industry with a long history, the coal industry has maintained a traditional production model with a very low level of modernization and a relatively backward level of informatization. Therefore, it is urgent to classify data from the traditional coal industry and establish a unified and complete data classification method to achieve open-pit mine data classification.

[0003] In related technologies, a data classification model training method is usually used to process the training data set, determine the target data set, construct a data classification model, train the data classification model using the target data set, generate a target data classification model, and use the target data classification model to perform data classification.

[0004] In this way, the data classification effect is not good, and there are cases of inclusion or partial inclusion between data classifications. Summary of the Invention

[0005] The present disclosure aims to solve one of the technical problems in the related art at least to a certain extent.

[0006] To this end, the purpose of the present disclosure is to propose a data classification method, device, computer equipment and storage medium for open-pit mines, which can realize data sharing at all stages of open-pit mines, facilitate data management, improve data processing efficiency, and provide reliable guidance information for the design of data models, the design of data warehouses, and the cleaning and storage of data.

[0007] To achieve the above-mentioned purpose, the data classification method for open-pit mines proposed in the first embodiment of the present disclosure includes:

[0008] Obtaining data classification indication information corresponding to the open-pit mine;

[0009] Formulate a data inventory template based on the data classification indication information;

[0010] Performing a data resource inventory on the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data;

[0011] Sorting out the business processes of the open-pit mine to identify multiple data subject domains;

[0012] Data classification processing is performed according to the metadata information and the multiple data subject domains to obtain a data classification result.

[0013] To achieve the above-mentioned purpose, a data classification device for an open-pit mine proposed in a second embodiment of the present disclosure includes:

[0014] An acquisition module, used to acquire data classification indication information corresponding to the open-pit mine;

[0015] A template formulation module, configured to formulate a data inventory template according to the data classification indication information;

[0016] a data resource inventory module, configured to perform a data resource inventory on the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data;

[0017] A determination module, configured to sort out the business processes of the open-pit mine to determine a plurality of data subject domains;

[0018] The classification processing module is used to perform data classification processing according to the metadata information and the multiple data subject domains to obtain a data classification result.

[0019] The computer device proposed in the third embodiment of the present disclosure includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the data classification method for open-pit mines proposed in the first embodiment of the present disclosure is implemented.

[0020] The fourth embodiment of the present disclosure proposes a non-transitory computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the data classification method for an open-pit mine proposed in the first embodiment of the present disclosure is implemented.

[0021] The fifth embodiment of the present disclosure provides a computer program product. When the instructions in the computer program product are executed by a processor, the data classification method for open-pit mines provided in the first embodiment of the present disclosure is executed.

[0022] The data classification method, device, computer equipment and storage medium for open-pit mines provided by the present disclosure obtain data classification indication information corresponding to the open-pit mine, formulate a data inventory template based on the data classification indication information, and conduct a data resource inventory of the open-pit mine according to the data inventory template to obtain metadata information of data related to the open-pit mine. The business process of the open-pit mine is sorted out to determine multiple data subject domains, and data classification processing is performed based on the metadata information and the multiple data subject domains to obtain data classification results. In this way, data sharing at various stages of the open-pit mine can be achieved, data management can be facilitated, data processing efficiency can be improved, and reliable guidance information can be provided for the design of data models, the design of data warehouses, and the cleaning and storage of data.

[0023] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present disclosure will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1 This is a flow chart of a data classification method for an open-pit mine proposed in one embodiment of the present disclosure;

[0026] Figure 2 is a flow chart of a data classification method for an open-pit mine proposed in another embodiment of the present disclosure;

[0027] Figure 3 It is a schematic diagram of the data classification management process proposed in this disclosure;

[0028] Figure 4 This is a schematic structural diagram of a data classification device for an open-pit mine proposed in one embodiment of the present disclosure;

[0029] Figure 5 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0030] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present disclosure and are not to be construed as limiting the present disclosure. On the contrary, the embodiments of the present disclosure include all variations, modifications, and equivalents that fall within the spirit and scope of the appended claims.

[0031] Figure 1 1 is a flow chart of a data classification method for an open-pit mine proposed in an embodiment of the present disclosure.

[0032] It should be noted that the executor of the data classification method for open-pit mines in this embodiment is the data classification device for open-pit mines. The device can be implemented by software and / or hardware. The device can be configured in a computer device. The computer device can include but is not limited to a terminal, a server, etc. For example, the terminal can be a mobile phone, a handheld computer, etc.

