A four-dimensional data value assessment method and system

Abstract

The present invention discloses a four-dimensional data value assessment method and system, which relates to the field of data processing, and includes steps 1: obtaining data assets to be assessed and information elements related to the data assets; step 2: determining the four-dimensional data asset value characteristic dimensions according to the data assets to be assessed and information elements related to the data assets; step 3: matching corresponding value assessment indicators according to the four-dimensional data asset value characteristic dimensions; step 4: configuring weights for the value assessment indicators according to the four-dimensional data asset value characteristic dimensions and the value assessment indicators; step 5: calculating data asset value assessment scores and outputting the calculated scores; step 6: identifying and classifying data assets according to the data asset value assessment scores; and step 7: obtaining the data asset value assessment report, thereby achieving the technical effect of improving data management efficiency and enabling enterprises to clearly grasp their own asset conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a four-dimensional data value assessment method and system. Background Art

[0002] Data elements are the core engine for the deepening development of the digital economy. It is necessary to carry out data rights confirmation, pricing and trading activities in an orderly manner. Data value assessment is an important foundation for realizing data circulation and application. From the current academic research and practical cases in various industries, the existing data value assessment technical solutions are used as examples for explanation: Technical Solution 1: Consider the intrinsic value of data based on the data itself, the cost value of data by the data seller, the use value of data by the data buyer, and the market value of data by the data market, and then calculate the comprehensive value of the data; Technical Solution 2: By building a unified data asset value assessment framework, combining the basic information of the data assets to be assessed to obtain the scope of the data assets to be assessed, and constructing assessment indicators, among which the assessment indicators mainly include quality dimension, cost dimension, and application dimension, and then determine the calculation method, comprehensively calculate to obtain the assessment results, and summarize the results to output the final data asset value assessment results; Technical Solution 3: Propose a data asset value assessment model, the assessment elements of the model include asset cost elements, inherent value elements, market value elements and environmental elements, and use the hierarchical analysis method to calculate the value of each part and finally determine the total score of the data asset value.

[0003] It can be seen that the research on data value assessment still has the following problems: First: the objective and scientific data asset value assessment system and data transaction research are still in the early stages, and there are no mature solutions and data asset value assessment operating systems similar to calculators; Second: because the same asset may play different values ​​in different development cycles or scenarios, and the existing data value assessment methods do not analyze the value of data assets according to the development characteristics of the entire life cycle of data, the evaluation results may be inaccurate; Third: the existing methods do not properly classify and organize the data value assessment results, resulting in chaotic and inefficient management of data assets. It is impossible to formulate effective management strategies for data assets of different values, resulting in problems in the maintenance, update, and utilization of data assets.

[0004] Therefore, how to provide a reasonable, sound and effective four-dimensional data asset value assessment method is an urgent problem to be solved. Summary of the invention

[0005] The embodiments of the present application provide a four-dimensional data value assessment method and system to solve the technical problems in the prior art that the data value assessment results are not properly classified and organized, resulting in chaotic and inefficient management of data assets, and effective management strategies cannot be formulated for data assets of different values ​​according to the development characteristics of the entire data life cycle, resulting in imperfect maintenance, updating, and utilization of data assets. The present application achieves the technical effect of being able to clearly display the value of data for internal business empowerment and external transaction circulation, and being able to clearly display the value growth of data based on a certain period of time, forming a more standardized data value assessment model, improving data management efficiency, and enabling enterprises to clearly understand their own asset status.

[0006] In a first aspect, an embodiment of the present invention provides a four-dimensional data value assessment method, comprising: step 1: obtaining data assets to be assessed and data asset-related information elements; step 2: determining the four-dimensional data asset value characteristic dimensions based on the data assets to be assessed and data asset-related information elements; step 3: matching corresponding value assessment indicators based on the four-dimensional data asset value characteristic dimensions; step 4: configuring weights for the value assessment indicators based on the four-dimensional data asset value characteristic dimensions and the value assessment indicators; step 5: calculating the data asset value assessment score and outputting the calculated score based on the four-dimensional data asset value characteristic dimensions, the value assessment indicators and the weights configured in step 4; step 6: identifying and classifying data assets based on the data asset value assessment scores; step 7: obtaining the data asset value assessment report.

[0007] Preferably, in step 1, the data assets to be evaluated include original data assets and value-added data assets, wherein the original data assets are detailed data obtained through external acquisition or internal collection, and the value-added data assets are based on the original data assets, and are summary data, personalized statistical data or data products obtained through data processing, handling, analysis, aggregation and mining.

