Business atlas construction method and device, equipment, storage medium and program product

Abstract

The invention discloses a business number graph construction method, device and equipment, a storage medium and a program product, and the method comprises the steps: determining a graph ontology model of main transformer equipment according to the business process and function mapping of the main transformer equipment in a full life cycle; obtaining business data of the main transformer equipment in a full life cycle, obtaining business entities corresponding to the main transformer equipment and business relationships among the business entities in the business data according to the graph ontology model, and constructing a business number graph of the main transformer equipment based on the business entities and the business relationships; and storing the business number atlas in a business number atlas system for the business number atlas system to respond to query of the retrieval control according to the business number atlas. The business entity and the business relation can be accurately extracted through the graph ontology model, it is ensured that the business data graph can accurately reflect the complex semantic relation between data, the retrieval control is integrated in the business data graph system, a user can rapidly position needed knowledge, and the management efficiency of main transformer equipment is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device, equipment, storage medium and program product for constructing an industry data graph. Background Art

[0002] With the rapid development of the power industry, higher requirements are placed on the management and maintenance of equipment. As an advanced management concept and method, the full life cycle management of power grid equipment is committed to comprehensive and systematic management of equipment from planning, procurement, installation, operation, maintenance to scrapping. However, with the increasing number and types of power grid equipment, the disadvantages of traditional power grid equipment full life cycle management methods are gradually emerging. On the one hand, traditional methods cannot fully cover and effectively integrate power grid equipment business data from multiple data sources, resulting in frequent data islands; on the other hand, with the advancement of technology, the industry data graph technology provides unprecedented support for management data with its powerful data integration, association and reasoning capabilities. However, there is still a lack of unified technical standards in the existing technology to guide the application of knowledge graph technology in the full life cycle management of power grid equipment, which limits the full potential of knowledge graph technology. Therefore, providing a method for constructing an industry data graph based on knowledge graph technology for the management of massive data in the full life cycle of power grid equipment has become an urgent problem to be solved in the field of data processing. Summary of the invention

[0003] The present invention provides a method, device, equipment, storage medium and program product for constructing an industry data map. The present invention ensures that the industry data map can accurately reflect the complex semantic connections between the business data of the main transformer equipment, realizes the sharing of the industry data map, and improves the management efficiency of the main transformer equipment.

[0004] In one aspect of an embodiment of the present invention, a method for constructing an industry data graph is provided, comprising:

[0005] Determine the graph ontology model of the main transformer equipment based on the business process and function mapping of the main transformer equipment in its entire life cycle;

[0006] Obtain the business data of the main transformer equipment throughout its life cycle, obtain the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and build a business data graph of the main transformer equipment based on the business entities and business relationships;

[0007] The business data graph is stored in the business data graph system so that the business data graph system can respond to the query of the retrieval control according to the business data graph.

[0008] Another aspect of an embodiment of the present invention provides a device for constructing an industry data graph, including:

[0009] A model determination module is used to determine the graph ontology model of the main transformer equipment according to the business process and function mapping of the main transformer equipment in the whole life cycle;

[0010] A graph construction module is used to obtain the business data of the main transformer equipment throughout its life cycle, obtain the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and construct a business data graph of the main transformer equipment based on the business entities and business relationships;

[0011] The graph query module is used to store the business data graph in the business data graph system so that the business data graph system can respond to the query of the retrieval control according to the business data graph.

[0012] Another aspect of an embodiment of the present invention provides a device, including:

[0013] at least one processor;

[0014] and a memory communicatively coupled to the at least one processor;

[0015] Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the industry number graph construction method of any embodiment of the embodiments of the present invention.

[0016] Another aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores:

[0017] Computer instructions, computer instructions are used to enable a processor to execute the industry data graph construction method of any embodiment of the present invention.

[0018] Another aspect of the embodiments of the present invention provides a computer program product, the computer program product comprising:

[0019] A computer program, when executed by a processor, is a method for constructing an industry data graph according to any embodiment of the present invention.

[0020] According to an embodiment of the present invention, a series of orderly activities of a main transformer device in its entire life cycle and a mapping relationship between various functional components related to the main transformer device are obtained, that is, the business process and function mapping of the main transformer device in its entire life cycle are obtained. Based on the obtained business process and function mapping of the main transformer device, entities related to the main transformer device and relationships between entities can be obtained. Based on the entities related to the main transformer device and relationships between entities, a graph ontology model of the main transformer device can be constructed, wherein entities related to the main transformer device and relationships between related entities can be obtained from business data of the main transformer device in its entire life cycle. Business data generated at each business process stage of the main transformer device in its entire life cycle can be obtained. Business entities related to the main transformer device and business relationships between various business entities can be extracted from business data according to the relationships between various entity indicator items and entity indicator items contained in the graph ontology model. A business data map of the main transformer device can be constructed based on the business entities and business relationships extracted from the business data. The business data map of the main transformer device constructed based on the business entities and business relationships can be stored in a business data map system. The business data map can be queried using a search control in the business data map system for querying the business data map. The embodiment of the present invention, by constructing a graph ontology model, unifies the data semantics and association relationships of the main transformer equipment throughout its life cycle, can provide clear guidance for the subsequent construction of the industry data map, and improve the accuracy of the industry data map construction. By relying on the graph ontology model, business entities and business relationships can be accurately extracted from business data, thereby avoiding data redundancy and omissions, and ensuring that the industry data map can more accurately reflect the complex semantic relationships between massive data of the main transformer equipment. By saving the industry data map to the industry data map system, the industry data map can be shared, thereby achieving the beneficial effect of improving the utilization rate of the industry data map. By integrating a retrieval control in the industry data map system, the query function of the industry data map can be realized, allowing users to quickly locate the required knowledge according to their needs, thereby improving the user experience and the management efficiency of the main transformer equipment.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1This is a flow chart of a method for constructing an industry data graph provided according to the first embodiment of the present invention;