[0033] like Figure 1 As shown in Figure 2, the data classification method for this open-pit mine includes:

[0034] S101: Acquire data classification indication information corresponding to the open-pit mine.

[0035] Among them, the data classification instruction information may refer to the instruction information related to data classification issued by the management entity corresponding to the open-pit mine, such as data classification management-related systems, guidelines, implementation details, etc., and there is no restriction on this.

[0036] In the disclosed embodiment, the platform informationization leadership group may formulate data classification and classification management-related systems, guidelines, implementation details, etc. as the above-mentioned data classification indication information.

[0037] In the implementation of the present disclosure, when data classification indication information corresponding to an open-pit mine is obtained, a reliable execution basis can be provided for a subsequent data inventory process.

[0038] S102: Develop a data inventory template based on the data classification instruction information.

[0039] The data inventory template refers to a template used for data inventory, for example, it may be a technical attribute inventory table for an open-pit mine.

[0040] In the embodiment of the present disclosure, when a data inventory template is formulated based on the data classification indication information, reliable reference information can be provided for the data collection process.

[0041] S103: performing a data resource inventory of the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data.

[0042] Metadata refers to data about data, describing its characteristics, attributes, sources, quality, structure, relationships, and usage. In other words, metadata describes and explains data, helping people understand and manage it.

[0043] In this disclosed embodiment, after conducting an inventory of open-pit mine data resources according to the data inventory template and obtaining metadata information related to the open-pit mine data, data resources can be better understood and utilized, improving data discoverability, accuracy, and credibility. Metadata management and application also play a key role in data warehouses, data lakes, data integration systems, and other systems, helping to ensure that data resources are correctly understood and used.

[0044] S104: Sorting out the business processes of the open-pit mine to identify multiple data subject domains.

[0045] Among them, data subject domain refers to the concept of classifying and organizing relevant data according to specific topics or business areas in the fields of data management and data analysis.

[0046] In the disclosed embodiment, when business processes of an open-pit mine are sorted out to determine multiple data subject domains, the applicability of the obtained multiple data subject domains to the business conditions of the open-pit mine can be effectively improved, thereby ensuring the data classification effect.

[0047] S105: Perform data classification processing according to the metadata information and multiple data subject domains to obtain a data classification result.

[0048] That is, in the embodiment of the present disclosure, after obtaining metadata information and multiple data subject domains, data classification processing can be performed based on the metadata information and the multiple data subject domains to obtain a data classification result.

[0049] In this embodiment, by obtaining data classification indication information corresponding to the open-pit mine, a data inventory template is formulated according to the data classification indication information, and a data resource inventory of the open-pit mine is performed according to the data inventory template to obtain metadata information of the open-pit mine-related data, and the business process of the open-pit mine is sorted out to determine multiple data subject domains. Data classification processing is performed based on the metadata information and the multiple data subject domains to obtain data classification results. In this way, data sharing at all stages of the open-pit mine can be achieved, data management is facilitated, data processing efficiency is improved, and reliable guidance information is provided for the design of data models, the design of data warehouses, and the cleaning and storage of data.

[0050] Figure 2 It is a flowchart of a data classification method for an open-pit mine proposed in another embodiment of the present disclosure.

[0051] like Figure 2 As shown in Figure 2, the data classification method for this open-pit mine includes:

[0052] S201: Acquire data classification indication information corresponding to the open-pit mine.

[0053] S202: Develop a data inventory template based on the data classification instruction information.

[0054] S203: performing a data resource inventory of the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data.

[0055] The description of S201 - S203 can be found in the above embodiment and will not be repeated here.

[0056] S204: sorting out the business processes of the open-pit mine to obtain process information collection results.

[0057] Optionally, in some embodiments, when combing the business processes of open-pit mines to obtain process information collection results, a business node can be established, and according to the different responsibilities and tasks assumed, a responsibility division node can be established under the business node. According to the work to be completed in performing the duties, a management activity node can be established under the responsibility division node. According to the specific links of the activity, a work step node can be established under the management activity node. According to the name of the relevant information form, an information form node can be established under the work step node. In this way, the business process can be combed clearly, accurately and quickly to effectively improve the reliability of the obtained process information collection results.

