Method and device for generating statistical table of data assets

Abstract

The embodiment of the invention discloses a method and device for generating a statistical table of data assets, and the method comprises the following steps: recognizing a plurality of independent subitems in a project, determining the amount of money corresponding to each independent subitem, and classifying the plurality of independent subitems into a data asset subitem, a support subitem and a subitem which cannot be used as the data assets; generating a statistical table supporting the subitems; according to the statistical table of the support subitems, a statistical table of data assets is generated, and the statistical table of the data assets comprises the number and the name of the support subitems corresponding to the data asset subitems and the amount of money, which can be depreciated and sold to the data asset subitems every year in the subsequent year, of the support subitems. According to the embodiment of the invention, the value of the data assets can be fully reflected, so that the problems of omission and repeated calculation during cost collection of the data assets are avoided.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and specifically relates to a method and device for generating a statistical table of data assets. Background Art

[0002] With the continuous advancement and widespread application of digital technology, the digital economy has become an important engine driving global economic growth. In the era of digital economy, data has become one of the core assets of enterprises, and plays a vital role in the decision-making, operation and innovation of enterprises. Traditional financial statements cannot fully reflect the value of data assets, which means that investors, creditors and other stakeholders have insufficient understanding of the financial status of enterprises. Therefore, it has become an urgent need to include data assets in financial statements to more comprehensively reflect the asset status of enterprises.

[0003] Application Contents

[0004] The purpose of the embodiments of the present application is to provide a method and device for generating a statistical table of data assets, so as to solve the defect that the prior art cannot fully reflect the value of data assets.

[0005] In order to solve the above technical problems, this application is implemented as follows:

[0006] In a first aspect, a method for generating a statistical table of data assets is provided, comprising the following steps:

[0007] According to the project architecture and data flow, identify multiple independent sub-items in the project, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot be used as data assets;

[0008] Generate a statistical table of supporting sub-items, including the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized to the data asset sub-items it supports in subsequent years;

[0009] Based on the statistical table of the supporting sub-items, a statistical table of data assets is generated, and the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

[0010] In a second aspect, a device for generating a statistical table of data assets is provided, comprising:

[0011] An identification module is used to identify multiple independent sub-items in a project based on the project architecture and data flow, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot be used as data assets;

[0012] A first generation module is used to generate a statistical table of supporting sub-items, wherein the statistical table of supporting sub-items includes the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized to the data asset sub-items it supports in subsequent years;

[0013] The second generation module is used to generate a statistical table of data assets based on the statistical table of the supporting sub-items, wherein the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

[0014] The embodiment of the present application can fully reflect the value of data assets by identifying multiple independent sub-items in the project, generating a statistical table of supporting sub-items, and generating a statistical table of data assets based on the statistical table of supporting sub-items, thereby avoiding omissions and repeated calculations when aggregating data asset costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a method for generating a statistical table of data assets provided in an embodiment of the present application;

[0016] Figure 2 It is a project system architecture diagram provided by an embodiment of the present application;

[0017] Figure 3 It is a relationship diagram between data assets and supporting sub-items provided in the embodiment of the present application;

[0018] Figure 4 It is a structural diagram of a device for generating a statistical table of data assets provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] The Interim Provisions on Accounting Treatment of Enterprise Data Resources clarify the accounting treatment methods for data resources, requiring enterprises to determine whether the data resources are applicable to intangible assets or inventory standards based on the purpose of holding, formation method and business model, and to list "data resources" under the corresponding items in the financial statements. The implementation of this provision provides policy support for the management and use of enterprise data assets, and also promotes the process of data assets being included in the financial statements. The Interim Provisions on Accounting Treatment of Enterprise Data Resources follow the standard "intangible assets" and "inventory" treatment methods in the Enterprise Accounting Standards for data assets, and summarize the cost range that can be attributed to data assets.