[0024] Figure 2 is a flow chart of another method for constructing an industry data graph provided according to the second embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of a process for constructing an industry data graph according to Embodiment 3 of the present invention;

[0026] Figure 4 is a schematic diagram of a main transformer model provided by Embodiment 3 of the present invention;

[0027] Figure 5 is a schematic diagram of a structured graph ontology model of a main transformer device provided according to Embodiment 3 of the present invention;

[0028] Figure 6 is a schematic diagram of an unstructured graph ontology model of a main transformer device provided according to Embodiment 3 of the present invention;

[0029] Figure 7 This is a schematic diagram of extracting business entities and business relationships provided according to Embodiment 3 of the present invention;

[0030] Figure 8 This is a schematic diagram of a data import method provided according to Embodiment 3 of the present invention;

[0031] Fig. 9 It is a schematic diagram of the structure of a device for implementing a method for constructing an industry data graph according to an embodiment of the present invention;

[0032] Fig.10 It is a device block diagram for executing an industry data graph construction method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Embodiment 1

[0036] Figure 1 A flowchart of a method for constructing a data graph is provided for the first embodiment of the present invention. The present embodiment of the present invention can be applied to the case where data graph technology is used to manage massive data in a power network. The method can be executed by a data graph construction device. The data graph construction device can be implemented in the form of hardware and / or software. The data graph construction device can be configured in a device. Figure 1 As shown, the method includes:

[0037] S101. Determine a graph ontology model of the main transformer equipment according to the business process and function mapping of the main transformer equipment in the entire life cycle.

[0038] Among them, the full life cycle refers to the complete process of a device or system from design to scrapping. For example, the full life cycle of the main transformer equipment may include: design process, production process, installation process, operation process, maintenance process and scrapping process, etc.

[0039] The business process can be understood as a collection of a series of orderly activities. For example, a series of orderly activities in the entire life cycle of the main transformer equipment may include: design, procurement, manufacturing, transportation, installation, commissioning, operation, maintenance, scrapping and other stages.

[0040] Functional mapping can be understood as a mapping relationship between various functional components related to the main transformer equipment. It can be understood that each functional component actually exists in the power system and is located in the same power network as the main transformer equipment. By way of example, the functional components related to the main transformer equipment may include: a data acquisition module for collecting business process data of the main transformer equipment or a performance judgment module for judging the performance of the main transformer equipment based on business process data.

[0041] The graph ontology model can be understood as a storage structure. In the graph ontology model, vertices can be used to represent entities related to the main transformer equipment, and edges can be used to represent the relationship between entities related to the main transformer equipment. It can be understood that in the graph ontology model, the relationship between related entities means that there is a conceptual connection between the entities, but the specific content of the connection is unclear.

[0042] Specifically, a series of ordered activities of the main transformer equipment in the entire life cycle and the mapping relationship between various functional components related to the main transformer equipment are obtained, that is, the business process and function mapping of the main transformer equipment in the entire life cycle are obtained, and the entities related to the main transformer equipment and the relationships between the entities can be obtained based on the obtained business process and function mapping of the main transformer equipment. Based on the entities related to the main transformer equipment and the relationships between the entities, a graph ontology model of the main transformer equipment can be constructed, wherein the entities related to the main transformer equipment and the relationships between the related entities can be obtained in the business data of the main transformer equipment in the entire life cycle.

[0043] For example, the steps of constructing a graph ontology model of the main transformer equipment based on the acquired business process and function mapping of the main transformer equipment may include: extracting the business data of the main transformer equipment in the data middle platform according to the business process, obtaining the mapping relationship between the functional components related to the main transformer equipment in the business data according to the actual connection relationship between the functional components related to the main transformer equipment, extracting all entity indicator items related to the main transformer equipment in the business data according to the mapping relationship and actual data requirements, and establishing associations between the entity indicator items, abstracting the entity indicator items into vertices, and abstracting the association relationships into edges between vertices, and constructing a graph ontology model of the main transformer equipment based on the abstracted vertices and edges.

[0044] S102. Obtain the business data of the main transformer equipment throughout its entire life cycle, obtain the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and construct a business data graph of the main transformer equipment based on the business entities and business relationships.

[0045] The business data may be understood as a series of process information generated by the main transformer device at each business process stage. For example, the business data may include: design data of the main transformer device or operation data of the main transformer device.

[0046] Business entities refer to objects and / or concepts that can be identified in the power system. For example, business object entities may include: physical object entities or conceptual object entities. Physical object entities may include: main transformer equipment entities or data acquisition component entities, etc. Conceptual object entities may include: main transformer equipment test report entities or main transformer equipment operation reports, etc.

[0047] A business relationship can be understood as an interaction between different business object entities. For example, the types of business relationships may include: physical connection or logical association.

[0048] The business data graph can be understood as a knowledge base, which can cover various entities and the relationships between entities in business data.

