WO2023246165A1

WO2023246165A1 - Data asset display method and apparatus, and device and storage medium

Info

Publication number: WO2023246165A1
Application number: PCT/CN2023/079074
Authority: WO
Inventors: 陈启安; 周芳芳; 唐健恒; 张江; 季振峰
Original assignee: 华为云计算技术有限公司
Priority date: 2022-06-24
Filing date: 2023-03-01
Publication date: 2023-12-28
Also published as: CN117332916A

Abstract

The present application belongs to the technical field of data processing. Disclosed are a data asset display method and apparatus, and a device and a storage medium. The method comprises: when a plurality of data assets are displayed, determining at least one data asset set from the plurality of data assets on the basis of asset information of the plurality of data assets; and displaying these data asset sets as corresponding asset set nodes in a data asset map in a map visualization way. Therefore, the scale of nodes in a data asset map is greatly reduced, the scale of connection edges used for representing an association relationship between the nodes in the data asset map is also correspondingly reduced, and the display effect of data assets is improved, such that a user can quickly master the global relationship of the data assets, and the user experience is thus improved.

Description

Data asset display methods, devices, equipment and storage media

This application claims priority to the Chinese patent application with application number 202210729181.6 and the invention name "Data Asset Display Method, Device, Equipment and Storage Medium" submitted on June 24, 2022, the entire content of which is incorporated into this application by reference. middle.

Technical field

This application relates to the field of data processing technology, and in particular to a data asset display method, device, equipment and storage medium.

Background technique

At present, the data assets owned by enterprises are often large in number and complex in structure. In order to facilitate enterprises to grasp the current status of data assets, quickly sort out which data assets they have and how these data assets are distributed, it is often necessary to rationally organize and organize data assets. manage.

In related technologies, data assets are usually displayed in the form of a directory. For example, multiple data assets are displayed one by one according to the level of the department to which the data assets belong.

However, the above method cannot display the global relationship between data assets, resulting in enterprises being unable to intuitively understand the global distribution of data assets, and the display effect of data assets is poor.

Contents of the invention

The embodiments of the present application provide a data asset display method, device, equipment and storage medium, which can effectively improve the display effect of data assets. The technical solution is as follows:

The first aspect provides a data asset display method, which includes:

Obtain the asset information of multiple data assets, which includes the association between data assets and the asset type of the data assets;

Based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets. The data asset set includes multiple groups of data assets. The composition of the asset type and association relationship of each group of data assets are the same, and each group of data assets has the same composition and association relationship. The group data assets have the same association relationship with the corresponding data assets;

Based on the data asset set, the data assets other than the data asset set among the multiple data assets, and the correlation between the data assets, a target data asset graph of the multiple data assets is displayed, and the target data asset graph includes the asset set. Node and asset node, the asset collection node corresponds to the data asset collection, and the asset node corresponds to the data asset.

When displaying multiple data assets, based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets, and these data asset sets are visualized in the data asset graph. Displayed as corresponding asset collection nodes, thereby greatly reducing the size of nodes in the data asset graph, that is, correspondingly reducing the size of the edges used to represent the relationships between nodes in the data asset graph, improving the display effect of data assets , enabling users to quickly grasp the overall relationship of data assets and improve user experience.

In some embodiments, the method further includes:

In response to a skeleton extraction operation on the target data asset graph, extract skeleton nodes from the nodes of the target data asset graph;

Based on the extracted skeleton nodes, a first data asset graph of the multiple data assets is displayed.

By extracting skeleton nodes, important data assets in the target data asset graph are displayed, thereby further reducing the size of nodes and edges in the data asset graph and improving the display effect of the data asset graph.

In some embodiments, in response to the skeleton extraction operation on the target data asset graph, extracting skeleton nodes from the nodes of the target data asset graph includes:

Obtain the centrality value of the node in the target data asset graph. The centrality value indicates the importance of the data asset corresponding to the node in the multiple data assets;

Based on the centrality value and residual degree of the node in the target data asset graph, obtain the core value of the node in the target data asset graph. The residual degree indicates the number of deleted adjacent nodes of the node. The core value indicates the number of nodes connected to the node. the number of nodes;

Based on the core values of nodes in the target data asset graph, skeleton nodes are extracted from the nodes in the target data asset graph.

By combining the centrality value and residual degree of nodes to extract skeleton nodes, the importance of cluster center nodes in the data asset graph is fully considered, and more cluster center nodes can be retained as much as possible, improving the accuracy of skeleton node extraction.

In some embodiments, obtaining the centrality value of the node in the target data asset graph includes:

Obtain the centrality value of the asset node in the target data asset graph based on at least one first weight, where the first weight indicates the importance of the data asset corresponding to the asset node among the multiple data assets;

Based on at least one second weight, obtain the centrality value of the asset set node in the target data asset graph, the second weight indicating the importance of the data asset set corresponding to the asset set node in the multiple data assets.

In this way, setting different weights for asset nodes and simplified asset collection nodes can improve the accuracy of skeleton node extraction.

In response to the skeleton extraction operation, display a plurality of skeleton extraction options, the skeleton extraction options indicating how to extract the skeleton nodes;

In response to the selection operation of the skeleton extraction option, based on the skeleton node extraction method corresponding to the skeleton extraction option, skeleton nodes are extracted from the nodes of the target data asset graph.

In some embodiments, in response to selecting the skeleton extraction option, extracting skeleton nodes from nodes in the target data asset graph includes any of the following:

In response to the selection operation of the first skeleton extraction option, based on the default skeleton extraction parameters, extract skeleton nodes from the nodes of the target data asset graph;

In response to the selection operation of the second skeleton extraction option, display a configuration control for the skeleton extraction parameters, and in response to the operation of the configuration control, extract the skeleton node from the node of the target data asset graph;

In response to the selection operation of the third skeleton extraction option, a selection function for the nodes in the target data asset graph is provided, and in response to the selection operation of the nodes in the target data asset graph, the skeleton is extracted from the nodes of the target data asset graph. node.

By providing a "one-click extraction" skeleton extraction method, the efficiency of human-computer interaction can be improved; by providing a "parameter configuration" skeleton extraction method, it is convenient for users to configure skeleton node extraction parameters according to their needs, thereby meeting personalized needs and improving user experience. experience; by providing a "local extraction" skeleton extraction method, users can flexibly control the scope of skeleton extraction to meet personalized needs.

In some embodiments, the method further includes:

In response to an update operation on the first data asset graph, display a plurality of skeleton node update options, the skeleton node update options indicating an update mode of the skeleton node;

In response to the selection operation of the skeleton node update option, the skeleton node in the first data asset graph is updated based on the skeleton node update method corresponding to the skeleton node update option, and the updated first data asset graph is displayed.

In some embodiments, in response to the selection operation of the skeleton node update option, the skeleton node in the first data asset graph is updated based on the skeleton node update method corresponding to the skeleton node update option, including any of the following: item:

In response to the selection operation of the first skeleton node update option, display a configuration control for the skeleton extraction parameters, and in response to the operation of the configuration control, update the skeleton node in the first data asset graph;

In response to the selection operation of the second skeleton node update option, a calibration function for the skeleton node in the first data asset graph is provided, and in response to the calibration operation of the skeleton node in the first data asset graph, the first data asset is updated Skeleton nodes in the diagram.

By providing a variety of update functions for data asset graphs, it meets users' personalized needs and facilitates users' data analysis.

In some embodiments, the method further includes:

In response to the exploration operation of the target skeleton node in the first data asset graph, display a plurality of exploration options for the target skeleton node, the exploration options indicating the exploration mode of the target skeleton node, the target skeleton node is the first Any skeleton node in the data asset graph;

In response to the selection operation of the exploration option, the exploration method corresponding to the exploration option is determined, and based on the location of the target skeleton node in the first data asset graph, the data assets corresponding to the target skeleton node are displayed.

In some embodiments, in response to the selection operation of the exploration option, the exploration method corresponding to the exploration option is determined, and based on the location of the target skeleton node in the first data asset graph, the data assets corresponding to the target skeleton node are displayed. , including any of the following:

In response to the selection operation of the first exploration option, determine all data assets corresponding to the target skeleton node, and display all data assets corresponding to the target skeleton node based on the location of the target skeleton node in the first data asset graph;

In response to the selection operation of the second exploration option, determine the target association relationship corresponding to the second exploration option, determine the target data asset based on the target association relationship, and determine the location of the target skeleton node in the first data asset graph, Display the target data asset, which has the target association relationship with the data asset indicated by the target skeleton node.

By providing the exploration function for the data asset graph, it is easier for users to further understand local details, and use a certain data asset as a starting point to explore other data assets, which provides great convenience for users' data analysis.

In some embodiments, the target data asset graph displaying the multiple data assets includes:

The asset collection node is displayed in a first display style, and the asset node is displayed in a second display style, and the first display style is different from the second display style.

By displaying asset collection nodes and asset nodes in different display styles, it can help users understand simplified data assets efficiently and intuitively, thus improving the display effect of the data asset graph.

In some embodiments, the method further includes:

In response to the expansion operation of the first asset collection node in the target data asset graph, determine the data asset collection corresponding to the first asset collection node, and the first asset collection node is any asset collection node in the target data asset graph;

Based on the location of the first asset collection node in the target data asset graph, the data assets in the data asset collection corresponding to the first asset collection node are displayed.

By providing the expansion function for asset collection nodes, it is easier for users to understand simplified data assets and improve the user experience.

In some embodiments, displaying the data assets in the data asset set corresponding to the first asset set node includes:

The data assets in the data asset set corresponding to the first asset set node are displayed in a prominent display manner.

In this way, users can intuitively understand the expanded data assets and improve the user experience.

In some embodiments, the method further includes:

Based on the asset information of the multiple data assets, display an initial data asset graph of the multiple data assets, and multiple nodes in the initial data asset graph correspond to the multiple data assets;

Based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets, including:

In response to a simplification operation on the initial data asset graph, display a plurality of simplification options indicating a manner in which the initial data asset graph is simplified;

In response to the selection operation of the simplification option, the simplification method corresponding to the simplification option is determined, and based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets.

In some embodiments, in response to the selection operation of the simplification option, the simplification method corresponding to the simplification option is determined, and based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets. , including any of the following:

In response to the selection operation of the first simplification option, determining at least one data asset set from the multiple data assets based on the asset information of all data assets in the multiple data assets;

In response to the selection operation of the second simplified option, a selection function for the nodes in the initial data asset graph is provided, and in response to the selection operation of the nodes in the initial data asset graph, the assets based on the data assets corresponding to the selected nodes are information, and determine at least one data asset set from the data assets corresponding to the selected node.

By providing a "global simplification" simplification method, the efficiency of human-computer interaction can be improved; by providing a "local simplification" simplification method, users can flexibly control the scope of simplification, meet personalized needs, and improve user experience.