[0058] S205: Generate multiple business process diagrams based on the process information collection results.

[0059] Among them, the business process diagram can be a first- and second-level business process diagram that depicts the business functions of each open-pit mine.

[0060] In the embodiment of the present disclosure, when multiple business process diagrams are generated based on the process information collection results, reliable reference information can be provided for the subsequent determination of business relationship information.

[0061] S206: Determine business relationship information based on multiple business process diagrams.

[0062] Optionally, in some embodiments, the business relationship information includes: macro-level planning and program management information; production management information; and management element information.

[0063] S207: Determine multiple data subject domains based on the business relationship information.

[0064] That is, in the embodiments of the present disclosure, multiple data subject domains can be determined based on business relationship information at different levels to ensure the practicality of the obtained multiple data subject domains at different levels.

[0065] Optionally, in some embodiments, the multiple data subject domains include: production, equipment, personnel, safety, environmental protection, transportation and marketing, materials, project management, and finance.

[0066] That is to say, in the embodiment of the present disclosure, the business process of the open-pit mine can be sorted out to obtain the process information collection results, and multiple business process diagrams can be generated based on the process information collection results. Business relationship information can be determined based on the multiple business process diagrams, and multiple data subject domains can be determined based on the business relationship information. Therefore, the reliability of the obtained data subject domain can be effectively improved in combination with the mine business process.

[0067] S208: Perform data classification processing based on the metadata information and multiple data subject domains to obtain a data classification result.

[0068] The description of S208 can be found in the above embodiment and will not be repeated here.

[0069] S209: Review the data classification results.

[0070] S210: If approved, the data classification results will be published.

[0071] S211: If the review fails, the data classification results will be adjusted.

[0072] That is to say, in the embodiment of the present disclosure, after obtaining the data classification result, the data classification result can be reviewed. If the review is passed, the data classification result will be published and processed. If the review is not passed, the data classification result will be adjusted. In this way, data assets can be effectively managed, and the integrity, rationality and applicability of the data classification system design can be tested, and the data classification system can be supplemented, improved, and version managed and maintained.

[0073] In this embodiment, the business processes of an open-pit mine are sorted to obtain process information collection results. Based on the process information collection results, multiple business process diagrams are generated. Business relationship information is determined based on the multiple business process diagrams. Based on the business relationship information, multiple data subject domains are determined. In this way, the reliability of the obtained data subject domains can be effectively improved by combining the business processes of the mine. Business nodes are established, and according to the different responsibilities and tasks, responsibility division nodes are established under the business nodes. According to the work to be completed in fulfilling the responsibilities, management activity nodes are established under the responsibility division nodes. According to the specific links of the activities, work step nodes are established under the management activity nodes. According to the names of the relevant information forms, information form nodes are established under the work step nodes. In this way, the business processes can be sorted clearly, accurately, and quickly, effectively improving the reliability of the obtained process information collection results. The data classification results are reviewed. If the review is passed, the data classification results are published and processed. If the review is not passed, the data classification results are adjusted. In this way, data assets can be effectively managed, the integrity, rationality, and applicability of the data classification system design can be verified, and the data classification system can be supplemented, improved, and versioned and maintained.

[0074] In summary of the above embodiments, the open-pit mine data classification method proposed in this disclosure is mainly divided into three stages: investigation and analysis of the current status of data resources and remediation needs, design of a data resource classification system, and classification management of data assets.

[0075] The analysis of the current status of data resources and the need for remediation mainly focuses on the current status of management organizations, business scope and processes, information technology status, data distribution and existence form, and data application demand collection. By analyzing and sorting out the survey results, the classification background and classification scope are clarified, laying a solid foundation for the design of the classification system and asset classification management and operation and maintenance.

[0076] The design of the data classification system is mainly based on the results of previous research and analysis. It focuses on the internal dimensions of the open-pit mine itself, the external business dimensions of the open-pit mine, the exchange and sharing dimensions between business departments, and the comprehensive analysis and decision-making dimensions. It inherits the general industry model, highlights the characteristic management business of open-pit mines, and ensures that the classification catalog is multi-dimensional and multi-perspective, ensuring that there is a traceable trace when applying data and that storage management is fully reasonable.