[0008] Preferably, in step 2, the four-dimensional data asset value characteristic dimensions include internal value characteristics of original data assets, internal value characteristics of value-added data assets, market value characteristics of original data assets, and market value characteristics of value-added data assets.

[0009] Preferably, in step 3, the matching of corresponding value assessment indicators according to the four-dimensional data asset value feature dimension includes: matching the internal value assessment indicators of the original data assets with the internal value assessment indicators of the original data assets, matching the market value assessment indicators of the original data assets with the market value assessment indicators of the original data assets, matching the internal value assessment indicators of the value-added data assets with the internal value assessment indicators of the value-added data assets, and matching the market value assessment indicators of the value-added data assets with the market value assessment indicators of the value-added data assets; wherein the internal value assessment indicators of the original data assets include: data scale, data quality, planning cost, acquisition cost, storage cost, management cost, and the data quality includes accuracy, consistency, completeness, standardization, timeliness, and accessibility; the market value assessment indicators of the original data assets include: data application, data market, data security, and data risk; the internal value assessment indicators of the value-added data assets include: data scale, data quality, planning cost, storage cost, processing cost, and management cost; the market value assessment indicators of the value-added data assets include: data application, data market, data security, data risk, return on investment, decision value, commercial value, strategic value, and industrial value.

[0010] Preferably, in step 4, the weight configuration method is a hierarchical analysis method or a neural network.

[0011] Preferably, in step 5, calculating the data asset value assessment score includes:

[0012] Step 51: The value evaluation index, obtains the corresponding value of the value evaluation index, and performs standardization on the corresponding value of the value evaluation index, and uniformly converts it into an evaluation value between 0 and 1, wherein:

[0013] The standardization processing formula is:

[0014] Step 52: Calculate the internal value of the data asset based on the evaluation value of step 51. The formula is:

[0015] P 内部价值 =(TC+I+S) / 3;

[0016]

[0017] Among them, the TC is planning cost + acquisition cost + processing cost + storage cost + management cost, and the P 内部价值 is the evaluation value, TC is the total cost of data assets, I is the total score of data quality, S is the data scale, i is the evaluation value of indicators related to data quality, and W i is the weight of the indicator;

[0018] Step 53: Calculate the market value of the data asset based on the evaluation value of step 51. The formula is:

[0019] P 外部价值 =(DA 数据应用 +DM 数据市场 +DS 数据安全 +DR 数据风险 +RI 投资回报 +DV 决策价值 +CV 商业价值 +SV 战略价值 +IV 产业价值 ) / 9;

[0020] Among them, the DA 数据应用 , the DM 数据市场 , the DS 数据安全 , the DR 数据风险 , the RI 投资回报 、The DV 决策价值 、The CV 商业价值 , the SV 战略价值 、The IV 产业价值 The scores of each indicator respectively.

[0021] Preferably, in step 6, the identification and classification of data assets includes: dividing the data asset value assessment scores into core data assets, standard data assets, inefficient data assets, and invalid data assets, wherein data asset value assessment scores between 0.9 and 1.0 and including 0.9 are marked as core data assets; data asset value assessment scores between 0.75 and 0.9 and including 0.75 are marked as standard data assets, data asset value assessment scores between 0.6 and 0.75 and including 0.6 are marked as inefficient data assets, and data asset value assessment scores below 0.6 are marked as invalid data assets.

[0022] In a second aspect, an embodiment of the present invention further provides a four-dimensional data value assessment system, the system comprising: a data acquisition unit, the data acquisition unit being used to obtain data assets to be assessed and data asset related information elements; a four-dimensional data asset value characteristic dimension determination unit, the four-dimensional data asset value characteristic dimension determination unit being used to determine the four-dimensional data asset value characteristic dimension based on the data assets to be assessed and data asset related information elements; a data value assessment indicator configuration unit, the data value assessment indicator configuration unit being used to match corresponding value assessment indicators based on the data assets to be assessed and data asset related information elements and the four-dimensional data asset value characteristic dimension; an indicator weight setting unit Element, the indicator weight setting unit is used to configure the weight of the value assessment indicator according to the four-dimensional data asset value characteristic dimension and the value assessment indicator; the data asset value assessment calculation unit, the data asset value assessment calculation unit is used to calculate the data asset value assessment score and output the calculated score according to the four-dimensional data asset value characteristic dimension, the value assessment indicator and the configured weight; the data asset classification and summary unit, the data asset classification and summary unit is used to identify and classify data assets according to the data asset value assessment score; the data asset value assessment report acquisition unit, the data asset value assessment report acquisition unit is used to obtain the data asset value assessment report.