[0049] Specifically, the business data generated by the main transformer equipment at each business process stage in its entire life cycle can be obtained, and the business entities related to the main transformer equipment and the business relationships between the various business entities can be extracted from the business data based on the relationships between the various entity indicator items and the entity indicator items contained in the graph ontology model. A business data graph of the main transformer equipment can be constructed based on the business entities and business relationships extracted from the business data.

[0050] For example, the steps of constructing a business data graph of the main transformer equipment based on business entities and business relationships extracted from business data may include: abstracting business entities into vertices, abstracting business relationships into edges between the vertices, and constructing a business data graph of the main transformer equipment based on the vertices and edges.

[0051] S103. Store the business number graph in the business number graph system so that the business number graph system can respond to the query of the retrieval control according to the business number graph.

[0052] Among them, the industry digital graph system can be understood as another storage structure, which can be used for the storage, management and query of industry digital graphs.

[0053] The search control can be understood as a front-end interactive component that can be used to query the industry data graph.

[0054] Specifically, the business data map of the main transformer equipment constructed based on business entities and business relationships can be stored in the business data map system, and the business data map can be queried using the search control in the business data map system for querying the business data map.

[0055] According to an embodiment of the present invention, a series of orderly activities of a main transformer device in its entire life cycle and a mapping relationship between various functional components related to the main transformer device are obtained, that is, the business process and function mapping of the main transformer device in its entire life cycle are obtained. Based on the obtained business process and function mapping of the main transformer device, entities related to the main transformer device and relationships between entities can be obtained. Based on the entities related to the main transformer device and relationships between entities, a graph ontology model of the main transformer device can be constructed, wherein entities related to the main transformer device and relationships between related entities can be obtained from business data of the main transformer device in its entire life cycle. Business data generated at each business process stage of the main transformer device in its entire life cycle can be obtained. Business entities related to the main transformer device and business relationships between various business entities can be extracted from business data according to the relationships between various entity indicator items and entity indicator items contained in the graph ontology model. A business data map of the main transformer device can be constructed based on the business entities and business relationships extracted from the business data. The business data map of the main transformer device constructed based on the business entities and business relationships can be stored in a business data map system. The business data map can be queried using a search control in the business data map system for querying the business data map. The embodiment of the present invention, by constructing a graph ontology model, unifies the data semantics and association relationships of the main transformer equipment throughout its life cycle, can provide clear guidance for the subsequent construction of the industry data map, and improve the accuracy of the industry data map construction. By relying on the graph ontology model, business entities and business relationships can be accurately extracted from business data, thereby avoiding data redundancy and omissions, and ensuring that the industry data map can more accurately reflect the complex semantic relationships between massive data of the main transformer equipment. By saving the industry data map to the industry data map system, the industry data map can be shared, thereby achieving the beneficial effect of improving the utilization rate of the industry data map. By integrating a retrieval control in the industry data map system, the query function of the industry data map can be realized, allowing users to quickly locate the required knowledge according to their needs, thereby improving the user experience and the management efficiency of the main transformer equipment.

[0056] Embodiment 2

[0057] Figure 2 This is a flow chart of another method for constructing a business number graph provided by the second embodiment of the present invention. Based on the above embodiment, this embodiment of the present invention provides another method for constructing a business number graph. Figure 2 As shown, the method includes:

[0058] S201. Extract the business process of the main transformer equipment in the entire life cycle according to the business configuration information, and extract the business data of the main transformer equipment in the data center according to the business process.

[0059] The business configuration information refers to a series of data set to realize the extraction of the business process of the main transformer equipment. For example, the business configuration information at least includes the business process name data.

[0060] The data middle platform can understand another storage structure, which can be used to store the business data of the main transformer equipment throughout its life cycle from different data sources.

[0061] Specifically, the business configuration information set for extracting the business process of the main transformer equipment can be obtained, the business process of the main transformer equipment throughout its life cycle can be obtained based on the business configuration information, and based on the obtained business process, the business data generated by the main transformer equipment in each business process stage throughout its life cycle can be extracted in the data middle platform.

[0062] For example, the steps of obtaining the business process of the main transformer equipment throughout its life cycle based on the business configuration information may include: establishing a communication connection with the data middle platform, extracting the business process pre-stored in the data middle platform, or importing the pre-stored business process of the main transformer equipment throughout its life cycle from the data middle platform through a data import technology.

[0063] For example, Figure 4 As shown, the business process of the main transformer equipment in the whole life cycle may include: project planning, bidding and procurement, material supervision, material sampling, material warehousing, material outbound, engineering construction, handover test, completion acceptance, commissioning / capital transfer / same source / maintenance, equipment inspection / equipment testing / equipment maintenance, hidden danger control / defect handling / fault handling, equipment retirement and other stages.

[0064] S202. Based on the actual connection relationship between the functional components related to the main transformer equipment, the mapping relationship between the functional components is obtained in the business data, and all entity indicator items related to the main transformer equipment and the association relationship between the entity indicator items are extracted from the business data based on the mapping relationship and actual data requirements, wherein the main transformer equipment and the functional components are located in the same power network.

[0065] Among them, the functional component refers to the component that interacts with the main transformer equipment in the power system. For example, the functional component may include: a data acquisition module for collecting business process data of the main transformer equipment or a performance judgment module for judging the performance of the main transformer equipment based on the business process data.

[0066] The actual connection relationship refers to a physical connection method that actually exists between functional components in the power network. For example, the types of actual connection relationships may include: electrical connection or mechanical connection.