In some embodiments, in the collection of data assets,

Each group of data assets includes one data asset, the asset type of each group of data assets belongs to the first asset type, and there is a first association relationship between each group of data assets and the corresponding first data asset; or,

Each group of data assets includes one data asset. The asset type of each group of data assets belongs to a second asset type. Each group of data assets has a second association relationship with the corresponding second data asset, and has a second association relationship with the corresponding third data asset. There is a third association between them; or,

Each group of data assets includes two data assets. The asset type of each group of data assets includes at least one. There is a fourth association relationship between each group of data assets and the corresponding fourth data asset. Each group of data assets has a fourth association relationship with the corresponding fifth data asset. The data assets have a fifth association relationship, and the two data assets have a sixth association relationship.

Since the asset type composition and association relationship of each group of data assets are the same, and each group of data assets has the same association relationship with the corresponding data asset, the graph structure generated by the terminal based on the data asset collection will include multiple equivalent Structure, an equivalent structure corresponds to a set of data assets, and these equivalent structures show a high degree of similarity in topology, business, and visual aspects. That is to say, the graph structure corresponding to the data asset collection is a simplifiable structure and can also be considered redundant. remainder. Based on this, by simplifying the data asset collection and simplifying it into an asset collection node, the size of nodes and edges in the data asset graph can be reduced, thereby improving the display effect of the data asset graph.

In a second aspect, embodiments of the present application provide a data asset display device. The device includes at least one functional module. The at least one functional module is used to perform the above-mentioned first aspect or any possible implementation of the first aspect. The data asset display method provided.

In a third aspect, embodiments of the present application provide a computing device. The computing device includes a processor and a memory. The memory is used to store at least one piece of program code. The at least one piece of program code is loaded by the processor and implements the first step described above. A data asset display method provided by any possible implementation method of the aspect or the first aspect.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, the computer-readable storage medium being used to store at least one piece of program code, and the at least one piece of program code is used to implement the above-mentioned first aspect or any of the first aspects. A possible implementation method provides a data asset display method. The storage medium includes but is not limited to volatile memory, such as random access memory, and non-volatile memory, such as flash memory, hard disk drive (HDD), and solid state drive (SSD).

In a fifth aspect, embodiments of the present application provide a computer program product. When the computer program product is run on a computing device, the computing device implements the above-mentioned first aspect or any possible implementation manner of the first aspect. Provided data asset display method. The computer program product can be a software installation package. If it is necessary to implement the aforementioned data asset display method, the computer program product can be downloaded and executed on the computing device.

Description of the drawings

Figure 1 is a schematic diagram of a data asset graph provided by an embodiment of the present application;

Figure 2 is a schematic diagram of the display effect of a data asset graph provided by an embodiment of the present application;

Figure 3 is a schematic diagram of an implementation environment provided by an embodiment of the present application;

Figure 4 is a schematic diagram of the hardware structure of a computing device provided by an embodiment of the present application;

Figure 5 is a flow chart of a data asset display method provided by an embodiment of the present application;

Figure 6 is a schematic diagram showing the display effect of an initial data asset map provided by the embodiment of the present application;

Figure 7 is a schematic diagram of a simplified option provided by the embodiment of the present application;

Figure 8 is a partially simplified schematic diagram provided by an embodiment of the present application;

Figure 9 is a schematic diagram of a simplified structure provided by an embodiment of the present application;

Figure 10 is a schematic diagram of the display effect of an asset collection node provided by the embodiment of the present application;

Figure 11 is a schematic diagram showing the display effect of a target data asset diagram based on global simplification provided by the embodiment of the present application;

Figure 12 is a schematic diagram showing the display effect of a target data asset diagram based on partial simplification provided by the embodiment of the present application;

Figure 13 is a schematic diagram of expanding and displaying asset collection nodes provided by an embodiment of the present application;

Figure 14 is a flow chart of another data asset display method provided by an embodiment of the present application;

Figure 15 is a schematic diagram of a skeleton extraction option provided by an embodiment of the present application;

Figure 16 is a schematic diagram of adjusting skeleton extraction parameters provided by an embodiment of the present application;

Figure 17 is a schematic diagram of the display effect of the first data asset graph based on one-click extraction provided by the embodiment of the present application;

Figure 18 is a schematic diagram showing the display effect of a first data asset graph based on partial extraction provided by the embodiment of the present application;

Figure 19 is a schematic diagram of updating the first data asset graph provided by the embodiment of the present application;

Figure 20 is a schematic diagram of exploring a target skeleton node provided by an embodiment of the present application;

Figure 21 is a schematic diagram of global exploration of a first data asset graph provided by an embodiment of the present application;

Figure 22 is a schematic diagram of an application interface for displaying a data asset graph provided by an embodiment of the present application;

Figure 23 is a schematic structural diagram of a data asset display device provided by an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

It should be noted that the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application, All are authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions. For example, the asset information of the data assets involved in this application was obtained with full authorization.

In order to facilitate understanding, the key terms and key concepts involved in this application are first described below.

Data assets refer to data resources recorded in physical or electronic ways, such as documents and electronic data, that are owned or controlled by an enterprise and can bring future economic benefits to the enterprise.

Data asset graph refers to the graph structure composed of data assets as nodes and the relationships between data assets as edges by applying knowledge graph technology in the data asset management process. Usually, there are various relationships between asset entities corresponding to data assets. Based on this, when asset information of multiple data assets (such as asset types, relationships, etc.) is obtained, it can be based on these For the asset information of data assets, knowledge graph technology is applied to generate the corresponding data asset graph.

Schematically, refer to Figure 1, which is a schematic diagram of a data asset graph provided by an embodiment of the present application. As shown in Figure 1, taking the example that the asset types of data assets include 10 types and the relationships between data assets include 4 types, a corresponding data asset graph is constructed. In this data asset graph, nodes represent data assets, and edges represent relationships between data assets. For example, data assets include directories, databases, jobs, logical entities, data tables, job nodes, business attributes, fields, column lineage and analysis information, and association relationships include parent-child relationships (such as the association between databases and data tables). ), logical_physical relationship (such as the relationship between logical entities and data tables), data flow relationship (data_flow) (such as the relationship between data tables and job nodes), and primary key_foreign key relationships (primary key_foreign key , referred to as PK_FK) (such as the relationship between the primary key and foreign key in the data table). It should be noted that what is shown in Figure 1 here is only a schematic example and does not constitute a limitation on the data asset types and association relationship types in the embodiments of this application. In some embodiments, corresponding data can be constructed according to actual business needs. Asset map.

A vertex-edge biheterogeneous graph refers to a graph that includes multiple node types and multiple edge types. Schematically, the data asset graph shown in Figure 1 above includes multiple types of nodes and multiple types of connected edges. That is, the data asset graph is a point-edge double heterogeneous graph.

Network skeleton refers to the core structure containing key information of the original network. Illustratively, in some embodiments, by Nodes corresponding to important data assets in the data asset graph are extracted to obtain skeleton nodes, and the important data assets are displayed based on the extracted skeleton nodes. In this way, it can help users effectively understand the main topological features in the data asset graph, quickly mine high-value information, and facilitate users' data analysis.

The force-directed graph algorithm is a graph layout algorithm for visual drawing. By configuring nodes in a two-dimensional or three-dimensional space, the nodes are connected by lines, called edges. Forces are applied to nodes and edges, and the forces are calculated based on the relative positions of nodes and edges. According to the action of force, the motion trajectories of nodes and edges are calculated, and their energy is continuously reduced, and finally a stable state is reached. In some embodiments, this algorithm is also called a force-guided algorithm. For example, force guidance algorithms are usually implemented based on data-driven documents (D3, an open source JavaScript function library) to visually display data. In the embodiment of this application, the application of force guidance algorithm to realize the visual display of data asset graph is used as an example for explanation. It should be understood that in some embodiments, the corresponding graph layout algorithm can be selected according to actual business needs, and there is no limitation on this. .

Betweenness centrality, centrality indicates the degree to which a node (edge) is in a core position in the network. The greater the centrality, the more important the node (edge) is. Betweenness centrality indicates the influence of a node on the flow of information in the network. . In some embodiments, the betweenness centrality is obtained by a shortest path betweenness centrality algorithm or a random walk betweenness centrality algorithm, which is not limited. In the embodiments of this application, the application of the random walk betweenness centrality algorithm is used as an example for explanation. It should be understood that in some embodiments, the corresponding centrality algorithm can be selected according to actual business requirements, and this is not limited.

Random walk betweenness centrality algorithm, a centrality algorithm used to identify important topological structures of a network. Schematically, random walk means that given a graph and a starting point, a neighbor node is randomly selected, moved to the neighbor node, and then the current node is used as the starting point, and the above process is repeated. The sequence of randomly selected neighbor nodes constitutes a random walk process on the graph. Find the number of times that node s passes through node i in the process of traveling to node t, and use this number as the centrality value to measure the centrality of node i.

K-kernel decomposition algorithm, a network skeleton node extraction algorithm, its basic idea is to peel off the nodes with lower outer degree layer by layer (the degree of the node is used to indicate the number of adjacent nodes connected to the node), and the remaining Nodes in the graph have high influence. Schematically, it includes the following steps: (1) Set the threshold Ks (Ks is a positive integer); (2) K = 1; (3) Delete the node with degree K in the current graph; (4) Check whether the graph There are nodes with degree less than or equal to K. If there are nodes, repeat steps (3) and (4); (5) If K<Ks, then K+1, repeat steps (3) to (5).

The application scenarios involved in this application are introduced below.

The technical solution provided by the embodiments of this application can be applied in the field of data governance, and its application scenarios include various scenarios where data assets need to be displayed to improve user experience.

For example, with the rapid development of Internet technology, the data assets owned by enterprises are often large in number and complex in structure. In order to facilitate enterprises to grasp the current status of data assets, quickly sort out what data assets they own and how these data assets are distributed, they often Visually display the data assets owned by the enterprise. For example, enterprise users use the data asset management platform to view the data assets they own. In this case, the data asset management platform obtains the asset information of the relevant data assets and displays the relevant data assets based on the acquired asset information. However, ,Due to the large scale of data assets, the display ,effect when displaying global data assets at one time is often ,poor. Schematically, refer to Figure 2, which is a schematic diagram showing the display effect of a data asset graph provided by an embodiment of the present application. As shown in Figure 2, when global data assets are visually displayed in the form of a knowledge graph, the network topology is chaotic and the readability of the data asset graph is poor, making it difficult for users to find the graph quickly and efficiently in a complex structure. The main topological characteristics of the data cannot accurately determine the important data in the data asset map. assets. In this case, users have almost no way to start. They can neither clearly browse the global relationships of data assets nor use interactive operations to explore detailed information, which seriously affects the understanding and governance of data assets.