[0023] In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and wherein when the computer program is executed by the processor, the processor executes the steps of the four-dimensional data value assessment method as described in any one of the preceding items.

[0024] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a program stored thereon, characterized in that when the program is executed by a processor, it is used to implement the steps of the four-dimensional data value assessment method as described in any of the above items.

[0025] The above one or more technical solutions in the embodiments of the present invention have at least one or more of the following technical effects:

[0026] A four-dimensional data value assessment method and system provided in an embodiment of the present invention includes step 1: obtaining data assets to be assessed and data asset related information elements; step 2: determining the four-dimensional data asset value characteristic dimension according to the data assets to be assessed and the data asset related information elements; step 3: matching the corresponding value assessment index according to the four-dimensional data asset value characteristic dimension; step 4: configuring weights for the value assessment index according to the four-dimensional data asset value characteristic dimension and the value assessment index; step 5: calculating the data asset value assessment score according to the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 6: matching the corresponding value assessment index according to the four-dimensional data asset value characteristic dimension and the value assessment index; step 7: configuring weights for the value assessment index according to the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 8: configuring weights for the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 9: configuring weights for the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 10 Data asset value assessment score, identification and classification of data assets; Step 7: Obtain the data asset value assessment report, thereby solving the problem that the prior art does not conduct appropriate data classification and organization of data value assessment results, resulting in chaotic and inefficient data asset management, and is unable to formulate effective management strategies for data assets of different values, resulting in imperfect technical problems in data asset maintenance, updating, and utilization. It achieves the technical effect of being able to clearly display the value of data to internal business empowerment and external transaction circulation, and being able to clearly display the value growth of data based on a certain period of time, forming a more standardized data value assessment model, improving data management efficiency, and enabling enterprises to clearly understand their own asset status.

[0027] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of a flow chart of a four-dimensional data value assessment method according to an embodiment of the present invention;

[0029] Figure 2 It is a schematic diagram of the value feature dimensions of four-dimensional data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The embodiments of the present application provide a four-dimensional data value assessment method and system to solve the technical problems in the prior art that the data value assessment results are not properly classified and organized, resulting in chaotic and inefficient management of data assets, and it is impossible to formulate effective management strategies for data assets of different values, resulting in imperfect maintenance, updating, and utilization of data assets.

[0031] The technical solution in the embodiment of the present invention has the following general idea:

[0032] The embodiment of the present invention provides a four-dimensional data value assessment method and system, through step 1: obtaining data assets to be assessed and data asset related information elements; step 2: determining the four-dimensional data asset value characteristic dimension according to the data assets to be assessed and the data asset related information elements; step 3: matching the corresponding value assessment indicator according to the four-dimensional data asset value characteristic dimension; step 4: configuring weights for the value assessment indicator according to the four-dimensional data asset value characteristic dimension and the value assessment indicator; step 5: calculating the data asset value assessment score and outputting the calculated score according to the four-dimensional data asset value characteristic dimension, the value assessment indicator and the weight configured in step 4; step 6: identifying and classifying data assets according to the data asset value assessment score; step 7: obtaining the data asset value assessment report, thereby achieving the technical effect of being able to clearly display the value of data for internal business empowerment and external transaction circulation value, being able to clearly display the value growth of data based on a certain period of time, forming a more standardized data value assessment model, improving data management efficiency, and enabling enterprises to clearly grasp their own asset status.

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Embodiment 1

[0035] This embodiment provides a four-dimensional data value assessment method, please refer to Figure 1 , the method comprising:

[0036] Step 1: Obtain the data assets to be evaluated and relevant information elements of the data assets.

[0037] Furthermore, in step 1, the data assets to be evaluated include original data assets and value-added data assets, wherein the original data assets are detailed data obtained through external acquisition or internal collection, and the value-added data assets are based on the original data assets and are summary data, personalized statistical data or data products obtained through data processing, handling, analysis, aggregation and mining.