[0021] The embodiment of the present application proposes a method for allocating the cost of data assets based on the average allocation method. In the same large digital project, the project scope includes multiple data assets and various sub-items that support these data assets, such as hardware equipment, network parts, security parts, information-based software, etc. Among them, a single data asset can be supported by multiple supporting sub-items; a single supporting sub-item can support multiple data assets and non-data assets. Each supporting sub-item jointly supports the construction and operation of multiple data assets, and the annual depreciation and amortization of each supporting sub-item can be evenly allocated according to the number of other sub-items (including data assets and non-data assets) it supports. If the data asset has not yet been formed, the depreciation and amortization of the qualified supporting project shall be allocated to the data asset according to the average allocation method as the formation cost of the data asset; if the data asset has been formed, a corresponding data asset update project can be established, and the depreciation and amortization of the qualified supporting project shall be allocated to the data asset update project according to the average allocation method as the formation cost of the newly formed data asset of the update project.

[0022] A data asset entry cost allocation method based on the average allocation method in this application generally includes the following steps:

[0023] ① Identify independent sub-items: Identify each independent sub-item based on the project system architecture diagram and detailed design plan; and based on the definition and confirmation conditions of data assets, identify data asset sub-items, sub-items that can be amortized as data asset sub-items, and sub-items that cannot be used as data assets, and clarify their corresponding amounts.

[0024] ② Identify the relationship between sub-items: According to the project system architecture diagram and detailed design plan, identify the relationship between each sub-item.

[0025] ③ Analyze the depreciation and amortization of supporting sub-items: List the statistical table of supporting sub-items, indicate the number, name, and amount of each supporting sub-item, pay special attention to the number and name of the supported data assets, determine the depreciation and amortization method and period of each supporting sub-item, and calculate the amount of depreciation and amortization that can be applied to data assets in subsequent years for each supporting sub-item.

[0026] ④ Analyze the depreciation and amortization of data assets: Make a statistical table of data assets, indicate the number, name, amount, depreciation and amortization method and years of the supporting sub-items of each data asset, establish update projects corresponding to each data asset, and calculate the amount of depreciation and amortization entering each data asset update project.

[0027] In conjunction with the accompanying drawings, a method for generating a statistical table of data assets provided by an embodiment of the present application is described in detail below through specific embodiments and application scenarios.

[0028] like Figure 1 FIG. 1 is a flow chart of a method for generating a statistical table of data assets provided in an embodiment of the present application, and the method includes the following steps:

[0029] Step 101, based on the project architecture and data flow, identify multiple independent sub-items in the project, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot serve as data assets.

[0030] Specifically, multiple independent sub-items in the project can be identified based on information such as the project system architecture diagram, detailed design plan, budget cost list, etc.; based on the definition and confirmation conditions of data assets, the multiple independent sub-items can be classified into data asset sub-items, supporting sub-items that can be amortized as data assets, and sub-items that cannot be used as data assets.

[0031] Step 102, generate a statistical table of supporting sub-items, which includes the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized to the data asset sub-items it supports in subsequent years.

[0032] In this embodiment, before generating the statistical table of the supporting sub-items, the data flow can be sorted out according to the project system architecture diagram, detailed design plan, business logic diagram and data flow diagram to identify the association relationship between the independent sub-items.

[0033] Step 103, generating a statistical table of data assets based on the statistical table of the supporting sub-items, wherein the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

[0034] In this embodiment, before generating a statistical table of data assets based on the statistical table of the supporting sub-items, the amount of depreciable and amortized annually for each data asset sub-item in the subsequent years can also be calculated based on the amount of depreciable and amortized annually for each supporting sub-item in the statistical table of the supporting sub-items to the data asset sub-items it supports.

[0035] After calculating the amount of depreciable and amortized annually for each data asset sub-item in the subsequent years based on the amount of each supporting sub-item in the statistical table of the supporting sub-items that can be depreciated and amortized annually for the data asset sub-items it supports, if the data asset sub-item has not yet been formed, the amount of depreciable and amortized annually for the data asset sub-item in the subsequent years can be used as the formation cost of the data asset sub-item; if the data asset sub-item has already been formed, a data asset update project is established in the statistical table of the data assets, and the amount of depreciable and amortized annually for the data asset sub-item in the subsequent years can be used as the formation cost of the newly formed data assets of the data asset update project.