Based on this, embodiments of the present application provide a data asset display method, by determining qualified data asset sets from a large number of data assets, and displaying these data asset sets as corresponding asset set nodes in the data asset graph, thereby greatly Reduce the size of the nodes in the data asset graph, which means correspondingly reducing the size of the edges used to represent the relationships between nodes in the data asset graph, which improves the display effect of data assets and enables users to quickly grasp the global relationships of data assets. , improve user experience.

The implementation environment involved in this application is introduced below.

Figure 3 is a schematic diagram of an implementation environment provided by an embodiment of the present application. As shown in Figure 3, the implementation environment includes a terminal 301 and a server 302. The terminal 301 is directly or indirectly connected to the server 302 through a wireless network or a wired network.

The terminal 301 has a display function. Illustratively, the terminal 301 may be at least one of a smart phone, a game console, a desktop computer, an augmented reality terminal, a tablet computer, an e-book reader, and a laptop computer. The terminal 301 installs and runs an application program that supports the data asset display function. The application can be a client application or a browser application. For example, this application is a data asset management platform. Users can view data assets through the data asset management platform, grasp the overall situation of data assets, quickly sort out which data assets they have, how these assets are distributed, etc., from different levels. This process of mastering the overview information of data assets and then controlling the use of data assets will be further explained through subsequent method embodiments and will not be described again here. Illustratively, the terminal 301 is a terminal used by a user, and a user account is logged in an application program running in the terminal 301.

Server 302 is an independent physical server, or a server cluster or distributed file system composed of multiple physical servers, or it provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, and middleware. Cloud servers for basic cloud computing services such as software services, domain name services, security services, content delivery network (CDN), and big data and artificial intelligence platforms. The server 302 is used to provide background services for applications that support data asset display functions.

In some embodiments, the server 302 and the terminal 301 can work together during the presentation of data assets. For example, the server 302 is used to provide the calculation function of the position of each node when laying out the data asset graph, and to feed back the calculation results to the terminal 301. The terminal 301 is used to display the data asset graph according to the received calculation results and provide the user with information about the data asset graph. Various viewing operations, such as simplification operation, skeleton extraction operation, expansion operation, exploration operation, update operation, etc. This process will be introduced in subsequent embodiments and will not be described again here.

It should be noted that the terminal 301 may generally refer to one of multiple terminals, or a set of multiple terminals; the server 302 may generally refer to one of multiple servers, or a set of multiple servers. The embodiments of this application do not limit the quantity and type of each device in the implementation environment.

In some embodiments, the wireless network or wired network described above uses standard communication technologies and/or protocols. Networks include but are not limited to data center network (data center network), storage area network (SAN), local area network (LAN), metropolitan area network (MAN), wide area network (wide area network) , WAN), mobile, wired or wireless network, private network or any combination of virtual private network. In some implementations, data exchanged over the network is represented using technologies and/or formats including hyper text markup language (HTML), extensible markup language (XML), etc. In addition, you can also use services such as secure sockets layer (SSL), transport layer security (transport layer Conventional encryption technologies such as security (TLS), virtual private network (VPN), and Internet protocol security (IPsec) are used to encrypt all or part of the link. In other embodiments, customized and/or dedicated data communication technologies can also be used in place of or in addition to the data communication technologies described above.

The hardware structure of the terminal and server in the above implementation environment is introduced below.

Embodiments of the present application provide a computing device that can be configured as the above-mentioned terminal or server. Schematically, refer to FIG. 4 , which is a schematic diagram of the hardware structure of a computing device provided by an embodiment of the present application. As shown in FIG. 4 , the computing device 400 includes a memory 401 , a processor 402 , a communication interface 403 and a bus 404 . Among them, the memory 401, the processor 402, and the communication interface 403 implement communication connections between each other through the bus 404.

Memory 401 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory (RAM)) or other type that can store information and instructions. A dynamic storage device can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures and can be used by a computer Any other media accessible, but not limited to this. Illustratively, taking the computing device that can be configured as the above-mentioned terminal as an example, the memory 401 is used to store at least a piece of program code. When the program code stored in the memory 401 is executed by the processor 402, the processor 402 is used to perform the following method Steps performed by the terminal in the embodiment.

The processor 402 may be a network processor (NP), a central processing unit (CPU), an application-specific integrated circuit (ASIC), or an integrated circuit used to control the execution of the program of the present application. circuit. The processor 402 may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. The number of the processor 402 may be one or multiple. The communication interface 403 uses a transceiver module, such as a transceiver, to implement communication between the computing device 400 and other devices or communication networks. For example, the data can be obtained through the communication interface 403.

Among them, the memory 401 and the processor 402 can be provided separately or integrated together.

Bus 404 may include a path that carries information between various components of computing device 400 (eg, memory 401, processor 402, communication interface 403).

The data asset display method provided by the embodiment of this application is introduced below.

In the embodiment of this application, a data asset display method is provided, which can not only display the data asset graph, but also provide the user with a series of interactive exploration operations for the data asset graph, thereby achieving a comprehensive display and analysis of the entire data asset. explore. This data asset display method is introduced in detail below.

Figure 5 is a flow chart of a data asset display method provided by an embodiment of the present application. As shown in Figure 5, taking the data asset display method being applied to the terminal involved in the above implementation environment as an example, the data asset display method includes the following steps 501 to 507.

501. The terminal obtains asset information of multiple data assets. The asset information includes associations between data assets and asset types of data assets.

In this embodiment of the present application, the association relationship between data assets includes at least one. For example, the association relationship includes parent Sub-relationships, logical-physical relationships, data flow relationships, primary and foreign key relationships, etc. are specifically shown in Figure 1 above and will not be described again here. The asset type of the data asset includes at least one type. For example, the asset type includes directory, database, job, logical entity, data table, job node, business attribute, field, column lineage, asset analysis information, etc. The embodiments of this application do not limit the specific forms of associations between data assets and asset types of data assets.

Schematically, the terminal runs an application that supports the data asset display function and can display the application interface of the application. The application interface includes a data set selection control. In response to a triggering operation of the data set selection control, the terminal displays at least A data set for the user to select. In response to the selection operation of the target data set, the terminal obtains the asset information of multiple data assets in the target data set, so that the subsequent terminal can display the corresponding data asset graph according to the data set selected by the user. .

502. The terminal displays the initial data asset map of the multiple data assets based on the asset information of the multiple data assets.

In this embodiment of the present application, multiple nodes in the initial data asset graph correspond to the multiple data assets. Based on the asset information of the multiple data assets, the terminal applies a force guidance algorithm to generate an initial data asset graph of the multiple data assets and displays the initial data asset graph. The initial data asset graph is composed of multiple nodes and the edges between the multiple nodes, where one node is used to indicate a data asset, and the edge between any two nodes is used to indicate where the two nodes are. The association between corresponding data assets.

In some embodiments, based on the asset information of the multiple data assets, the terminal counts the types of asset types in the multiple data assets, the number of data assets corresponding to each asset type, the types of association relationships, and each association relationship. The corresponding quantity is obtained, and the statistical results are obtained. Based on the statistical results, the graph structure information of the initial data asset graph is displayed. The graph structure information indicates the node type, node number, edge type, and edge number in the initial data asset graph. . In this way, it is convenient for users to initially understand the basic panoramic information of these multiple data assets.

In some embodiments, taking any node in the initial data asset graph as a target node as an example, the terminal acquires the data asset corresponding to the target node in response to a data asset viewing operation on the target node in the initial data asset graph, Display the asset content of this data asset. For example, take the target node being used to indicate a data table as an example. In response to a data asset viewing operation on the target node, the terminal acquires the data table and displays the data table. That is, users can view the specific content of each data asset through the initial data asset map, so that users can understand the detailed information of the corresponding data assets according to their needs. It should be noted that the terminal can obtain the corresponding data assets when the user views a certain data asset, or can obtain multiple data assets when obtaining asset information of multiple data assets. The embodiment of this application is for This is not a limitation.

Schematically, refer to FIG. 6 , which is a schematic diagram showing the display effect of an initial data asset graph provided by an embodiment of the present application. As shown in Figure 6, the application interface displayed by the terminal includes a data set selection control 601. The terminal displays multiple data sets in response to the triggering operation of the data set selection control 601, and in response to the selection operation of the target data set, obtains The asset information of multiple data assets in the target data set is generated, and the initial data asset graph of the multiple data assets is generated, the initial data asset graph is displayed in the application interface, and the graph structure information of the initial data asset graph is displayed in the application interface.

503. In response to the simplification operation on the initial data asset graph, the terminal displays multiple simplification options, and the simplification options indicate a simplification method for the initial data asset graph.

In this embodiment of the present application, the plurality of simplification options include a first simplification option and a second simplification option, wherein the first simplification option indicates global simplification of the initial data asset graph, that is, based on all the initial data asset graphs. Data Assets Simplify this initial data asset graph. The second simplification option indicates partial simplification of the initial data asset graph, that is, simplification of the initial data asset graph based on part of the data assets in the initial data asset graph.

In some embodiments, the simplified operation refers to a triggering operation for the simplified control. Schematically, the terminal displays The application interface includes a simplified control for the initial data asset graph, and the terminal displays the plurality of simplified options in response to a triggering operation of the simplified control. For example, the terminal displays the multiple simplified options horizontally in the menu bar corresponding to the simplified control in the form of a menu bar; or displays the multiple simplified options vertically in the menu bar, which is not limited.

Schematically, refer to FIG. 7 , which is a schematic diagram of a simplified option provided by an embodiment of the present application. As shown in Figure 7, the application interface includes a simplified control 701. In response to the triggering operation of the simplified control 701, the terminal displays a first simplified option 702 ("Global Simplification") and a horizontally displayed menu bar corresponding to the simplified control 701. Second simplification option 703 ("local simplification").

It should be noted that the terminal can improve the efficiency of human-computer interaction by providing a simplification method of "global simplification"; by providing a simplification method of "local simplification", it can facilitate users to flexibly control the scope of simplification, meet personalized needs, and enhance user experience. .

504. In response to the selection operation of the simplification option, the terminal determines the simplification method corresponding to the simplification option, and determines at least one data asset set from the multiple data assets based on the asset information of the multiple data assets.

In this embodiment of the present application, the process of the terminal determining at least one data asset set from multiple data assets includes any of the following methods:

First, in response to the selection operation of the first simplified option, the terminal determines at least one data asset set from the multiple data assets based on the asset information of all data assets in the multiple data assets. That is, the terminal performs global simplification on the initial data asset graph in response to the selection operation of the first simplification option.