[0067] The mapping relationship can be understood as a corresponding relationship between various functional components, which can reflect the physical connection method between various functional components and can be used to guide the determination of entity indicator items in business data.

[0068] The entity indicator items can be understood as a series of data items. For example, the entity indicator items can include status data items or performance data items related to the main transformer equipment and functional components.

[0069] The association relationship can be understood as an interaction between different entity indicators, and the business relationship between business objects can be determined based on the association relationship.

[0070] Specifically, the actual physical connection mode of each functional component in the power network can be obtained, and the physical connection mode can be mapped to the actual connection relationship of each functional component, wherein each functional component can interact with the main transformer equipment in the power network, and the mapping relationship between each functional component can be extracted in the business data based on the obtained actual connection relationship of each functional component, and the actual data requirements for constructing the graph ontology model can be obtained. Based on the obtained mapping relationship and the actual data requirements, a series of entity indicator items related to the main transformer equipment can be extracted in the business data, and the association between each entity indicator item can be established based on the obtained mapping relationship, and the association relationship between each entity indicator item can be extracted in the business data through the established association between each entity indicator item.

[0071] S203, abstracting entity index items into vertices, abstracting association relationships into edges between vertices, and constructing a graph ontology model of the main transformer equipment based on the vertices and edges.

[0072] Specifically, each entity indicator item of the main transformer equipment in the business data and the association relationship between each entity indicator item can be obtained, all entity indicator items obtained in the business data can be abstracted into vertices, all association relationships can be abstracted into edges connecting vertices, and a graph ontology model can be constructed based on all abstracted vertices and edges.

[0073] S204. According to the entity index items in the graph ontology model, all business entities corresponding to the entity index items are extracted from the business data.

[0074] Specifically, entity index items may be extracted from the constructed graph ontology model, and all business entities corresponding to the entity index items may be extracted from the business data of the main transformer equipment based on the extracted entity index items.

[0075] S205: Perform association rule mining on the business data according to each business entity to determine the business relationship of each business object entity.

[0076] The association rules refer to the rules found in the business data and describing the connection between different business entities, which can be used to determine the business relationship between the business entities. For example, the association rules may include: a single association rule or multiple association rules.

[0077] Specifically, an association rule mining technology may be used to mine potential association rules between business object entities, and the mined association rules may be determined as business relationships between business entities.

[0078] S206. Construct a business data map of the main transformer equipment based on business entities and business relationships.

[0079] Specifically, all business entities in the business data can be abstracted as vertices, all business relationships can be abstracted as edges connecting vertices, and the business data graph of the main transformer equipment can be constructed based on all the abstracted vertices and edges.

[0080] S207. Obtain the user search instruction that triggers the entity search control through the data operation interface of the industry data graph system.

[0081] Among them, the data operation interface can be understood as a visual interface for users to interact with the graph knowledge system for data. For example, the data operation interface can provide users with controls such as retrieval controls for query operations or modification controls for modification operations.

[0082] The entity retrieval control can be understood as a specific functional area on the data operation interface, which can be used to retrieve the business data graph saved in the business data graph system.

[0083] A user search instruction refers to a search request issued by a user to the industry graph system, wherein the search request may include relevant information of the entity to be queried. For example, the search request may include: entity name or entity attributes and other information.

[0084] Specifically, a data operation interface for users to interact with the industry data graph can be displayed in the graph recognition system, wherein the data operation interface includes a specific functional area for searching the industry data graph, and the specific functional area can be used as an entity retrieval control. The user's search instructions can be obtained through the data operation interface, and the entity retrieval control can be triggered based on the user's search instructions.

[0085] S208: extract the business entity name included in the user search instruction, and fill the business entity name into the entity search operation page corresponding to the entity search control according to the user search instruction.

[0086] The business entity name may be understood as a noun representing a specific business entity. For example, the business entity name may include: main transformer equipment resources or main transformer equipment test report and the like.

[0087] The entity retrieval operation page can be understood as another visual interface for users to interact with the graph knowledge system for data. It can be used to display information such as the target business entity retrieved by the user or the target business relationship corresponding to the target business entity.

[0088] Specifically, the user search instruction can be obtained, the user search instruction can be parsed to obtain the business entity name contained in the user search instruction, and the parsed business entity name can be filled into the entity search operation page. It can be understood that the entity search operation page is obtained by triggering the entity search control.

[0089] S209. Obtain the target business entity displayed on the entity search operation page and the target business relationship corresponding to the target business entity, wherein the target business entity and the target business relationship are obtained by querying the business data graph by the business entity name.

[0090] Among them, the target business entity refers to the business object that is queried and displayed in the business data map through the business entity name on the entity search operation page. The target business entity can be represented as a vertex in the business data map.

[0091] The target business relationship refers to an interaction between the target business entity and other business entities in the business data graph. The target business relationship can be represented as an edge in the business data graph.

[0092] Specifically, by filling the business entity name into the entity search operation page, the target business entity corresponding to the business entity name, other business entities connected to the target business entity, and the target business relationship between the target business entity and other business entities can be queried in the business data map. By filling the business entity name into the entity search operation page, the target business entity and target business relationship displayed on the entity search operation page can be obtained. It can be understood that other business entities connected to the target business entity can also be obtained through the entity search operation page.