[0077] Data classification management mainly follows the data classification system and is carried out layer by layer from business to model to data. The existing open-pit mine data assets are reviewed and released, which not only effectively manages data assets, but also verifies the integrity, rationality and applicability of the data classification system design, and supplements and improves the data classification system as well as manages and maintains the version.

[0078] 1. Data classification research

[0079] The review of open-pit mine data resources emphasizes the close integration of needs analysis and system planning. Needs analysis serves as a preparatory step for system planning, while system planning formalizes and formalizes user needs. Only through meticulous research and analysis, closely aligned with customer needs, can rational allocation and scientific design be achieved. Using models as a vehicle, can business personnel and analysts reach consensus on the "what needs to be done" in data resource development. Reviewing the current status of open-pit mine data resources includes: Sorting out the key business processes of open-pit mine management and taking inventory of data resource information.

[0080] a) Sorting out the main business processes of open-pit mines

[0081] Through research, a division of labor tree was established to determine the scope of information resources. By investigating and questioning business personnel in various open-pit mining enterprises and combining the results of the research on the business functions of each department, it was concluded that the main needs include two parts: the open-pit mine management information exchange business process and the production business management process. The process of sorting out the actual business content and process is as follows:

[0082] 1) Establish business nodes; under the business nodes, establish responsibility division nodes according to the different responsibilities and tasks undertaken;

[0083] 2) Under the responsibility division node, establish management activity nodes based on the work to be completed in fulfilling responsibilities;

[0084] 3) Under the management activity node, establish work step nodes according to the specific links of the activity;

[0085] 4) Under the work step node, create an information form node according to the name of the relevant information form.

[0086] After completing the process information collection, based on the division of labor tree and the collection results of the business process, the first and second level business process diagrams are drawn for the business functions of each open-pit mine, so as to clarify the business exchange relationship between business departments (horizontally), within business departments, and between superior and subordinate business departments.

[0087] b) Inventory of open-pit mine data resources

[0088] The business scope covers all business systems in open-pit mining enterprises. The specific final access situation of the system will be adjusted according to the actual situation. According to the data resource construction guide and the compiled data resource list, the data resource inventory is completed in the following four steps:

[0089] 1) Summarize and sort out the construction status of the business information system database, follow the reporting requirements, organize business personnel according to the business system database classification and the division of labor implemented by the developer, collect all fields involved in the technical attribute inventory table, including the hierarchical relationship between the collection fields and the data table, clarify the Chinese name of the data item, data type, length precision, data format, value range, whether it is non-empty, whether it is a primary key, and record them to form a technical attribute inventory table.

[0090] 2) Organize personnel to sort out, summarize, and format-check the data items in the draft technical attribute inventory table based on the research and analysis results. Considering that different business units (departments) may create redundant basic information resources such as equipment, organizational structure, personnel, and materials during data structure design, and that data items may be abandoned during software design and continuous maintenance, implementation personnel will uniformly mark reporting issues such as duplicate data tables, unclear data table meanings, ambiguous field meanings, and ambiguous foreign key relationships in the collected content in accordance with the clear reporting requirements, and summarize them into the final document.

[0091] 3) Organize open-pit mine business personnel and system developers to conduct information verification on the survey content. First, verify the authenticity of information resources. Compare and verify the contents of the data resource list with each stage of the business process to ensure that they are consistent with actual use. Second, verify the consistency of information resources. Different departments may have different definitions and understandings of the same business information resources. To avoid duplication of information resources due to information resource aliases, duplication verification should be performed through data tables and data items. Third, verify the data sharing and exchange information such as the responsible unit of the information resource, the sharing scope, the provision cycle, and the validity period.

[0092] 4) Organize personnel to complete relevant information items of the research information based on the expert review opinions. Confirm any questionable information resources with relevant business units and compile them into the data research report.

[0093] 2. Data classification principles

[0094] According to the business type, data with common attributes or characteristics are grouped together, and the data are distinguished by the attributes or characteristics of their categories.

[0095] The construction process must adhere to the following principles: scientificity, integrity, systematicity, practicality, scalability, and stability:

[0096] a) The classification dimensions, classification element selection and classification hierarchy determination should refer to relevant standard materials and advanced methodologies to ensure that they are scientific and reasonable;

[0097] b) Data that are interrelated, mutually constrained, and mutually influential within the system should be centralized as much as possible to facilitate the selection and management of related data sets;

[0098] c) The data classification system should be constructed with a clear logical hierarchy, reasonable structure and clear categories.