Second, in response to the selection operation of the second simplified option, the terminal provides a selection function for the nodes in the initial data asset graph, and in response to the selection operation of the nodes in the initial data asset graph, based on the selected node corresponding to asset information of the data assets, and determine at least one data asset set from the data assets corresponding to the selected node. That is, the terminal determines the nodes to be simplified in the initial data asset graph by selecting nodes in response to the selection operation of the second simplification option. For example, the terminal provides a "lasso tool" so that users can delineate the node range according to their needs without any limitation.

In some embodiments, the terminal displays the selected node in a highlighted display for the user to confirm whether to simplify the selected node to enhance the user experience. For example, the highlighting includes highlighting, adding shadows, adding text boxes, etc., but is not limited thereto.

Third, in response to the selection operation of the second simplified option, the terminal provides a selection function for the data assets in the initial data asset map, and in response to the selection operation of the data assets in the initial data asset map, based on the selected data The asset information of the asset determines at least one data asset set from the selected data assets. That is, in response to the selection operation of the second simplification option, the terminal determines the nodes to be simplified in the initial data asset graph by selecting the data assets.

Schematically, the terminal displays the time selection control in response to the selection operation of the second simplified option, and determines the target time period in response to the triggering operation of the time selection control, based on the multiple data assets within the target time period. The asset information of the generated data assets determines at least one data asset set from the data assets generated within the target time period. In other embodiments, the terminal can also display an asset type selection control so that users can select data assets they want to simplify based on different asset types. In this way, users' personalized needs for local simplification are met, thereby improving user experience.

Schematically, refer to FIG. 8 , which is a partially simplified schematic diagram provided by an embodiment of the present application. As shown in Figure 8, the application interface displayed by the terminal includes a second simplification option 801 ("local simplification"). In response to the selection operation of the second simplification option 801, the terminal displays a plurality of local simplification function controls, such as "set of "Search", "Time" and "Asset Type", etc., to facilitate users to select the corresponding local simplification function controls according to their needs to achieve local simplification. Taking "Lasso" as an example, the terminal is based on user Use the lasso tool to display the selected node in a highlighted manner, and determine at least one data asset collection from the selected data assets.

The following is an introduction to the principle for the terminal to determine at least one data asset set from multiple data assets in this step.

Illustratively, for any data asset collection, the data asset collection includes multiple groups of data assets. The composition of asset types and association relationships of each group of data assets are the same, and each group of data assets and the corresponding data assets have the same connection relation. In other words, since the asset type composition and association relationship of each group of data assets are the same, and each group of data assets has the same association relationship with the corresponding data asset, the graph structure generated by the terminal based on the data asset set will include multiple Equivalent structure. An equivalent structure corresponds to a set of data assets. These equivalent structures show a high degree of similarity in topology, business, and visual aspects. That is to say, the graph structure corresponding to the data asset collection is a simplifiable structure and can also be considered redundant. Based on this, by simplifying the data asset collection and simplifying it into an asset collection node, the size of nodes and edges in the data asset graph can be reduced, thereby improving the display effect of the data asset graph.

The following is an introduction to several types of data asset collections involved in the embodiments of the present application with reference to Figure 9. It should be understood that the following are only examples and do not constitute a limitation of the present application.

Figure 9 is a schematic diagram of a simplified structure provided by an embodiment of the present application. As shown in Figure 9, one reducible structure corresponds to one set of data assets. Multiple data assets involved in this application correspond to the following three reducible graph structures as an example.

(1) Sector cluster structure.

As shown in (a) in Figure 9, the sector cluster structure includes multiple equivalent structures. Each equivalent structure includes a node and an edge, and the edge connects the node to a central node. Connected, that is, the central node is connected to the nodes in each equivalent structure. It should be understood that an equivalent structure corresponds to a group of data assets in the data asset set. Therefore, in the first data asset set corresponding to the sector cluster structure, each group of data assets includes one data asset, and each group of data assets The asset type belongs to the first asset type, and each group of data assets has a first association relationship with the corresponding first data asset.

For example, if the first asset type is a field, the first data asset is Data Table 1, and the first association relationship is a parent-child relationship, then the data assets corresponding to all fields in the first data asset set have a parent-child relationship with Data Table 1. .

(2) Single bridge structure.

As shown in (b) of Figure 9, the single bridge structure includes multiple equivalent structures. Each equivalent structure includes a node (the node corresponds to two endpoints) and two connecting edges. These two The connecting edge is the connecting edge between this node and the two endpoints. It should be understood that an equivalent structure corresponds to a group of data assets in the data asset set. Therefore, in the second data asset set corresponding to the single bridge structure, each group of data assets includes one data asset, and each group of data assets The asset type belongs to the second asset type, and each group of data assets has a second association relationship with the corresponding second data asset, and a third association relationship with the corresponding third data asset. In some embodiments, the second association relationship and the third association relationship may be the same, which is not limited.

For example, if the second asset type is a job node, the second data asset is Data Table 2, the third data asset is Data Table 3, and both the second association relationship and the third association relationship are data flow relationships, then the second data asset set The data assets corresponding to all job nodes in have a data flow relationship with data table 2, and also have a data flow relationship with data table 3.

(3)Double bridge structure.

As shown in (c) of Figure 9, the double-bridge structure includes multiple equivalent structures. Each equivalent structure includes two nodes (each node corresponds to an endpoint) and three connecting edges. These three The connecting edges are the connecting edges of these two nodes and each The edge connecting a node to its endpoints. It should be understood that an equivalent structure corresponds to a group of data assets in the data asset set. Therefore, in the third data asset set corresponding to the double-bridge structure, each group of data assets includes two data assets, and each group of data assets The asset type includes at least one, each group of data assets has a fourth association relationship with the corresponding fourth data asset, and each group of data assets has a fifth association relationship with the corresponding fifth data asset. The two data There is a sixth correlation between assets. In some embodiments, the fourth association relationship, the fifth association relationship, and the sixth association relationship may be the same, which is not limited.

For example, the asset type of each group of data assets includes business attributes and fields. The fourth data asset is logical entity 1, the fifth data asset is data table 5, the fourth association relationship is parent-child relationship, the fifth association relationship is parent-child relationship, and the fourth association relationship is parent-child relationship. The sixth association relationship is a logical physical relationship, then there is a parent-child relationship between the data assets corresponding to all business attributes in the third data asset set and logical entity 1, and there is a parent-child relationship between the data assets corresponding to all fields and data table 5, and the business There is a logical physical relationship between the data assets corresponding to attributes and the data assets corresponding to fields.

After the above steps 503 and 504, the terminal determines at least one data asset set from multiple data assets in response to the simplification operation on the initial data asset graph, because the graph structure corresponding to these data asset sets belongs to a simplifiable graph structure. , therefore, the terminal can simplify the asset nodes corresponding to these data asset sets, that is, convert multiple asset nodes corresponding to one data asset set into one asset set node, so as to reduce the number of nodes and edges in the data asset graph. scale to improve the display effect of data asset graphs.

505. The terminal displays the target data asset graph of the multiple data assets based on the data asset set, the data assets other than the data asset set among the multiple data assets, and the correlation between the data assets.

In this embodiment of the present application, the target data asset graph includes an asset collection node and an asset node. The asset collection node corresponds to the data asset collection, and the asset node corresponds to the data asset. Schematically, the terminal applies a force guidance algorithm to generate target data assets for the multiple data assets based on the data asset set, the data assets other than the data asset set among the multiple data assets, and the correlation between the data assets. Figure, showing the target data asset diagram.

In some embodiments, the terminal displays the asset collection node in a first display style, and displays the asset node in a second display style, and the first display style is different from the second display style. For example, the first display style is a highlighted display, the second display style is a regular display, etc. The embodiments of this application are not limited to this, as long as the asset collection node and the asset node can be clearly distinguished in terms of visual display effect. By displaying asset collection nodes and asset nodes in different display styles, it can help users understand simplified data assets efficiently and intuitively, thus improving the display effect of the data asset graph.

In some embodiments, the terminal implements display of asset collection nodes in a first display style based on strong semantic primitive visual coding. This optional implementation is introduced below with reference to Figure 10. Figure 10 is a schematic diagram of the display effect of an asset collection node provided by an embodiment of the present application. As shown in Figure 10, the various simplified structures shown in Figure 9 are introduced as examples.

As shown in (a) of Figure 10 , for the first data asset set corresponding to the sector cluster structure, the asset set node corresponding to the first data asset set is displayed with the first primitive code. In some embodiments, based on the type of data assets in the first data asset collection, first graphic element codes of different colors are displayed to optimize the display effect of the asset collection nodes. For example, if the asset type of the data assets in the first data asset collection is a field and the asset type of the first data asset is a data table, a blue first primitive code will be displayed; if the asset type of the data assets in the first data asset collection is The type is a business attribute, and the asset type of the first data asset is a logical entity, then the purple first primitive code is displayed; if the asset type of the data asset in the first data asset collection is a job node, the asset type of the first data asset is job, the green first element code is displayed; if the asset type of the data asset in the first data asset collection is a data table, and the asset type of the first data asset is a database, Then the first primitive code of red is displayed, and so on.

As shown in (b) of FIG. 10 , for the second data asset set corresponding to the single-bridge structure, the asset set node corresponding to the second data asset set is displayed with the second primitive code. In some embodiments, based on the type of data assets in the second data asset collection, second primitive codes of different colors are displayed to optimize the display effect of the asset collection node. This process is the same as the above figure (a), so it will not be described again.

As shown in (c) of Figure 10 , for the third data asset set corresponding to the double-bridge structure, the asset set node corresponding to the third data asset set is displayed with the third primitive encoding. In some embodiments, based on the type of data assets in the third data asset collection, third graphic element codes of different colors are displayed to optimize the display effect of the asset collection node. This process is the same as the above figure (a), so it will not be described again.

In addition, based on the above step 503, it can be known that the terminal provides two simplification methods for the initial data asset graph (global simplification and local simplification). Correspondingly, the effect of the target data asset graph displayed by the terminal is different. The display effect of the target data asset graph is introduced below with reference to Figures 11 and 12.

Figure 11 is a schematic diagram showing the display effect of a target data asset diagram based on global simplification provided by an embodiment of the present application. As shown in (a) of Figure 11 , in response to the selection operation of the first simplification option ("global simplification"), the terminal determines from the multiple data assets based on the asset information of all data assets in the multiple data assets. At least one data asset collection displays a target data asset graph. In the target data asset graph, asset collection nodes are displayed with the primitive coding shown in Figure 10. In addition, as shown in (b) of Figure 11, a local area of the target data asset graph is intercepted to show the simplification effect more clearly.

Figure 12 is a schematic diagram showing the display effect of a target data asset diagram based on partial simplification provided by the embodiment of the present application. As shown in (a) of Figure 12, the terminal provides a "lasso" function in response to the selection operation of the second simplification option ("local simplification"). Based on the asset information of the data asset corresponding to the selected node, Determine at least one data asset set from the data assets corresponding to the selected node, and display the target data asset graph. The specific display effect is shown in (b) of Figure 12.