[0093] The embodiments of the present invention can obtain business configuration information set for extracting the business process of the main transformer equipment, can obtain the business process of the main transformer equipment in the whole life cycle according to the business configuration information, can extract the business data generated by the main transformer equipment in various business process stages in the whole life cycle in the data center based on the obtained business process, can obtain the actual physical connection mode of each functional component in the power network, can map the physical connection mode to the actual connection relationship of each functional component, wherein each functional component can interact with the main transformer equipment in the power network, can extract the mapping relationship between each functional component in the business data based on the actual connection relationship of each functional component obtained, can obtain the construction The actual data requirements of the graph ontology model can be used to extract a series of entity indicator items related to the main transformer equipment from the business data based on the obtained mapping relationship and the actual data requirements. The association between the entity indicator items can be established based on the obtained mapping relationship. The association relationship between the entity indicator items can be extracted from the business data through the established association between the entity indicator items. The entity indicator items of the main transformer equipment in the business data and the association relationship between the entity indicator items can be obtained. All entity indicator items obtained in the business data can be abstracted into vertices. All association relationships can be abstracted into edges connecting vertices. The graph ontology model can be constructed based on all abstracted vertices and edges. The entity indicator items can be extracted from the constructed graph ontology model. According to the extracted entity index items, all business entities corresponding to the entity index items can be extracted from the business data of the main transformer equipment. An association rule mining technology can be used to mine the potential association rules between business object entities. The mined association rules can be determined as business relationships between business entities. All business entities in the business data can be abstracted as vertices. All business relationships can be abstracted as edges connecting vertices. The business data map of the main transformer equipment can be constructed based on all the abstracted vertices and edges. A data operation interface for users to interact with the business data map can be displayed in the map recognition system, wherein the data operation interface includes a specific functional area for retrieving the business data map, and the specific functional area can be As an entity retrieval control, the user's user retrieval instruction can be obtained through the data operation interface, the entity retrieval control can be triggered based on the user retrieval instruction, the user retrieval instruction can be parsed to obtain the business entity name contained in the user retrieval instruction, and the parsed business entity name can be filled into the entity retrieval operation page. It can be understood that the entity retrieval operation page is obtained by triggering the entity retrieval control, and the business entity name can be filled into the entity retrieval operation page to query the target business entity corresponding to the business entity name, other business entities connected to the target business entity, and the target business relationship between the target business entity and other business entities in the business data map. The business entity name can be filled into the entity retrieval operation page.The target business entity and target business relationship displayed on the entity search operation page can be obtained. It can be understood that other business entities connected to the target business entity can also be obtained through the entity search operation page. In the embodiment of the present invention, by obtaining the actual connection relationship between each functional component, the physical and functional connection between each functional component can be accurately reflected, ensuring the accuracy and comprehensiveness of the determination of the association relationship between each entity indicator item. The business relationship between business entities is mined through association rule mining technology, which can improve the accuracy of business relationship identification, thereby improving the accuracy of industry data map construction. Through the data operation interface of the industry data map system, users can initiate searches and view search results, which improves user experience. The search results are displayed on the entity search operation page. Through the search results, users can intuitively understand the status of the main transformer equipment, thereby improving the management efficiency of the main transformer equipment. ,

[0094] On the basis of the above embodiments, embodiments of the present invention also include: obtaining structured data and unstructured data of the main transformer equipment in the entire life cycle; extracting all structured entity indicator items related to the main transformer equipment and the structured association relationships between the structured entity indicator items in the structured data based on the mapping relationship and actual data requirements, and constructing a structured graph ontology model based on the structured entity indicator items and the structured association relationships; extracting all unstructured entity indicator items related to the main transformer equipment and the unstructured association relationships between the unstructured entity indicator items in the unstructured data based on the mapping relationship and actual data requirements, and constructing an unstructured graph ontology model based on the unstructured entity indicator items and the unstructured association relationships.

[0095] Among them, structured data can be data that is stored and arranged in a regular manner. For example, structured data can be represented and stored using a relational database.

[0096] Unstructured data may be data whose format is not fixed. For example, the unstructured data may include: documents, pictures or video information related to the main transformer equipment.

[0097] Specifically, an embodiment of the present invention may also provide a construction step for constructing a structured graph ontology model and an unstructured graph ontology model, wherein the step of constructing a structured graph ontology model based on structured data may include: obtaining structured data of the main transformer equipment in the business data of the main transformer equipment, extracting entity indicator items related to the main transformer equipment and the association relationship between the entity indicator items in the structured data based on the mapping relationship extracted from the business data and the actual data requirements, using the entity indicator items extracted from the structured data as structured entity indicator items, using the association relationship extracted from the structured data as the structured relationship between the entity indicator items, abstracting the structured entity indicator items into vertices, abstracting the structured association relationship into edges between vertices, and constructing a structured graph ontology model based on the above vertices and edges; and constructing an unstructured graph ontology model based on the same principles as above.

[0098] For example, Figure 5 As shown in Figure 1, it is a structured graph ontology model of the main transformer equipment, such as Figure 6 As shown, it is an unstructured graph ontology model of the main transformer equipment.

[0099] On the basis of the above embodiments, embodiments of the present invention also include: obtaining a data operation interface of the industry data graph system, triggering a data import control in the data operation interface, so as to import the business data of the main transformer equipment from the data middle station through a Restful interface; adding the business data as attribute information to the corresponding edge of the industry data graph; wherein, the import method of importing the business data of the main transformer equipment from the data middle station includes at least: a full data import method, a T+1 day incremental data import method, and a real-time data import method.