[0099] d) The constructed data system should fully consider its usability and operability, with the goal of facilitating data maintenance, use, and sharing;

[0100] e) When setting categories or dividing levels, appropriate margins should be left to ensure that when the number of classification objects increases in the future, the impact on the established classification system will be reduced;

[0101] f) The most stable and essential characteristics of the classification object should be clearly defined to ensure its stability.

[0102] 3. Data classification method

[0103] Data classification is to group data with certain common attributes or characteristics together and distinguish the data by the attributes or characteristics of their categories. In other words, information with the same content and nature and information that requires unified management is grouped together, while information that is different and needs to be managed separately is distinguished, and then the relationship between each set is determined to form an organized classification system.

[0104] Different data have different properties, and the nature of the data is the determining factor in choosing a data analysis method. Therefore, the ability to correctly classify data is the basis for data analysis and obtaining analytical results. For example, from the perspective of equipment life cycle management, data can be divided into procurement data, on-site data, production data, usage data, and decommissioning data. From the perspective of project management, data can be divided into planning data, project data, project milestone data, and project deliverable data. Based on attributes and characteristics such as data stability, usage frequency, business stage, source unit, and data connotation, the classification "class" and classification objects are determined by sorting out the business, dividing the disorganized data resources into different data sets, and ensuring that each piece of information has a corresponding position in the corresponding classification system. This forms a data classification system that can cover open-pit mining operations, realizes data sharing at all stages of open-pit mining, facilitates data management, and improves data processing efficiency. It also provides guidance for the design of data models, the design of data warehouses, and the cleaning and storage of data.

[0105] Data resources are refined based on the key business processes of open-pit mines. All operations in open-pit mines are centered around process flows. Therefore, centered around top-level objectives, the business relationships within open-pit mines are primarily structured at three levels. The first level involves macro-level planning and program management, which involves analyzing the open-pit mine's plans, current execution, and capacity gaps. Based on these gaps, a series of open-pit mine development and construction goals are planned, and annual funding applications are prepared based on project progress. The second level of management is production management, focusing on the implementation of drilling, blasting, mining, transportation, and drainage, ensuring the achievement of project objectives within safety and environmental constraints. The third level encompasses the management elements of equipment, personnel, organizational structure, and materials. Based on the actual situation of open-pit mines, data resources are categorized into business domains from a holistic business perspective. These are presented through thematic domains, including nine categories: production, equipment, personnel, safety, environmental protection, transportation and sales, materials, engineering management, and finance.

[0106] For example, the production subject domain may include mining plans, mining progress, ore-rock ratio, equipment efficiency, production statistics, scheduling information, equipment transportation distance statistics, electric shovel truck grouping information, explosion scale and other information; the equipment subject domain includes detailed information on various open-pit mining equipment, such as the model, specifications, purchase date, location, usage status, maintenance records and other information of excavators, transport vehicles, loaders, crushers, belt conveyors and other equipment; the personnel subject domain includes basic information, job titles and other information of employees; the safety subject domain includes relevant data covering open-pit mine safety management, such as production safety system, safety training records, emergency plans, accident investigation reports, occupational health data, etc.; the environmental protection subject domain includes information related to Data related to environmental protection and governance of open-pit mines, including compliance with environmental laws and regulations, pollution emission data, energy-saving and emission reduction measures, ecological restoration plans, etc.; the transportation and sales subject domain includes transportation and sales data related to coal mines, including customer information, sales plans, transportation methods, transportation costs, sales statistics, etc.; the materials subject domain includes data related to material procurement and inventory management of open-pit mines, such as supplier information, purchase orders, inventory location, inventory quantity, material distribution, etc.; the engineering management subject domain includes data related to open-pit mine engineering projects, such as project plans, budgets, progress tracking, quality control, etc.; the financial subject domain includes financial statements, cost accounting, income and expenditure, and other financial-related information of open-pit mining enterprises.

[0107] 4. Data classification management

[0108] For example, if Figure 3 As shown, Figure 3 It is a schematic diagram of the data classification management process proposed in this disclosure.

[0109] Among them, the platform informationization leading group will unify the leadership of the platform data classification and management work, and coordinate the resolution of major issues in the platform data classification and management work.