After the above steps 501 to 505, based on the obtained asset information of multiple data assets, the terminal provides a variety of simplified functions for the initial data asset graph on the basis of displaying the initial data asset graph, so that the user can select the corresponding one according to the needs. Simplified method, so that the terminal can determine at least one data asset set based on the simplified method selected by the user and display the corresponding target data asset graph. Moreover, based on the above Figures 11 and 12, it can be seen that compared with the initial data asset graph , the size of nodes and edges in the target data asset graph is greatly reduced, which effectively avoids visual clutter, improves the display effect of the data asset graph, and enables users to intuitively understand the global distribution of multiple data assets.

It should be understood that for global data asset diagrams of large-scale data assets, since the amount of data is too large, displaying a huge amount of data at one time has a significant impact on the visual effect of the data asset diagram. The diagram simplification provided by the embodiment of the present application is used. The function aggregates a large number of nodes and edges and uses strong semantic visual primitive coding to represent the simplified structure (or aggregation structure), thereby reducing redundant information in the graph and helping users reduce visual impact.

It should be noted that in other embodiments, when the terminal obtains the asset information of multiple data assets, it can directly display the target data asset graph based on global simplification. This process is also the process of "the terminal obtains multiple data assets". asset information; based on the asset information of the multiple data assets, determine at least one data asset set from the multiple data assets; based on the data asset set, the data assets in the multiple data assets other than the data asset set, and The correlation between data assets displays the target data asset graph of the multiple data assets. In this way, the simplified data asset graph can be directly displayed, thereby avoiding the user's manual selection of the simplified method and improving the efficiency of human-computer interaction.

In addition, while displaying the target data asset graph, the terminal can also provide an expansion function for asset collection nodes so that users can view simplified displayed data assets. This optional implementation method is introduced below through steps 506 and 507. Mode.

506. In response to the expansion operation of the first asset collection node in the target data asset graph, the terminal determines the data asset collection corresponding to the first asset collection node.

In this embodiment of the present application, the first asset collection node is any asset collection node in the target data asset graph. The expansion operation may be a click operation, a double-click operation, a long-time stay operation, etc. on the first asset collection node, which is not limited.

507. Based on the location of the first asset collection node in the target data asset graph, the terminal displays the data assets in the data asset collection corresponding to the first asset collection node.

In this embodiment of the present application, the terminal applies a force guidance algorithm based on the location of the first asset collection node in the target data asset graph to display the data assets in the data asset collection corresponding to the first asset collection node. In some embodiments, the terminal displays the data assets in the data asset set corresponding to the first asset set node in a highlighted display manner. For example, the expanded data asset is wrapped by a semi-transparent irregular convex hull, and the range changes as the number of nodes changes. In this way, users can intuitively understand the expanded data assets and improve the efficiency of human-computer interaction. Of course, in some embodiments, the terminal can also recover the expanded data assets in response to the shrink operation on the basis of expanding and displaying the first asset collection node. For example, the expansion operation is a click operation on the first asset collection node, and the shrink operation is a click operation on the expanded range, which is not limited.

Schematically, refer to Figure 13, which is a schematic diagram of an expanded display asset collection node provided by an embodiment of the present application. As shown in (a) of Figure 13, in response to the expansion operation of the first asset collection node, the terminal highlights the data in the data asset collection corresponding to the first asset collection node at the location of the first asset collection node. assets. In addition, as shown in (b) of Figure 13, another expanded display rendering is provided to clearly illustrate the above display effect.

It should be understood that based on the same process as the above step 502, when the terminal displays the target data asset map, the user can also view the specific content of each data asset through the target data asset map, so that the user can understand the corresponding data according to the needs. The details of the assets will not be repeated here.

In summary, embodiments of this application provide a data asset display method. When displaying multiple data assets, at least one data asset set is determined from the multiple data assets based on the asset information of the multiple data assets. These data asset collections are displayed as corresponding asset collection nodes in the data asset graph in a graph visualization manner, thereby greatly reducing the size of nodes and edges in the data asset graph, improving the display effect of data assets, and enabling users to Quickly grasp the overall relationship of data assets and improve user experience.

Based on the content shown in the above Figures 5 to 13, a data asset display method provided by the embodiment of the present application is introduced, that is, for multiple data assets, the terminal can based on at least one data asset set among the multiple data assets to Graph visualization shows the global relationship of data assets. In other embodiments, the terminal can further simplify based on the above target data asset graph and display important data assets in the target data asset graph by extracting skeleton nodes, thereby further improving the display effect of data assets. , to provide convenience for users’ data analysis.

This data asset display method based on extracting skeleton nodes is introduced below.

Figure 14 is a flow chart of another data asset display method provided by an embodiment of the present application. As shown in Figure 14, taking the application of the data asset display method to the terminal involved in the above implementation environment as an example, the data asset display method includes the following steps 1401 to 1408.

1401. The terminal obtains the asset information of multiple data assets. Based on the asset information of the multiple data assets, the terminal obtains the asset information of the multiple data assets. Determine at least one data asset collection among the data assets and display the target data asset diagram of the multiple data assets.

In the embodiment of the present application, the process of the terminal displaying the target data asset graph based on the asset information of multiple data assets is the same as the above embodiment shown in Figure 5, so it will not be described again here.

1402. In response to the skeleton extraction operation on the target data asset graph, the terminal displays multiple skeleton extraction options, and the skeleton extraction options indicate the extraction method of the skeleton nodes.

In this embodiment of the present application, the plurality of skeleton extraction options include a first skeleton extraction option, a second skeleton extraction option, and a third skeleton extraction option. Wherein, the first skeleton extraction option indicates that the skeleton is extracted from the target data asset graph based on the default skeleton extraction parameters; the second skeleton extraction option indicates that the skeleton is extracted from the target data asset graph based on the configured skeleton extraction parameters; the third skeleton The extraction option indicates the skeleton extraction of the target data asset graph based on the selected nodes.

In some embodiments, the skeleton extraction operation refers to a triggering operation for the skeleton extraction control. Schematically, the application interface displayed by the terminal includes a skeleton extraction control for the target data asset graph, and the terminal displays the multiple skeleton extraction options in response to a triggering operation of the skeleton extraction control. For example, the terminal displays the multiple simplified options horizontally in the menu bar corresponding to the skeleton extraction control in the form of a menu bar; or displays the multiple simplified options vertically in the menu bar, which is not limited.

Schematically, refer to FIG. 15 , which is a schematic diagram of a skeleton extraction option provided by an embodiment of the present application. As shown in Figure 15, the application interface includes a skeleton extraction control 1501. In response to the triggering operation of the skeleton extraction control 1501, the terminal horizontally displays the first skeleton extraction option 1502 ("One-click" in the menu bar corresponding to the skeleton extraction control 1501. "Extraction"), the second skeleton extraction option 1503 ("Parameter Configuration"), and the third skeleton extraction option 1504 ("Local Extraction").

It should be noted that the terminal can improve the efficiency of human-computer interaction by providing a "one-click extraction" skeleton extraction method; by providing a "parameter configuration" skeleton extraction method, it can facilitate users to configure skeleton node extraction parameters according to their needs, thereby satisfying Personalized needs improve user experience; by providing a "local extraction" skeleton extraction method, users can flexibly control the scope of skeleton extraction to meet personalized needs.

1403. In response to the selection operation of the skeleton extraction option, the terminal extracts skeleton nodes from the nodes of the target data asset graph based on the skeleton node extraction method corresponding to the skeleton extraction option.

In this embodiment of the present application, the terminal extracts skeleton nodes from the nodes of the target data asset graph based on the skeleton node extraction method corresponding to the skeleton extraction option, including any of the following methods:

First, in response to the selection operation of the first skeleton extraction option, the terminal extracts skeleton nodes from nodes in the target data asset graph based on default skeleton extraction parameters.

Among them, the default skeleton extraction parameters are preset skeleton extraction parameters. Illustratively, the default skeleton extraction parameters indicate preset weights corresponding to different types of data assets and preset weights corresponding to different types of associations. It should be understood that the greater the preset weight corresponding to a certain type of data asset, the more likely it is that this type of data asset will become a skeleton node and be extracted. Similarly, the greater the preset weight corresponding to a certain type of association relationship. , the more likely this type of association is to be extracted as a skeleton node. In other embodiments, the default skeleton extraction parameter indicates a preset weight corresponding to the association between any two types of data assets, which is not limited in the embodiments of the present application.

For example, take the asset type of data assets including fields and data tables as an example. When the association between fields and data tables is a parent-child relationship, the preset weight corresponding to the association is 80%. The association between fields and data tables The relationship is a data flow relationship, and the preset weight corresponding to this association relationship is 70%. It should be noted that the examples here are only illustrative. In some embodiments, the default skeleton extraction parameters can be set according to requirements, as long as the default skeleton extraction parameters can indicate the target It is sufficient to extract skeleton nodes that meet the requirements from the data asset graph. The embodiment of this application does not limit the specific form of the default skeleton extraction parameters.

Second, in response to the selection operation of the second skeleton extraction option, the terminal displays the configuration control for the skeleton extraction parameters, and in response to the operation of the configuration control, extracts the skeleton nodes from the nodes of the target data asset graph. For example, the configuration control is a draggable slider, and the user can adjust the skeleton extraction parameters by operating the slider. For another example, the configuration control is an editable input box, and the user can adjust the skeleton extraction parameters by inputting corresponding parameters, etc. The embodiment of the present application does not limit the specific form of the configuration control, as long as the configuration control can adjust the skeleton. Just extract the function of parameters.

Schematically, refer to FIG. 16 , which is a schematic diagram of adjusting skeleton extraction parameters according to an embodiment of the present application. As shown in Figure 16, the application interface includes a second skeleton extraction option ("parameter configuration"). In response to the selection operation of the second skeleton extraction option, the terminal displays configuration controls for the skeleton extraction option, such as a draggable slider. block to facilitate the user to adjust the corresponding skeleton extraction parameters according to needs. The terminal responds to the operation of the configuration control and extracts the skeleton nodes from the nodes of the target data asset graph.

Third, the terminal provides a selection function for nodes in the target data asset graph in response to the selection operation of the third skeleton extraction option, and in response to the selection operation of the nodes in the target data asset graph, selects the node from the target data asset graph. Extract skeleton nodes from the nodes. That is, the user can flexibly select the range of skeleton node extraction, such as using the "lasso" tool provided by the terminal to select the range of skeleton node extraction, etc., and there is no limit to this. Of course, in other embodiments, the terminal can also provide a selection function for data assets in the target data asset graph, so that the user can determine the range of skeleton node extraction by selecting data assets. It should be noted that the specific implementation of the third method is the same as the process of partially simplifying the initial data asset graph in the above step 504, so it will not be described again here.