[0100] Among them, the data import control can be understood as another specific functional area on the data operation interface, which can be used to import business data pre-stored in the data middle platform.

[0101] Specifically, the business data graph system may have a data import control for importing business data pre-stored in the data middle platform. The business data graph system can obtain the imported business data through the Restful interface, and can add the imported business data to the business data graph corresponding to the main transformer equipment, which can be used as the attribute information of the edge in the business data graph.

[0102] Embodiment 3

[0103] Based on the above embodiments, the present invention provides a process for constructing a business data map of the entire life cycle of a main transformer device, such as Figure 3As shown, the process includes six stages: business process combing, data tracing, business object definition, graph ontology model design, data processing, and main transformer equipment application scenario construction. It can be understood that the execution order of the three stages of business process combing, data tracing, and business objects in this process is changeable, and is not executed sequentially. In the business process combing stage, all business processes and business activity information of the main transformer equipment in the thirteen stages of the entire life cycle can be comprehensively combed, including: business process nodes, business activity arrangements, and can cover professional online business production systems such as development, materials, construction, operation and inspection, and regulation. In the business object definition stage, based on the business process of the main transformer equipment and the mapping relationship between the various functional components in the power system, various business objects related to the main transformer equipment and the relationship between various business objects can be combed out in the business process data. It can be understood that the business process data mentioned in this embodiment is the same as the business data mentioned in the above embodiment, and the business objects mentioned in this embodiment are the same as the business entities mentioned in the above embodiment. Based on the business objects and business relationships of the main transformer equipment, a graph ontology model of the main transformer equipment in the entire life cycle can be formed, such as Figure 3 As shown, before the graph ontology model is constructed, a data tracing step can also be included, including: sorting out the source data and table structure information corresponding to the business process, determining the authoritative data source and authoritative fields; in the data processing stage, entity tables and relationship tables can be extracted from the public data set based on business objects; all business entities and business relationships related to the main transformer equipment are extracted from the entity tables and relationship tables according to the graph ontology model, and stored in the graph database to form an industry data graph; in the scenario construction stage, the industry data graph can be stored in the industry data graph system to provide external services such as entity retrieval and graph analysis. Figure 4 It shows that the business process of the whole life cycle of the main transformer equipment includes: project planning, bidding and procurement, material supervision, material sampling, material warehousing, material outbound, engineering construction, handover test, completion acceptance, commissioning / capital transfer / same source / maintenance, equipment inspection / equipment testing / equipment maintenance, hidden danger control / defect handling / fault handling, equipment retirement and other processes. For example, various entities related to the main transformer equipment may include: substation, test report, factory test report, project failure, defect, hidden danger, team, unit, inspection plan, maintenance plan and monitoring plan and other entities. Figure 5 As shown, a structured graph ontology model can be designed for the structured data involved in the business process during the entire life cycle of the main transformer equipment. In this structured model, various entities related to the main transformer equipment may include: substation, busbar, transmission line, measurement point, test report, factory test report, project failure, defect, hidden danger, team, unit, inspection plan, maintenance plan and monitoring plan, etc. In this structured model, other business entities associated with the above entities are also included. Figure 6As shown, an unstructured graph ontology model can be designed for the unstructured data involved in the entire life cycle process of the main transformer equipment, including main transformer equipment product-related instruction documents, main transformer management process record materials, main transformer technical parameters and standards, main transformer related drawings and materials, etc. For example, the unstructured graph ontology model of the main transformer equipment may include: academic paper documents related to mutual transformer equipment, standard specification documents, patent documents, pictures containing national standards, and pictures containing linear standards, etc. Based on the graph ontology model, business objects and business relationships between business objects can be extracted from the business data of the entire life cycle of the main transformer equipment, and a list of core business objects can be formed through standardization, unified semantics, deduplication, merging, integration, splitting and other fusion designs. For example, the main transformer equipment defect record table is part of the business data of the entire life cycle of the main transformer equipment. The main transformer equipment defect record table can be taken as an example, such as Figure 7 As shown, the specific processing and extraction logic of the main transformer equipment defect record table can be: extract the main business object: defect, secondary business objects: equipment resources, equipment assets, manufacturers, units, teams, personnel, and the extracted business relationships are defect-equipment asset ownership relationship, defect-equipment manufacturer relationship, defect-unit disposal relationship, defect-personnel processing relationship, etc. In the above manner, the construction of the main transformer equipment business data map can be completed based on the business data map triples (entity, relationship, behavior). In an embodiment of the present invention, the business data of the main transformer equipment throughout its life cycle can be stored in the data center, and the constructed business data map can be stored in the business data map system. The business data map system can have functions such as entity retrieval and graph analysis. The business data map system can import the business data in the data center through a Restful interface. The import method may include: according to business needs, it can be divided into full data import, batch import of T+1 day incremental data, real-time data import, etc. In the business data map system, such as Figure 8 As shown, you can use the import tool provided by the industry graph system to read Hive / HDFS File data\Data Rows in Spark distributed task mode and import it into a graph database (Graph Data Base, GraphDB), ElasticSearch database or HBase database, etc. You can create an import task through the "Industry Graph System->Knowledge Construction->Data Access" function, which supports file import, HDFS file import, Hive file import, etc. You can create a data import scenario through the "Graph System->Knowledge Mining->My Scenario" function, which is completed through the read data table and write data table components. It supports data source expansion, and real-time data addition, deletion and modification operations can be performed through the Restful interface provided by the graph system.