[0036] The embodiment of the present application can fully reflect the value of data assets by identifying multiple independent sub-items in the project, generating a statistical table of supporting sub-items, and generating a statistical table of data assets based on the statistical table of supporting sub-items, thereby avoiding omissions and repeated calculations when aggregating data asset costs.

[0037] In the embodiment of the present application, the system architecture corresponding to the project is as follows: Figure 2 As shown. According to the relevant provisions of the Enterprise Accounting Standards, an asset refers to a resource formed by an enterprise's past transactions or events, owned or controlled by the enterprise, and expected to bring economic benefits to the enterprise. To recognize a resource as an asset, it must meet the definition of an asset and must also meet the following two conditions: (1) the economic benefits associated with the resource are likely to flow into the enterprise; (2) the cost or value of the resource can be reliably measured. We believe that in this project, data resources must also meet the above conditions to be recognized as an asset. The essence of data assets is data resources with four attributes: (1) the essence is data resources; (2) the ownership is clear; (3) it has value, that is, it can bring direct or indirect economic benefits to the enterprise; (4) the cost of data assets can be accurately and independently measured.

[0038] Based on the project system architecture diagram, detailed design plan, budget cost list and other information, the independent sub-items in the project can be identified; and according to the definition and confirmation conditions of data assets, they can be classified into data asset sub-items, supporting sub-items that can be amortized as data assets, and sub-items that cannot be used as data assets, and their corresponding amounts are clarified, and then an independent sub-item statistical table is generated, as shown in Table 1. Among them, for the i-th sub-item, if it is a data asset, the corresponding amount is set to Ai; if it is a supporting sub-item, the corresponding amount is set to Bi; if it is a sub-item that cannot be used as a data asset, the corresponding amount is set to Ci.

[0039] Table 1: Statistics of independent sub-items

[0040]

[0041]

[0042]

[0043] Furthermore, according to the project system architecture diagram, detailed design plan, business logic diagram, data flow diagram, etc., sort out the data flow and identify the relationship between each sub-item, such as Figure 3 As shown in Table 2, Ai represents the name of the data asset and Bi represents the name of the supporting sub-item; the situation of each supporting sub-item is highlighted, as shown in Table 2. Among them, the i-th sub-item, if it is a supporting sub-item, the corresponding amount is set to Bi, and the number of sub-items it supports is Mi.

[0044] Table 2: Statistics of associations between sub-items

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051] Furthermore, the depreciation and amortization of the supporting sub-items can be analyzed, and a statistical table of the supporting sub-items can be listed, indicating the number and name of each supporting sub-item, as shown in Table 3. Among them, for the i-th supporting sub-item, the corresponding amount is set to Bi, the number of its supported sub-items is Mi, and the number of data assets is Ni. For the i-th supporting sub-item, determine the depreciation and amortization method and period of each supporting sub-item. If it is set to use the straight-line method for depreciation and amortization over 5 years, then for the i-th supporting sub-item, the amount of depreciation and amortization to data assets in subsequent years is:

[0052] Bi′=Bi / 5 / Mi*Ni

[0053] Table 3: Statistics of supporting sub-items

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] Furthermore, the depreciation and amortization of data assets are analyzed, and a statistical table of data assets is listed, such as Figure 4 As shown, indicate the corresponding supporting sub-item quantity, name, and amount of each data asset, set up the corresponding update project for each data asset, and calculate the amount that can be depreciated and amortized into each data asset update project in the next year, recorded as A i '. Among them, the i-th sub-item, if it is a data asset, the corresponding amount is set to Ai, and the set of serial numbers of the supporting sub-items supporting the i-th data asset is recorded as H i ; For the jth sub-item, if it is a supporting sub-item, the corresponding amount is set to Bj, and the total number of sub-items it supports is Mj; this setting adopts the straight-line method for depreciation and amortization over 5 years; then

[0060] Table 4: Statistics of data assets

[0061]

[0062]

[0063]

[0064]

[0065] In summary, for the data asset sub-item, after it is converted into "intangible assets-data resources", it will be amortized normally in accordance with the original accounting policy of the enterprise. At the same time, a new data asset update project is established to allocate the depreciation and amortization of qualified supporting projects to the data asset update project according to the average allocation method as the formation cost of the data assets formed by the update project.