The process of extracting skeleton nodes from the nodes of the target data asset graph in this step is introduced below.

Schematically, taking the default skeleton extraction parameter indicating the preset weight corresponding to the association between any two types of data assets as an example, the process of extracting skeleton nodes by the terminal includes the following steps A to C:

Step A: Obtain the centrality value of the node in the target data asset graph. The centrality value indicates the importance of the data asset corresponding to the node among the multiple data assets.

Among them, the terminal applies a centrality algorithm to calculate the centrality value of the node in the target data asset graph based on at least one preset weight. For example, the centrality algorithm is a random walk betweenness centrality algorithm, which is not limited.

It should be noted that, based on the above embodiment shown in Figure 5, it can be known that the target data asset graph includes asset collection nodes and asset nodes. In some embodiments, the asset collection nodes and asset nodes correspond to different preset weights. Illustratively, the terminal obtains the centrality value of the asset node in the target data asset graph based on at least one first weight, which indicates the importance of the data asset corresponding to the asset node in the multiple data assets. ; Based on at least one second weight, obtain the centrality value of the asset collection node in the target data asset graph, the second weight indicating the importance of the data asset collection corresponding to the asset collection node in the multiple data assets. In this way, setting different weights for asset nodes and simplified asset collection nodes can improve the accuracy of skeleton node extraction.

Step B: Obtain the core value of the node in the target data asset graph based on the centrality value and residual degree of the node in the target data asset graph.

The residual degree indicates the number of deleted adjacent nodes of the node, and the core value indicates the number of nodes connected to the node. The terminal calculates the core value of the node in the target data asset graph based on the centrality value and residual degree of the node in the target data asset graph. Illustratively, the terminal calculates the core value K of the node through the following formula (1).
K=((node degree+0.7×residual degree)×node centrality value) ^0.5 (1)

In the formula, the node degree indicates the number of edges associated with the node. Through the above formula (1), the K value of the cluster center node in the target data asset graph is appropriately increased, thereby fully considering the importance of the cluster center node, so as to retain more cluster center nodes and improve the accuracy of skeleton node extraction. It should be noted that the parameter 0.7 in the above formula (1) is an example and can be set according to requirements, and is not limited to this.

Step C: Extract skeleton nodes from the nodes in the target data asset graph based on the core values of the nodes in the target data asset graph.

Among them, the terminal applies the K-core decomposition algorithm and extracts skeleton nodes from the nodes of the target data asset graph based on the core values of the nodes in the target data asset graph. Schematically, the terminal sets a threshold Ks and compares the minimum core value Km in the target data asset graph with the threshold Ks. If Km ≤ Ks, deletes the node corresponding to the Km and updates the centrality values of all adjacent nodes of the node. and residual degree. Further, delete the nodes whose core value is less than or equal to Km in the target data asset graph, and update the centrality value and residual degree of the adjacent nodes of the deleted node. This iteration continues until there is no need to delete the node. At this time The remaining nodes in the target data asset graph are the extracted skeleton nodes.

It should be noted that the method of extracting skeleton nodes shown in the above steps A to C is only an optional implementation method provided by the embodiment of the present application. In some embodiments, the terminal can also apply other algorithms for extracting skeleton nodes. To achieve the extraction of skeleton extraction nodes, such as local adaptive network sparsification algorithm or differential filtering algorithm, etc., any other algorithm for extracting important nodes in the network during the graph visualization process can be applied to the embodiments of this application , there is no limit to this.

After the above steps 1402 and 1403, the terminal responds to the skeleton extraction operation for the target data asset graph and extracts skeleton nodes from the nodes of the target data asset graph, because the data assets corresponding to these skeleton nodes belong to a relatively large number of data assets. important data assets. Therefore, by subsequently displaying these skeleton nodes, the terminal can further reduce the size of nodes and edges in the data asset graph while displaying the main relationship structures of multiple data assets and improve the display effect of the data asset graph. .

1404. The terminal displays the first data asset graph of the multiple data assets based on the extracted skeleton nodes.

In this embodiment of the present application, the terminal applies a force guidance algorithm based on the extracted skeleton nodes, generates a first data asset graph corresponding to these skeleton nodes, and displays the first data asset graph.

In addition, based on the above step 1402, it can be known that the terminal provides multiple extraction methods for skeleton nodes. Correspondingly, the effect of the first data asset graph displayed by the terminal is different. The display effect of the first data asset graph is introduced below with reference to Figure 17 and Figure 18 .

Figure 17 is a schematic diagram showing the display effect of the first data asset graph based on one-click extraction provided by the embodiment of the present application. As shown in Figure 17, in response to the selection operation of the first simplified option ("one-click extraction"), the terminal extracts skeleton nodes from the nodes of the target data asset graph based on the default skeleton extraction parameters, and displays the first data asset graph. . It should be understood that the effect of the terminal extracting the skeleton nodes and displaying the first data asset graph based on configuring the skeleton extraction parameters is the same as in Figure 17, so no details will be given.

Figure 18 is a schematic diagram showing the display effect of a first data asset graph based on partial extraction provided by an embodiment of the present application. As shown in Figure 18, in response to the selection operation of the third skeleton extraction option ("local extraction"), the terminal provides a "lasso" function, based on the selected node, extracts the skeleton node from the selected node, and displays the third skeleton extraction option. A data asset map.

After the above steps 1401 to 1404, the terminal provides a skeleton extraction function for the target data asset graph on the basis of displaying the target data asset graph, so that the user can select the corresponding skeleton extraction method according to the needs, so that the terminal can based on the skeleton selected by the user. Extraction method is used to extract skeleton nodes and display the corresponding first data asset graph, and, based on the above As can be seen from Figures 17 and 18, compared with the target data asset graph, the size of nodes and edges in the first data asset graph is further reduced, and the distribution of important data assets among multiple data assets is intuitively displayed.

It should be understood that the target data asset graph often includes multi-cluster and multi-bridge structures. Through the above-mentioned skeleton extraction function, finding important nodes and important relationships in the data asset graph can help users understand the main structural features of the data asset graph and improve user experience. Experience and efficiency of human-computer interaction.

It should be noted that in other embodiments, when the terminal obtains asset information of multiple data assets, it can directly display the first data asset graph based on one-click extraction. This process is also "the terminal obtains multiple data assets." asset information of one data asset; based on the asset information of the multiple data assets, determine at least one data asset set from the multiple data assets; based on the data asset set, the multiple data assets other than the data asset set Data assets and the correlation between data assets, generate a target data asset graph, extract skeleton nodes from the nodes of the target data asset graph, and display the first data asset graph based on the extracted skeleton nodes." In this way, A network skeleton that can display multiple data assets at once to improve the efficiency of human-computer interaction.

In addition, while displaying the first data asset graph, the terminal can also provide an update function and an exploration function for the first data asset graph, which will be introduced below through steps 1405 to 1408.

1405. In response to the update operation of the first data asset graph, the terminal displays multiple skeleton node update options, and the skeleton node update options indicate the update method of the skeleton node.

In this embodiment of the present application, the multiple skeleton node update options include a first skeleton node update option and a second skeleton node update option. The first skeleton node update option indicates updating the first data asset graph based on the configured skeleton extraction parameters; the second skeleton node update option indicates updating the first data asset graph based on the selected skeleton node.

In some embodiments, the update operation refers to a trigger operation for updating the skeleton control. Schematically, the application interface displayed by the terminal includes a skeleton update control for the first data asset graph, and in response to a triggering operation of the skeleton update control, the multiple skeleton node update options are displayed. For example, the terminal displays the multiple skeleton node update options horizontally in the menu bar corresponding to the skeleton update control in the form of a menu bar; or displays the multiple skeleton node update options vertically in the menu bar, and does not do this. limited.

1406. In response to the selection operation of the skeleton node update option, the terminal updates the skeleton node in the first data asset graph based on the skeleton node update method corresponding to the skeleton node update option, and displays the updated first data asset. picture.

In this embodiment of the present application, the terminal updates the skeleton node in the first data asset graph based on the skeleton node update method corresponding to the skeleton node update option, including any of the following methods:

The first method is to display a configuration control for skeleton extraction parameters in response to the selection operation of the first skeleton node update option, and in response to the operation of the configuration control, update the skeleton node in the first data asset graph. This process is the same as that shown in Figure 16 above, so it will not be described again.

Second, in response to the selection operation of the second skeleton node update option, provide a calibration function for the skeleton node in the first data asset graph, and in response to the calibration operation of the skeleton node in the first data asset graph, update the The skeleton node in the first data asset graph.

For example, the calibration operation may be a click operation, a double-click operation or a long-time dwell operation on the skeleton node, etc., which is not limited. Taking the calibration operation as a click operation as an example, the user can click a certain skeleton node to cause the terminal to display a menu item for deleting the skeleton node. In this way, the user can manually delete the first data asset graph. Skeleton nodes and edges meet personalized needs. Of course, in other embodiments, the terminal can also According to the asset data graph, non-skeleton nodes are displayed. In response to the calibration operation of the non-skeleton nodes (that is, the nodes deleted in the above step 1403), the first data asset graph is updated, thereby facilitating the user to manually add the nodes that need to be displayed. Skeleton nodes further meet personalized needs. For example, the display styles of non-skeleton nodes and skeleton nodes are different to facilitate user distinction, and there is no limitation on this.

Schematically, refer to Figure 19, which is a schematic diagram of updating the first data asset graph provided by an embodiment of the present application. As shown in Figure 19, the terminal displays the corresponding menu item "Delete Node" in response to the calibration operation on the skeleton node, and deletes the skeleton node in response to the click operation on the menu item; in addition, the terminal responds to the calibration operation on the non-skeleton node. The calibration operation displays the corresponding menu item "Display Node", and in response to the click operation on the menu item, the non-skeleton node is updated to a skeleton node for display.

1407. In response to the exploration operation of the target skeleton node in the first data asset graph, the terminal displays multiple exploration options for the target skeleton node, where the exploration options indicate an exploration method for the target skeleton node.

In this embodiment of the present application, the target skeleton node is any skeleton node in the first data asset graph. The multiple exploration options include a first exploration option and a second exploration option, wherein the first exploration option indicates exploring all data assets corresponding to the target skeleton node, and the second exploration option indicates exploring the target skeleton node based on the target association relationship. Explore the corresponding data assets. It should be understood that there may be multiple second search options to correspond to multiple associations, which is not limited in the embodiments of the present application.

In some embodiments, the exploration operation is a click operation, a double-click operation or a long-time stay operation on the target skeleton node, which is not limited. Illustratively, in response to a click operation on the target skeleton node, the terminal vertically displays multiple exploration options in the menu bar corresponding to the target skeleton node in the form of a menu bar, which is not limited.