[0104] Embodiment 4

[0105] Fig. 9 Embodiment 4 of the present invention provides a device capable of executing a method for constructing a business data graph, such as Fig. 9 As shown, the device comprises:

[0106] The model determination module 301 is used to determine the graph ontology model of the main transformer device according to the business process and function mapping of the main transformer device in the whole life cycle;

[0107] A graph construction module 302 is used to obtain the business data of the main transformer equipment in the entire life cycle, obtain the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and construct a business data graph of the main transformer equipment based on the business entities and business relationships;

[0108] The graph query module 303 is used to store the business data graph in the business data graph system so that the business data graph system can respond to the query of the retrieval control according to the business data graph.

[0109] According to an embodiment of the present invention, a series of orderly activities of a main transformer device in its entire life cycle and a mapping relationship between various functional components related to the main transformer device are obtained, that is, the business process and function mapping of the main transformer device in its entire life cycle are obtained. Based on the obtained business process and function mapping of the main transformer device, entities related to the main transformer device and relationships between entities can be obtained. Based on the entities related to the main transformer device and relationships between entities, a graph ontology model of the main transformer device can be constructed, wherein entities related to the main transformer device and relationships between related entities can be obtained from business data of the main transformer device in its entire life cycle. Business data generated at each business process stage of the main transformer device in its entire life cycle can be obtained. Business entities related to the main transformer device and business relationships between various business entities can be extracted from business data according to the relationships between various entity indicator items and entity indicator items contained in the graph ontology model. A business data map of the main transformer device can be constructed based on the business entities and business relationships extracted from the business data. The business data map of the main transformer device constructed based on the business entities and business relationships can be stored in a business data map system. The business data map can be queried using a search control in the business data map system for querying the business data map. The embodiment of the present invention, by constructing a graph ontology model, unifies the data semantics and association relationships of the main transformer equipment throughout its life cycle, can provide clear guidance for the subsequent construction of the industry data map, and improve the accuracy of the industry data map construction. By relying on the graph ontology model, business entities and business relationships can be accurately extracted from business data, thereby avoiding data redundancy and omissions, and ensuring that the industry data map can more accurately reflect the complex semantic relationships between massive data of the main transformer equipment. By saving the industry data map to the industry data map system, the industry data map can be shared, thereby achieving the beneficial effect of improving the utilization rate of the industry data map. By integrating a retrieval control in the industry data map system, the query function of the industry data map can be realized, allowing users to quickly locate the required knowledge according to their needs, thereby improving the user experience and the management efficiency of the main transformer equipment.

[0110] On the basis of the above embodiments, embodiments of the present invention also include obtaining structured data and unstructured data of the main transformer equipment throughout its entire life cycle; extracting all structured entity indicator items related to the main transformer equipment and the structured association relationships between the structured entity indicator items in the structured data based on the mapping relationship and actual data requirements, and constructing a structured graph ontology model based on the structured entity indicator items and the structured association relationships; extracting all unstructured entity indicator items related to the main transformer equipment and the unstructured association relationships between the unstructured entity indicator items in the unstructured data based on the mapping relationship and actual data requirements, and constructing an unstructured graph ontology model based on the unstructured entity indicator items and the unstructured association relationships.

[0111] On the basis of the above embodiments, embodiments of the present invention also include: obtaining a data operation interface of the industry data graph system, triggering a data import control in the data operation interface, so as to import the business data of the main transformer equipment from the data middle station through a Restful interface; adding the business data as attribute information to the corresponding edge of the industry data graph; wherein, the import method of importing the business data of the main transformer equipment from the data middle station includes at least: a full data import method, a T+1 day incremental data import method, and a real-time data import method.

[0112] On the basis of the above-mentioned embodiments, the model determination module 301 of the embodiment of the present invention is specifically used to extract the business process of the main transformer equipment in the whole life cycle according to the business configuration information, and extract the business data of the main transformer equipment in the data middle platform according to the business process; according to the actual connection relationship between the functional components related to the main transformer equipment, obtain the mapping relationship between the functional components in the business data, and extract all entity indicator items related to the main transformer equipment and the association relationship between the entity indicator items in the business data according to the mapping relationship and actual data requirements, wherein the main transformer equipment and the functional components are located in the same power network; abstract the entity indicator items into vertices, and abstract the association relationship into edges between vertices, and construct a graph ontology model of the main transformer equipment based on vertices and edges.

[0113] Based on the above embodiments, the graph relationship determination module 302 of the embodiment of the present invention is specifically used to extract all business entities corresponding to the entity indicator items in the business data according to the entity indicator items in the graph ontology model; perform association rule mining on the business data according to each business entity to determine the business relationship of each business object entity.

[0114] On the basis of the above-mentioned embodiments, the graph query module 303 of the embodiment of the present invention is specifically used to obtain the user search instruction that triggers the entity search control through the data operation interface of the industry digital graph system; extract the business entity name included in the user search instruction, and fill the business entity name into the entity search operation page corresponding to the entity search control according to the user search instruction; obtain the target business entity displayed on the entity search operation page and the target business relationship corresponding to the target business entity, wherein the target business entity and the target business relationship are obtained by querying the industry digital graph by the business entity name.

[0115] Embodiment 5

[0116] Embodiments of the present invention provide a device for executing a method for constructing an industry graph, a computer-readable storage medium, and a computer program product.

[0117] Fig.10A schematic diagram of a structure of an apparatus that can be used to implement an embodiment of the present invention is shown. The apparatus is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The apparatus may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown in the embodiments of the present invention, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present invention described and / or required herein.