[0066] As for the supporting sub-items, since they do not meet the conditions for being directly included as data assets, but they contribute to the data asset formation process, they are identified as supporting sub-items. This category of projects includes both software systems and hardware equipment. After they are converted into "intangible assets" or "fixed assets", they will be depreciated or amortized normally in accordance with the original accounting policies of the enterprise and in combination with actual conditions. However, the depreciation or amortization part can be used as the formation cost of the data asset according to the average allocation method. If the data asset has been formed, a corresponding data asset update project can be established. The depreciation and amortization amount of the qualified supporting project can be allocated to the data asset update project according to the average allocation method as the formation cost of the newly formed data asset of the update project.

[0067] The embodiment of the present application provides a method for allocating the cost of data assets based on the average allocation method. According to the project architecture and data flow, data asset sub-items and their corresponding supporting sub-items are identified. According to the total number of other projects supported by the supporting sub-items and the number of data asset sub-items therein, the amount of depreciation or amortization of the supporting sub-items is evenly allocated to the data assets in proportion as the formation cost of the data assets. Through the above measures, the problem of how to calculate the cost of multiple data assets with the same underlying supporting sub-items in an overall project is solved, and the problems of omissions and repeated calculations when aggregating data asset costs are avoided. At the same time, the depreciation or amortization amount of the supporting sub-items is reclassified into the formation cost of the data assets, so as to achieve the effect of asset value preservation by using data assets.

[0068] like Figure 4 FIG. 1 is a schematic diagram of a structure of a device for generating a statistical table of data assets provided in an embodiment of the present application, including:

[0069] The identification module 410 is used to identify multiple independent sub-items in the project according to the project architecture and data flow, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot serve as data assets.

[0070] Specifically, the identification module 410 is specifically used to identify multiple independent sub-items in the project based on information such as the project system architecture diagram, detailed design plan, budget cost list, etc.; according to the definition and confirmation conditions of data assets, the multiple independent sub-items are classified into data asset sub-items, supporting sub-items that can be amortized as data assets, and sub-items that cannot be used as data assets.

[0071] In this embodiment, the identification module 410 is also used to sort out the data flow and identify the association relationship between independent sub-items according to the project system architecture diagram, detailed design plan, business logic diagram and data flow diagram.

[0072] The first generation module 420 is used to generate a statistical table of supporting sub-items, which includes the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized annually for the data asset sub-items it supports in subsequent years.

[0073] The second generation module 430 is used to generate a statistical table of data assets based on the statistical table of the supporting sub-items, wherein the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

[0074] In this embodiment, the second generation module is also used to, if the data asset sub-item has not yet been formed, use the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years as the formation cost of the data asset sub-item;

[0075] If a data asset sub-item has been formed, a data asset update project will be established in the statistical table of the data asset, and the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years will be used as the formation cost of the newly formed data asset of the data asset update project.

[0076] Furthermore, the above device further comprises:

[0077] A calculation module is used to calculate the amount of depreciation and amortization that a supporting sub-item can provide to each data asset sub-item in subsequent years based on the amount of depreciation and amortization that each supporting sub-item can provide to the data asset sub-item it supports in subsequent years in the statistical table of the supporting sub-items.

[0078] The embodiment of the present application can fully reflect the value of data assets by identifying multiple independent sub-items in the project, generating a statistical table of supporting sub-items, and generating a statistical table of data assets based on the statistical table of supporting sub-items, thereby avoiding omissions and repeated calculations when aggregating data asset costs.

[0079] The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the method embodiment for generating a statistical table of data assets is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0080] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0081] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0082] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for generating a statistical table of data assets, characterized in that: The following steps are involved: According to the project architecture and data flow, identify multiple independent sub-items in the project, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot be used as data assets; Generate a statistical table of supporting sub-items, including the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized to the data asset sub-items it supports in subsequent years; Based on the statistical table of the supporting sub-items, a statistical table of data assets is generated, and the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

2. The method according to claim 1, characterized in that According to the project architecture and data flow, multiple independent sub-items in the project are identified, including: Identify multiple independent sub-items in the project based on the project system architecture diagram, detailed design plan, budget cost list and other information; The classification of the plurality of independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot be used as data assets specifically includes: According to the definition and confirmation conditions of data assets, the multiple independent sub-items are classified into data asset sub-items, supporting sub-items that can be amortized as data assets, and sub-items that cannot be used as data assets.