It should be noted that the terminal can display all the relationships of the target skeleton node at once by providing a "global exploration" exploration method for the target skeleton node; by providing a "target correlation exploration" exploration method, it can facilitate users to flexibly Control the scope of exploration to meet personalized needs and improve user experience.

1408. In response to the selection operation of the exploration option, the terminal determines the exploration method corresponding to the exploration option, and displays the data assets corresponding to the target skeleton node based on the location of the target skeleton node in the first data asset graph.

In this embodiment of the present application, the process of the terminal displaying the data assets corresponding to the target skeleton node based on the location of the target skeleton node in the first data asset graph includes any of the following methods:

First, the terminal determines all data assets corresponding to the target skeleton node in response to the selection operation of the first exploration option, and displays all data assets corresponding to the target skeleton node based on the location of the target skeleton node in the first data asset graph. Data assets. Among them, the terminal obtains the asset information of all data assets corresponding to the target skeleton node, applies a force guidance algorithm, and displays all data assets corresponding to the target skeleton node based on the location of the target skeleton node.

Second, the terminal determines the target association corresponding to the second exploration option in response to the selection operation of the second exploration option, and determines the target data asset based on the target association, based on the target in the first data asset map. The location of the skeleton node displays the target data asset, and the target data asset has the target association relationship with the data asset indicated by the target skeleton node.

Schematically, refer to FIG. 20 , which is a schematic diagram of exploring a target skeleton node provided by an embodiment of the present application. As shown in (a) of Figure 20, in response to the exploration operation on the target skeleton node, the terminal vertically displays a first exploration option 2001 ("Global Exploration") and a plurality of second exploration options 2002 ("Global Exploration") in the menu bar. "Exploration of target association relationships"). Taking the terminal responding to the selection operation of the first exploration option as an example, the display effect of global exploration for the target skeleton node is as shown in (b) of Figure 20 .

It should be noted that in the above steps 1407 and 1408, the exploration function for a skeleton node is introduced as an example. In other embodiments, the terminal provides a global exploration function for the first data asset graph to facilitate All data assets corresponding to each skeleton node are displayed at one time (it can also be understood as restoring and displaying the aforementioned target data asset graph). Schematically, the application interface displayed by the terminal includes a global exploration control for the first data asset graph, and in response to a triggering operation of the global exploration control, the target data asset graph is displayed. The display effect of this process is shown in Figure 21. Figure 21 is a global exploration schematic diagram of a first data asset graph provided by an embodiment of the present application. As shown in Figure 21, the terminal displays the first data asset on the application interface. The global exploration control 2101 of the graph displays the target data asset graph in response to a triggering operation on the global exploration control 2101.

It should be understood that the first data asset map shows the distribution of important data assets among multiple data assets. Through the exploration function provided in the above steps 1407 and 1408, it can facilitate the user to further understand the local detailed information, and use a certain data asset to As a starting point to explore other data assets, it provides great convenience for users’ data analysis. Moreover, based on the same process as the embodiment shown in Figure 5 above, when the terminal displays the first data asset diagram, the user can also view the specific content of each data asset through the first data asset diagram, which is convenient for the user Understand the detailed information of the corresponding data assets according to your needs, which will not be detailed here.

In addition, the embodiment of the present application does not limit the execution order of the above-mentioned steps 1405 to 1408. The terminal can execute corresponding steps in response to different operations of the user on the first data asset graph.

In summary, embodiments of this application provide a data asset display method. When displaying multiple data assets, at least one data asset set is determined from the multiple data assets based on the asset information of the multiple data assets. These data asset collections are displayed as corresponding asset collection nodes in the data asset graph, thereby greatly reducing the size of nodes and edges in the data asset graph, improving the display effect of data assets, and enabling users to quickly grasp the global relationship of data assets. Improve user experience. Furthermore, important data assets in the target data asset graph are displayed by extracting skeleton nodes, thereby further reducing the size of nodes and edges in the data asset graph and improving the display effect of the data asset graph; and, by It provides update functions and exploration functions for data asset graphs, which meets users' personalized needs and facilitates users' data analysis.

Based on the content shown in the above Figures 5 to 21, various optional implementations of the data asset display method provided by the embodiment of the present application are introduced. The following is an example of the data asset display method provided by the embodiment of the present application with reference to Figure 22. .

Figure 22 is a schematic diagram of an application interface for displaying a data asset graph provided by an embodiment of the present application. As shown in Figure 22, a data set selection control 2201 is displayed on the left side of the application interface, and a simplified control 2202, a skeleton extraction control 2203, and a global exploration control 2204 are displayed on the upper right side of the application interface.

Schematically, the data asset display method includes the following steps 1 to 4.

Step 1. The terminal displays multiple data sets in response to the triggering operation of the data set selection control 2201. In response to the selection operation of the target data set, the terminal obtains the asset information of multiple data assets in the target data set. On the right side of the application interface The designated area displays the initial data asset map of the multiple data assets. At the same time, the graph structure information of the initial data asset graph is displayed in the application interface.

Step 2: In response to the triggering operation of the simplification control 2202, the terminal displays the simplification options "global simplification" and "local simplification", and in response to the selection operation of any simplification option, determines the simplification method corresponding to the simplification option, based on For the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets, and the corresponding target data asset map is displayed in the designated area on the right side of the application interface. Further, the terminal can also provide the asset collection node in the target data asset graph. The expansion display function will not be described again here.

Step 3: In response to the triggering operation of the skeleton extraction control 2203, the terminal displays the skeleton extraction options "one-click extraction", "parameter configuration" and "local extraction", and in response to the selection operation of any skeleton extraction option, determine the The skeleton node extraction method corresponding to the skeleton extraction option extracts skeleton nodes from the nodes of the target data asset graph, and displays the corresponding first data asset graph in the designated area on the right side of the application interface. Further, the terminal can also provide an update function for the first data asset graph so that the user can adjust the skeleton nodes in the first data asset graph according to needs, which will not be described again here.

Step 4: The terminal displays the target data asset graph in response to the triggering operation on the global exploration control 2204. Alternatively, the terminal responds to the exploration operation on any skeleton node and implements the exploration function on the skeleton node, which will not be described again here.

It should be understood that the specific implementation manner of the above-mentioned steps 1 to 4 is the same as that shown in the above-mentioned FIGS. 5 to 21 , and therefore will not be described again.

In addition, it should be noted that the drawings provided in the embodiments of the present application are only schematic illustrations and do not constitute a limitation of the present application. For example, in the data asset graph mentioned in the attached figure, nodes of different asset types can be displayed through different display styles, and the edges corresponding to different associations can also be displayed through different display styles. For another example, the layout of various controls, options, etc. in the application interface can be adjusted according to actual needs. For another example, when displaying options, adjust the interface layout so that the options do not block the display of the data asset diagram, etc. Moreover, in the data asset graph mentioned in the accompanying drawings, the number of nodes, node types, number of edges, etc. are all examples. In some embodiments, the edges in the data asset graph have arrows to indicate information. The flow direction is not limited in the embodiments of this application.

In summary, embodiments of this application provide a data asset display method. When displaying multiple data assets, at least one data asset set is determined from the multiple data assets based on the asset information of the multiple data assets. These data asset collections are displayed as corresponding asset collection nodes in the data asset graph, thereby greatly reducing the size of nodes and edges in the data asset graph, improving the display effect of data assets, and enabling users to quickly grasp the global relationship of data assets. Improve user experience.

Furthermore, important data assets in the target data asset graph are displayed by extracting skeleton nodes, thereby further reducing the size of nodes and edges in the data asset graph and improving the display effect of the data asset graph; and, by It provides update functions and exploration functions for data asset graphs, which meets users' personalized needs and facilitates users' data analysis.

It can be seen that the data asset graph visualization and interactive exploration method proposed in this application vividly and intuitively displays data assets and the connections between assets to users in the form of graph visualization, and greatly reduces the scale of the data asset graph through graph simplification. The network skeleton is used to highlight the main structure of the data asset graph, which not only provides a panoramic view of data assets, but also allows users to flexibly explore the relationships between data assets, providing great convenience for users' data analysis.

Figure 23 is a schematic structural diagram of a data asset display device provided by an embodiment of the present application. The data asset display device can be implemented as the aforementioned data asset display method through software, hardware, or a combination of the two. As shown in Figure 23, the data asset display device includes an asset information acquisition module 2301, an asset collection determination module 2302, and a data asset diagram display module 2303.

The asset information acquisition module 2301 is used to obtain asset information of multiple data assets. The asset information includes the association between data assets and the asset type of the data assets;

The asset set determination module 2302 is configured to determine at least one data asset set from the multiple data assets based on the asset information of the multiple data assets. The data asset set includes multiple groups of data assets, and the asset type of each group of data assets is The composition and association relationships are the same, and each group of data assets has the same association relationship with the corresponding data assets;

The data asset graph display module 2303 is used to display the target data asset graph of the multiple data assets based on the data asset set, the data assets other than the data asset set among the multiple data assets, and the correlation between the data assets. , the target data asset graph includes asset collection nodes and asset nodes. The asset collection node corresponds to the data asset collection, and the asset node corresponds to the data asset.

In some embodiments, the device further includes:

A skeleton node extraction module, configured to extract skeleton nodes from the nodes of the target data asset graph in response to a skeleton extraction operation on the target data asset graph;

The data asset graph display module 2303 is also used to display the first data asset graph of the multiple data assets based on the extracted skeleton nodes.

In some embodiments, the skeleton node extraction module is used for:

In some embodiments, the skeleton node extraction module is used for any of the following:

In some embodiments, the device further includes an update module, the update module is configured to:

In some embodiments, the update module is used for any of the following:

In response to the selection operation of the second skeleton node update option, a calibration function for the skeleton node in the first data asset graph is provided, and in response to the calibration operation of the skeleton node in the first data asset graph, the first data asset is updated Skeleton nodes in the graph.

In some embodiments, the device further includes an exploration module configured to:

In some embodiments, the exploration module is used for any of the following:

In some embodiments, the data asset graph display module 2303 is used for:

In some embodiments, the data asset graph display module 2303 is also used to:

The asset set determination module 2302 is used for:

In some embodiments, the asset set determination module 2302 is used for any of the following:

In some embodiments, in the collection of data assets,

It should be noted that when displaying data assets in the data asset display device provided in the above embodiment, only the division of the above functional modules is used as an example. In actual applications, the above function allocation can be completed by different functional modules as needed. , that is, dividing the internal structure of the device into different functional modules to complete all or part of the functions described above. In addition, the data asset display device provided by the above embodiments and the data asset display method embodiments belong to the same concept. The specific implementation process can be found in the method embodiments and will not be described again here.