[0110] a) Formulate relevant systems, guidelines, implementation rules, etc. for data classification and management;

[0111] b) To guide, supervise, manage and coordinate data classification and categorization work;

[0112] c) Establish a communication mechanism for data classification and grading management to coordinate and arbitrate disputes arising from classification and grading work;

[0113] d) Review the accuracy and rationality of data classification and categorization of each department;

[0114] e) Regularly review the rationality of data level upgrades and classification rules, and make adjustments as needed;

[0115] f) Formulate a data grading and classification work assessment system, and coordinate the assessment of data grading and classification work.

[0116] The data governance implementation department shall perform the following duties in data classification and categorization:

[0117] a) Implement relevant systems, guidelines, implementation rules, etc. formulated by the platform informatization leadership group;

[0118] b) Based on the data resources provided by the business department, organize and form complete metadata information, and then classify the data;

[0119] c) Create a data classification list based on the opinions of the business department.

[0120] The data business department shall perform the following duties in data classification and categorization:

[0121] a) Classify the data connected to the platform according to the data classification system, guidelines, implementation rules, etc. formulated by the platform informatization leadership group;

[0122] b) Support the data implementation needs of data classification and grading implementation departments.

[0123] If any department and its staff violate the provisions of these Measures or are suspected of infringing upon the rights and interests of data subjects during the process of data grading and classification, the relevant competent authorities shall directly make accountability decisions on them in accordance with relevant regulations and management authority.

[0124] like Figure 3 As shown, the data classification management process includes four stages: top-level design, data inventory, data classification, and approval and release.

[0125] During the top-level design stage, the platform informationization leadership group formulated data classification management systems, processes, implementation details, etc.

[0126] During the data inventory phase, the implementation department formulates an inventory plan and inventory template, and sorts out the data resources provided by the business department to form complete metadata information.

[0127] During the data classification stage, the implementation department will classify the data based on the data metadata information and this management specification, and submit the classification results to the platform informatization leadership group.

[0128] During the approval and release phase, the platform information leadership team reviews the data classification results. If approved, they are approved for release; if not, they are returned to the implementation department for reclassification.

[0129] The process for data classification changes must also be carried out according to this process.

[0130] The data classification method for open-pit mines proposed in this disclosure focuses on sorting out the internal dimensions of the open-pit mine itself, sorting out the external business dimensions of the open-pit mine, sorting out the exchange and sharing dimensions between business departments, and sorting out the comprehensive analysis and decision-making dimensions. It inherits the general industry model, highlights the characteristic management business of open-pit mines, and ensures that the classification catalog is multi-dimensional and multi-perspective. It not only ensures that there is a traceable trace when applying data, but also ensures that storage and management are fully reasonable. By reviewing and publishing existing open-pit mine data assets, it not only effectively manages data assets, but also verifies the integrity, rationality and applicability of the data classification system design, and supplements and improves the data classification system, as well as manages and maintains versions.

[0131] Figure 4 Schematic diagram of the structure of a data classification device for an open-pit mine proposed in one embodiment of the present disclosure.

[0132] like Figure 4 As shown, the data classification device 40 for the open-pit mine includes:

[0133] An acquisition module 401 is used to acquire data classification indication information corresponding to the open-pit mine;

[0134] The template formulation module 402 is used to formulate a data inventory template according to the data classification indication information;

[0135] The data resource inventory module 403 is used to perform a data resource inventory on the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data;

[0136] A determination module 404 is used to sort out the business processes of the open-pit mine to determine multiple data subject domains;

[0137] The classification processing module 405 is used to perform data classification processing according to metadata information and multiple data subject domains to obtain data classification results.

[0138] It should be noted that the aforementioned explanation of the data classification method for an open-pit mine is also applicable to the data classification device for an open-pit mine in this embodiment, and will not be repeated here.

[0139] In this embodiment, by obtaining data classification indication information corresponding to the open-pit mine, a data inventory template is formulated according to the data classification indication information, and a data resource inventory of the open-pit mine is performed according to the data inventory template to obtain metadata information of the open-pit mine-related data, and the business process of the open-pit mine is sorted out to determine multiple data subject domains. Data classification processing is performed based on the metadata information and the multiple data subject domains to obtain data classification results. In this way, data sharing at all stages of the open-pit mine can be achieved, data management is facilitated, data processing efficiency is improved, and reliable guidance information is provided for the design of data models, the design of data warehouses, and the cleaning and storage of data.