3. The method according to claim 1, characterized in that Before generating the statistical table of the supporting sub-items, the method further includes: According to the project system architecture diagram, detailed design plan, business logic diagram and data flow diagram, sort out the data flow and identify the relationship between each independent sub-item.

4. The method according to claim 1, characterized in that: Before generating the statistical table of data assets according to the statistical table of the supporting sub-items, the method further includes: According to the amount of depreciation and amortization that each supporting sub-item can provide to the data asset sub-item it supports in subsequent years in the statistical table of the supporting sub-items, calculate the amount of depreciation and amortization that can be provided to each data asset sub-item in subsequent years.

5. The method according to claim 1, characterized in that The amount of depreciable and amortized data asset sub-items supported by each supporting sub-item in the statistical table of the supporting sub-items in subsequent years is calculated, and after that, the amount of depreciable and amortized data asset sub-items supported by the supporting sub-items in subsequent years is calculated, and the amount of depreciable and amortized data asset sub-items supported by the supporting sub-items in subsequent years is calculated, and the method further includes: If the data asset sub-item has not yet been formed, the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years shall be regarded as the formation cost of the data asset sub-item; If a data asset sub-item has been formed, a data asset update project will be established in the statistical table of the data asset, and the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years will be used as the formation cost of the newly formed data asset of the data asset update project.

6. A device for generating a statistical table of data assets, characterized in that: include: An identification module is used to identify multiple independent sub-items in a project based on the project architecture and data flow, clarify the amount corresponding to each independent sub-item, and classify the multiple independent sub-items into data asset sub-items, supporting sub-items, and sub-items that cannot be used as data assets; A first generation module is used to generate a statistical table of supporting sub-items, wherein the statistical table of supporting sub-items includes the amount corresponding to each supporting sub-item, the total number of sub-items supported by each supporting sub-item, the depreciation and amortization period of each supporting sub-item, the number of data asset sub-items supported by each supporting sub-item, and the amount of each supporting sub-item that can be depreciated and amortized to the data asset sub-items it supports in subsequent years; The second generation module is used to generate a statistical table of data assets based on the statistical table of the supporting sub-items, wherein the statistical table of data assets includes the number and name of the supporting sub-items corresponding to each data asset sub-item, and the amount of the supporting sub-items that can be depreciated and amortized to each data asset sub-item in subsequent years.

7. The device according to claim 6, characterized in that The identification module is specifically used to identify multiple independent sub-items in the project based on information such as the project system architecture diagram, detailed design plan, budget cost list, etc.; according to the definition and confirmation conditions of data assets, the multiple independent sub-items are classified into data asset sub-items, supporting sub-items that can be amortized as data assets, and sub-items that cannot be used as data assets.

8. The device according to claim 6, characterized in that The identification module is also used to sort out the data flow and identify the relationship between independent sub-items based on the project system architecture diagram, detailed design plan, business logic diagram and data flow diagram.

9. The device according to claim 6, characterized in that Also includes: A calculation module is used to calculate the amount of depreciation and amortization that a supporting sub-item can provide to each data asset sub-item in subsequent years based on the amount of depreciation and amortization that each supporting sub-item can provide to the data asset sub-item it supports in subsequent years in the statistical table of the supporting sub-items.

10. The device according to claim 6, characterized in that The second generation module is further configured to, if the data asset sub-item has not yet been formed, use the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years as the formation cost of the data asset sub-item; If a data asset sub-item has been formed, a data asset update project will be established in the statistical table of the data asset, and the amount of the supporting sub-item that can be depreciated and amortized to the data asset sub-item in subsequent years will be used as the formation cost of the newly formed data asset of the data asset update project.

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