In this application, the terms "first", "second" and other words are used to distinguish the same or similar items with basically the same functions and functions. It should be understood that the terms "first", "second" and "nth" There is no logical or sequential dependency, and there is no limit on the number or execution order. It should also be understood that, although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of various examples, a first data asset graph may be referred to as a second data asset graph, and similarly, the second data asset graph may be referred to as a first data asset graph. Both the first data asset graph and the second data asset graph may be data asset graphs, and in some cases, may be separate and different data asset graphs.

The term "at least one" in this application means one or more, and the term "multiple" in this application means two or more. For example, multiple data asset graphs means two or two The above data asset diagram.

The above description is only a specific implementation mode of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of various equivalent modifications within the technical scope disclosed in the present application. Or replacement, these modifications or replacements should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of program structure information. The program structure information includes one or more program instructions. When the program instructions are loaded and executed on a computing device, all or part of the process or function in the embodiment.

Those of ordinary skill in the art can understand that all or part of the steps to implement the above embodiments can be completed by hardware, or can be completed by instructing the relevant hardware through a program. The program can be stored in a computer-readable storage medium. As mentioned above, The storage medium can be read-only memory, magnetic disk or optical disk, etc.

As shown above, the above embodiments are only used to illustrate the technical solution of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still make the foregoing The technical solutions described in each embodiment may be modified, or some of the technical features may be equivalently replaced; however, these modifications or substitutions do not cause the essence of the corresponding technical solutions to depart from the scope of the technical solutions in each embodiment of the present application.

Claims

A data asset display method, characterized in that the method includes:

Obtain asset information of multiple data assets, where the asset information includes associations between data assets and asset types of data assets;

Based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets. The data asset set includes multiple groups of data assets, and the asset type composition and association relationship of each group of data assets are the same. , and each group of data assets has the same association relationship with the corresponding data assets;

Based on the data asset set, the data assets other than the data asset set among the multiple data assets, and the correlation between the data assets, a target data asset graph of the multiple data assets is displayed, and the target data The asset graph includes asset collection nodes and asset nodes. The asset collection nodes correspond to the data asset collection, and the asset nodes correspond to data assets.
The method of claim 1, further comprising:

In response to a skeleton extraction operation on the target data asset graph, extract skeleton nodes from the nodes of the target data asset graph;

Based on the extracted skeleton nodes, a first data asset graph of the multiple data assets is displayed.
The method according to claim 2, characterized in that, in response to the skeleton extraction operation on the target data asset graph, extracting skeleton nodes from the nodes of the target data asset graph includes:

Obtain the centrality value of the node in the target data asset graph, where the centrality value indicates the importance of the data asset corresponding to the node among the multiple data assets;

Based on the centrality value and residual degree of the node in the target data asset graph, the core value of the node in the target data asset graph is obtained. The residual degree indicates the number of deleted adjacent nodes of the node. The core value Indicates the number of nodes the node is connected to;

Based on the core values of nodes in the target data asset graph, skeleton nodes are extracted from the nodes in the target data asset graph.
The method according to claim 3, characterized in that said obtaining the centrality value of a node in the target data asset graph includes:

Obtain the centrality value of the asset node in the target data asset graph based on at least one first weight, where the first weight indicates the importance of the data asset corresponding to the asset node among the multiple data assets. ;

Based on at least one second weight, obtain the centrality value of the asset collection node in the target data asset graph, the second weight indicating that the data asset collection corresponding to the asset collection node is among the multiple data assets importance.
The method according to claim 2, characterized in that, in response to the skeleton extraction operation on the target data asset graph, extracting skeleton nodes from the nodes of the target data asset graph includes:

In response to the skeleton extraction operation, a plurality of skeleton extraction options are displayed, the skeleton extraction options indicating the skeleton node's Extraction method;

In response to the selection operation of the skeleton extraction option, skeleton nodes are extracted from the nodes of the target data asset graph based on the skeleton node extraction method corresponding to the skeleton extraction option.
The method according to claim 5, characterized in that, in response to the selection operation of the skeleton extraction option, based on the skeleton node extraction method corresponding to the skeleton extraction option, from the nodes of the target data asset graph Extract skeleton nodes from , including any of the following:

In response to the selection operation of the first skeleton extraction option, extract skeleton nodes from the nodes of the target data asset graph based on default skeleton extraction parameters;

In response to the selection operation of the second skeleton extraction option, display a configuration control for the skeleton extraction parameters, and in response to the operation of the configuration control, extract skeleton nodes from the nodes of the target data asset graph;

In response to the selection operation of the third skeleton extraction option, a selection function for the nodes in the target data asset graph is provided, and in response to the selection operation of the nodes in the target data asset graph, from the nodes of the target data asset graph Extract skeleton nodes from .
The method according to any one of claims 2-6, characterized in that the method further includes:

In response to an update operation on the first data asset graph, display a plurality of skeleton node update options, the skeleton node update options indicating an update mode of the skeleton node;

In response to the selection operation of the skeleton node update option, based on the skeleton node update method corresponding to the skeleton node update option, the skeleton node in the first data asset graph is updated to display the updated first data Asset map.
The method according to claim 7, characterized in that, in response to the selection operation of the skeleton node update option, the first data asset is updated based on the skeleton node update mode corresponding to the skeleton node update option. The skeleton nodes in the graph include any of the following:

In response to a selection operation on the first skeleton node update option, display a configuration control for skeleton extraction parameters, and in response to an operation on the configuration control, update the skeleton node in the first data asset graph;

In response to the selection operation of the second skeleton node update option, a calibration function for the skeleton node in the first data asset graph is provided, and in response to the calibration operation of the skeleton node in the first data asset graph, the third A skeleton node in a data asset graph.
The method according to any one of claims 2-8, characterized in that the method further includes:

In response to an exploration operation on a target skeleton node in the first data asset graph, display a plurality of exploration options for the target skeleton node, the exploration options indicating an exploration mode for the target skeleton node, the target skeleton The node is any skeleton node in the first data asset graph;

In response to the selection operation of the exploration option, the exploration mode corresponding to the exploration option is determined, and based on the location of the target skeleton node in the first data asset graph, the data assets corresponding to the target skeleton node are displayed.
The method according to claim 9, characterized in that, in response to the selection operation of the exploration option, determining the exploration mode corresponding to the exploration option is based on the target skeleton node in the first data asset graph. location, Display the data assets corresponding to the target skeleton node, including any of the following:

In response to the selection operation of the first exploration option, determine all data assets corresponding to the target skeleton node, and display all data corresponding to the target skeleton node based on the location of the target skeleton node in the first data asset graph. assets;

In response to the selection operation of the second exploration option, determine the target association corresponding to the second exploration option, determine the target data asset based on the target association, and determine the target skeleton in the first data asset graph. The location of the node displays the target data asset, and the target data asset has the target association relationship with the data asset indicated by the target skeleton node.
The method according to any one of claims 1-10, characterized in that the target data asset graph displaying the multiple data assets includes:

The asset collection node is displayed in a first display style, and the asset node is displayed in a second display style, where the first display style is different from the second display style.
The method according to any one of claims 1-11, characterized in that the method further includes:

In response to an expansion operation on the first asset collection node in the target data asset graph, determine the data asset collection corresponding to the first asset collection node, and the first asset collection node is any one in the target data asset graph. Asset collection node;

Based on the location of the first asset collection node in the target data asset graph, the data assets in the data asset collection corresponding to the first asset collection node are displayed.
The method of claim 12, wherein displaying the data assets in the data asset set corresponding to the first asset set node includes:

The data assets in the data asset set corresponding to the first asset set node are displayed in a prominent display manner.
The method according to any one of claims 1-13, characterized in that the method further includes:

Based on the asset information of the multiple data assets, display an initial data asset graph of the multiple data assets, with multiple nodes in the initial data asset graph corresponding to the multiple data assets;

Determining at least one data asset set from the multiple data assets based on the asset information of the multiple data assets includes:

In response to a simplification operation on the initial data asset graph, display a plurality of simplification options, the simplification options indicating a manner in which the initial data asset graph is simplified;

In response to the selection operation of the simplification option, a simplification method corresponding to the simplification option is determined, and based on the asset information of the multiple data assets, at least one data asset set is determined from the multiple data assets.
The method according to claim 14, characterized in that, in response to the selection operation of the simplification option, the simplification method corresponding to the simplification option is determined, based on the asset information of the multiple data assets, from the Determine at least one data asset set among the above multiple data assets, including any of the following:

In response to the selection operation of the first simplified option, based on the asset information of all data assets in the plurality of data assets, Determine at least one data asset set from the plurality of data assets;

In response to the selection operation of the second simplified option, a selection function for the node in the initial data asset graph is provided, and in response to the selection operation of the node in the initial data asset graph, based on the data asset corresponding to the selected node asset information, and determine at least one data asset set from the data assets corresponding to the selected node.
The method according to any one of claims 1-15, characterized in that, in the data asset collection,

Each group of data assets includes one data asset, the asset type of each group of data assets belongs to the first asset type, and there is a first association relationship between each group of data assets and the corresponding first data asset; or,

Each group of data assets includes one data asset. The asset type of each group of data assets belongs to a second asset type. Each group of data assets has a second association relationship with the corresponding second data asset, and has a second association relationship with the corresponding third data asset. There is a third association between them; or,

Each group of data assets includes two data assets. The asset type of each group of data assets includes at least one. There is a fourth association relationship between each group of data assets and the corresponding fourth data asset. Each group of data assets has a fourth association relationship with the corresponding fifth data asset. The data assets have a fifth association relationship, and the two data assets have a sixth association relationship.
A data asset display device, characterized in that the device includes:

An asset information acquisition module is used to acquire asset information of multiple data assets, where the asset information includes associations between data assets and asset types of data assets;

An asset set determination module, configured to determine at least one data asset set from the multiple data assets based on the asset information of the multiple data assets. The data asset set includes multiple groups of data assets, and the assets of each group of data assets are The type composition and association relationship are the same, and each group of data assets has the same association relationship with the corresponding data asset;

A data asset diagram display module, configured to display the goals of the multiple data assets based on the data asset set, data assets other than the data asset set among the multiple data assets, and the correlation between the data assets. Data asset graph, the target data asset graph includes asset collection nodes and asset nodes, the asset collection nodes correspond to the data asset collection, and the asset nodes correspond to data assets.
A computing device, characterized in that the computing device includes a processor and a memory, the memory is used to store at least one piece of program code, and the at least one piece of program code is loaded by the processor and executed as claimed in claim 1 to claim 1 . The data asset display method described in any one of requirements 16.
A computer-readable storage medium, characterized in that the computer-readable storage medium is used to store at least one piece of program code, and the at least one piece of program code is used to execute any one of claims 1 to 16. Data asset display method.
A computer program product, characterized in that, when the computer program product is run on a computing device, it causes the computing device to execute the data asset display method according to any one of claims 1 to 16.