[0118] like Fig.10 As shown, the device includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the ROM 12 or the computer program loaded from the storage unit 18 to the RAM 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0119] A number of components in the device are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0120] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit, a graphics processing unit, various special artificial intelligence computing chips, various processors running machine learning model algorithms, digital signal processors, and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, for example, the industry data graph construction method.

[0121] In some embodiments, the industry digital map construction method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the device via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps based on the industry digital map construction method can be performed. Alternatively, in other embodiments, the processor 11 can be configured as the industry digital map construction method by any other appropriate means (for example, by means of firmware).

[0122] Various implementations of the systems and techniques described above in the embodiments of the present invention may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays, application specific integrated circuits, application specific standard products, systems on chips, load programmable logic devices, computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs, which may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general programmable processor, which may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] The computer programs for implementing the methods of the embodiments of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0124] In the context of an embodiment of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0125] To provide interaction with a user, the systems and techniques described herein can be implemented on a device having: a display device (e.g., a cathode ray tube or liquid crystal display monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including: acoustic input, voice input, or tactile input).

[0126] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area networks, wide area networks, blockchain networks, and the Internet.

[0127] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private server services.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0129] The above specific implementations do not constitute a limitation on the protection scope of the embodiments of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for constructing an industry data graph, characterized in that: The method comprises: Determine a graph ontology model of the main transformer equipment according to the business process and function mapping of the main transformer equipment in the entire life cycle; Acquire the business data of the main transformer equipment in the whole life cycle, acquire the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and construct the business data graph of the main transformer equipment based on the business entities and the business relationships; The business number graph is stored in a business number graph system so that the business number graph system can respond to queries of retrieval controls according to the business number graph.

2. The method according to claim 1, characterized in that: The industry data graph system responds to the query of the retrieval control according to the industry data graph, including: Obtaining a user search instruction that triggers an entity search control through the data operation interface of the industry data graph system; Extracting the business entity name included in the user search instruction, and filling the business entity name into the entity search operation page corresponding to the entity search control according to the user search instruction; Obtain the target business entity displayed on the entity search operation page and the target business relationship corresponding to the target business entity, wherein the target business entity and the target business relationship are obtained by querying the business data graph through the business entity name.

3. The method according to claim 1, characterized in that: Determining the graph ontology model of the main transformer device according to the business process and function mapping of the main transformer device in the entire life cycle includes: Extract the business process of the main transformer device in the whole life cycle according to the business configuration information, and extract the business data of the main transformer device in the data center according to the business process; According to the actual connection relationship between the functional components related to the main transformer device, the mapping relationship between the functional components is obtained in the business data, and according to the mapping relationship and actual data requirements, all entity index items related to the main transformer device and the association relationship between the entity index items are extracted from the business data, wherein the main transformer device and the functional components are located in the same power network; The entity index items are abstracted as vertices, the association relationships are abstracted as edges between the vertices, and a graph ontology model of the main transformer equipment is constructed based on the vertices and the edges.

4. The method according to claim 3, characterized in that: Acquiring the business entity corresponding to the main transformer device and the business relationship between the business entities in the business data according to the graph ontology model includes: According to the entity index item in the graph ontology model, extracting all business entities corresponding to the entity index item from the business data; Association rule mining is performed on the business data according to each of the business entities to determine the business relationship of each of the business object entities.

5. The method according to claim 3, characterized in that: Also includes: Acquire structured data and unstructured data of the main transformer equipment throughout its entire life cycle; Extracting all structured entity index items related to the main transformer device and the structured association relationships between the structured entity index items from the structured data according to the mapping relationship and the actual data requirements, and constructing a structured graph ontology model according to the structured entity index items and the structured association relationships; According to the mapping relationship and the actual data requirements, all unstructured entity indicator items related to the main transformer equipment and the unstructured association relationships between the unstructured entity indicator items are extracted from the unstructured data, and an unstructured graph ontology model is constructed according to the unstructured entity indicator items and the unstructured association relationships.

6. The method according to claim 2, characterized in that: Also includes: Obtain the data operation interface of the business data graph system, and trigger the data import control in the data operation interface to import the business data of the main transformer equipment from the data middle platform through the Restful interface; Adding the business data as attribute information to the edge corresponding to the business data graph; Among them, the importing method of the business data of the main transformer equipment from the data center includes at least: a full data import method, a T+1 day incremental data import method and a real-time data import method.

7. A device for constructing an industry data graph, characterized in that: The device comprises: A model determination module, used to determine the graph ontology model of the main transformer device according to the business process and function mapping of the main transformer device in the whole life cycle; A graph construction module, used to obtain the business data of the main transformer equipment in the whole life cycle, obtain the business entities corresponding to the main transformer equipment and the business relationships between the business entities in the business data according to the graph ontology model, and construct the business data graph of the main transformer equipment based on the business entities and the business relationships; A graph query module is used to store the industry data graph in an industry data graph system so that the industry data graph system can respond to queries of retrieval controls based on the industry data graph.

8. A device, characterized in that The device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the industry digital graph construction method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores: Computer instructions, which are used to enable a processor to implement the industry data graph construction method described in any one of claims 1-6 when executed.

10. A computer program product, characterized in that The computer program product comprises: A computer program which, when executed by a processor, implements the method for constructing an industry digital graph according to any one of claims 1 to 6.

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