[0038] Specifically, the present invention considers the characteristics of data assets, value types and the development of the entire life cycle of data from multiple angles. Based on the development of the entire life cycle of data, data assets can be divided into original data assets and value-added data assets. Based on the internal empowerment of data and the characteristics of external transaction circulation, the internal value and market value of data assets can be calculated. Based on this, a four-dimensional data asset value evaluation method and system based on calculating the internal value of original data assets, the internal value of value-added data assets, the market value of original data assets, and the market value of value-added data assets are formed. In the data value evaluation method, it is first necessary to obtain the data assets to be evaluated and the relevant information elements of the data assets. Among them, the data assets to be evaluated include original data assets and value-added data assets. The original data assets are detailed data obtained by external acquisition or internal collection, which can provide original information for subsequent data processing applications. The original data assets can also include internal business data of the enterprise, as well as externally acquired data. The value-added data assets are based on the original data assets. The summary data, personalized statistical data or data products obtained by adopting the processing methods of data processing, processing, analysis, aggregation and mining can be directly applied to the business department to support the development of business-related work and the improvement of revenue.

[0039] Step 2: Determine the four-dimensional data asset value characteristic dimensions based on the data assets to be evaluated and the relevant information elements of the data assets.

[0040] Furthermore, in step 2, the four-dimensional data asset value characteristic dimensions include internal value characteristics of original data assets, internal value characteristics of value-added data assets, market value characteristics of original data assets, and market value characteristics of value-added data assets.

[0041] Specifically, if Figure 2 As shown, the four-dimensional data asset value feature dimension is selected. The main purpose of selecting the dimension is for users to choose to calculate the data value according to the data characteristics and their own needs. Furthermore, the four-dimensional data asset value feature dimension includes the internal value characteristics of original data assets, the internal value characteristics of value-added data assets, the market value characteristics of original data assets, and the market value characteristics of value-added data assets.

[0042] Step 3: Match the corresponding value assessment indicators according to the four-dimensional data asset value characteristic dimensions.

[0043] Furthermore, in step 3, the matching of corresponding value assessment indicators according to the four-dimensional data asset value feature dimension includes: matching the original data asset internal value assessment indicator with the original data asset internal value assessment indicator, matching the original data asset market value assessment indicator with the original data asset market value assessment indicator, matching the value-added data asset internal value assessment indicator with the value-added data asset internal value assessment indicator, and matching the value-added data asset market value assessment indicator with the value-added data asset market value assessment indicator; wherein, the original data asset internal value assessment indicators include: data scale, data Quality, planning cost, acquisition cost, storage cost, and management cost. In addition, the data quality includes accuracy, consistency, completeness, standardization, timeliness, and accessibility. The market value assessment indicators of the original data assets include data application, data market, data security, and data risk. The internal value assessment indicators of the value-added data assets include data scale, data quality, planning cost, storage cost, processing cost, and management cost. The market value assessment indicators of the value-added data assets include data application, data market, data security, data risk, return on investment, decision-making value, commercial value, strategic value, and industrial value.

[0044] Specifically, after the four-dimensional data asset value characteristic dimensions are determined in step 2, it is necessary to configure the corresponding value assessment indicators according to the four-dimensional data asset value characteristic dimensions determined in step 2. The specific configuration method is: for the internal value assessment of original data assets, the internal value assessment indicators of original data assets are configured; for the market value assessment of original data assets, the market value assessment indicators of original data assets are configured; for the internal value assessment of value-added data assets, the internal value assessment indicators of value-added data assets are configured; for the market value assessment of value-added data assets, the market value assessment indicators of value-added data assets are configured. Among them, the design principles of evaluation indicators include scientific principles, systematic principles, universal principles, operability principles, coordination principles, and guiding principles. The indicator design is applicable to the development of the entire life cycle of data and refers to data value management factors.

[0045] Furthermore, the internal value assessment indicators of original data assets include: data scale, data quality, planning cost, acquisition cost, storage cost, and management cost; among which data quality includes: accuracy, consistency, completeness, standardization, timeliness, and accessibility; the market value assessment indicators of original data assets include data application, data market, data security, and data risk; the internal value assessment indicators of value-added data assets include: data scale, data quality, planning cost, storage cost, processing cost, and management cost; the market value assessment indicators of value-added data assets include: data application, data market, data security, data risk, return on investment, decision-making value, commercial value, strategic value, and industrial value; as shown in Table 1, the specific meanings of all the value assessment indicators listed above are given.

[0046] Table 1. Description of data value assessment indicators

[0047]

[0048]

[0049]

[0050] Step 4: According to the four-dimensional data asset value characteristic dimension and the value assessment indicator, weights are configured for the value assessment indicator.

[0051] Furthermore, in step 4, the weight configuration method is a hierarchical analysis method or a neural network.