[0140] Figure 5 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. Figure 5 The computer device 12 shown is only an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present disclosure.

[0141] like Figure 5 As shown, computer device 12 is implemented as a general-purpose computing device. Components of computer device 12 may include, but are not limited to, one or more processors or processing units 16, system memory 28, and a bus 18 that connects various system components (including system memory 28 and processing unit 16).

[0142] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. Examples of such architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnection (PCI) bus.

[0143] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0144] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be configured to read and write non-removable, non-volatile magnetic media ( Figure 5 Not shown, often called a "hard drive").

[0145] although Figure 5Although not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a Compact Disc Read Only Memory (hereinafter referred to as: CD-ROM), a Digital Video Disc Read Only Memory (hereinafter referred to as: DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the various embodiments of the present disclosure.

[0146] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 42 generally implement the functions and / or methods of the embodiments described herein.

[0147] The computer device 12 can also communicate with one or more external devices 14 (e.g., a keyboard, pointing device, display 24, etc.), one or more devices that enable human interaction with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). This communication can occur via an input / output (I / O) interface 22. Furthermore, the computer device 12 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via a bus 18. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with the computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0148] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28 , such as implementing the data classification method for open-pit mines mentioned in the above embodiment.

[0149] In order to implement the above embodiments, the present disclosure further proposes a non-transitory computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the data classification method for an open-pit mine proposed in the above embodiments of the present disclosure is implemented.

[0150] In order to implement the above embodiments, the present disclosure further proposes a computer program product. When an instruction processor in the computer program product executes, the data classification method for an open-pit mine proposed in the above embodiments of the present disclosure is executed.

[0151] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0152] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0153] It should be noted that, in the description of this disclosure, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of this disclosure, unless otherwise specified, the meaning of "plurality" is two or more.

[0154] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0155] It should be understood that various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0156] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0157] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0158] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0159] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0160] Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are illustrative and are not to be construed as limitations on the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A data classification method for open-pit mines, characterized in that: include: Obtaining data classification indication information corresponding to the open-pit mine; Formulate a data inventory template based on the data classification indication information; Performing a data resource inventory on the open-pit mine according to the data inventory template to obtain metadata information of the open-pit mine related data; Sorting out the business processes of the open-pit mine to identify multiple data subject domains; Data classification processing is performed according to the metadata information and the multiple data subject domains to obtain a data classification result.

2. The method according to claim 1, wherein The business process of the open-pit mine is sorted out to determine multiple data subject domains, including: Sorting out the business processes of the open-pit mine to obtain process information collection results; Generate multiple business process diagrams based on the process information collection results; determining business relationship information according to the multiple business process diagrams; The multiple data subject domains are determined according to the business relationship information.

3. The method according to claim 2, wherein The business process of the open-pit mine is sorted out to obtain process information collection results, including: Establish business nodes and, based on the different responsibilities and tasks undertaken, establish responsibility division nodes under the business nodes; Establish management activity nodes under the division of responsibilities nodes based on the work to be completed in fulfilling responsibilities; Establish work step nodes under the management activity nodes according to the specific links of the activities; According to the name of the related information form, an information form node is created under the work step node.

4. The method according to claim 2, wherein The business relationship information includes: Macro-level planning and management information; Production management information; Manage feature information.

5. The method according to claim 2, wherein The multiple data subject domains include: production, equipment, personnel, safety, environmental protection, transportation and marketing, materials, project management and finance.

6. The method according to claim 1, wherein Also includes: Review the results of the data classification; If approved, the data classification results will be published; If the review fails, the data classification results will be adjusted.

7. A data classification device for an open-pit mine, characterized in that: include: An acquisition module, used to acquire data classification indication information corresponding to the open-pit mine; A template formulation module, configured to formulate a data inventory template according to the data classification indication information; a data resource inventory module, configured to perform a data resource inventory on the open-pit mine according to the data inventory template to obtain metadata information of relevant data of the open-pit mine; A determination module, configured to sort out the business processes of the open-pit mine to determine a plurality of data subject domains; The classification processing module is used to perform data classification processing according to the metadata information and the multiple data subject domains to obtain a data classification result.

8. A computer device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: in, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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