[0052] Specifically, after the corresponding value assessment indicators are configured in step 3, it is necessary to configure weights for the indicators according to the value assessment dimensions selected in step 2 and the corresponding value assessment indicators configured in step 3; wherein, the weight setting method is as follows: The weight setting method used includes hierarchical analysis method, etc. In a specific embodiment, the weights of each value assessment indicator can also be calculated by a neural network or the like, which is not specifically limited in this embodiment. Each weight can also be adjusted based on the needs of the user to ensure the accuracy of the calculated data asset value.

[0053] Step 5: Based on the four-dimensional data asset value characteristic dimensions, the value assessment indicators and the weights configured in step 4, calculate the data asset value assessment score and output the calculated score.

[0054] Furthermore, in step 5, the calculation of the data asset value assessment score includes: step 51: the value assessment indicator, obtaining the corresponding value of the value assessment indicator, and standardizing the corresponding value of the value assessment indicator, uniformly converting it into an evaluation value between 0 and 1, wherein the standardization processing formula is: Step 52: Calculate the internal value of the data asset based on the evaluation value of step 51. The formula is: P 内部价值 =(TC+I+S) / 3; Among them, the TC is planning cost + acquisition cost + processing cost + storage cost + management cost, and the P 内部价值 is the evaluation value, TC is the total cost of data assets, I is the total score of data quality, S is the data scale, and I i is the evaluation value of the index related to data quality, the W i is the weight of the indicator; Step 53: Calculate the market value of the data asset according to the evaluation value of step 51, the formula is:

[0055] P 外部价值 =(DA 数据应用 +DM 数据市场 +DS 数据安全 +DR 数据风险 +RI 投资回报 +DV 决策价值 +CV 商业价值 +SV 战略价值 +IV 产业价值 ) / 9

[0056] ; wherein the DA 数据应用 , the DM 数据市场 , the DS 数据安全 , the DR 数据风险 , the RI 投资回报 , the DV decision value, the CV 商业价值 , the SV 战略价值 、The IV 产业价值 The scores of each indicator respectively.

[0057] Specifically, after determining the indicator weights in step 4, it is necessary to calculate the data asset value assessment score and output the calculated score based on the value assessment dimensions selected in step 2, the value assessment indicators configured in step 3, and the indicator weights determined in step 4; the specific calculation process is as follows:

[0058] Step 51: For the selected indicators, obtain the corresponding values ​​of each indicator, and first calculate the indicators with the same unit, such as counting all cost items and calculating the total quality score; and in order to eliminate the influence of different indicator dimensions, it is necessary to standardize the data and uniformly convert them into evaluation values ​​between 0 and 1.

[0059] The standardization method uses the TOPSIS method based on the superior and inferior solution distance method. The specific formula is as follows: The maximum values ​​in the embodiments are given based on industry research and expert experience.

[0060] Step 52: Based on the normalized statistical results of step 51, calculate the internal value of data assets. The specific calculation formula is as follows: 内部价值 =(TC+I+S) / 3; Among them, TC = planning cost + acquisition cost + processing cost + storage cost + management cost; among them, P 内部价值 is the evaluation value, TC is the total cost of data assets, I is the total score of data quality, S is the data scale, and I i Represents the evaluation value of indicators related to data quality, W i represents the weight of the indicator;

[0061] Step 53: Based on the normalized statistical results of step 51, the market value of data assets is calculated. The specific calculation formula is as follows:

[0062] P 外部价值 =(DA 数据应用 +DM 数据市场 +DS 数据安全 +DR 数据风险 +RI 投资回报 +DV 决策价值 +CV 商业价值 +SV 战略价值 +IV 产业价值 ) / 9

[0063] DA 数据应用 DM 数据市场 DS 数据安全 ,DR 数据风险 , RI 投资回报 、DV 决策价值 、CV 商业价值 SV 战略价值 IV 产业价值 The scores of each indicator respectively.

[0064] Step 6: Identify and classify data assets based on the data asset value assessment score.

[0065] Furthermore, in step 6, the identification and classification of data assets includes: dividing the data asset value assessment scores into core data assets, standard data assets, inefficient data assets, and invalid data assets, wherein data asset value assessment scores between 0.9 and 1.0 and including 0.9 are marked as core data assets; data asset value assessment scores between 0.75 and 0.9 and including 0.75 are marked as standard data assets, data asset value assessment scores between 0.6 and 0.75 and including 0.6 are marked as inefficient data assets, and data asset value assessment scores below 0.6 are marked as invalid data assets.

[0066] Specifically, data assets are identified and classified according to the obtained value assessment scores. The specific method is: identify and classify data assets, and divide data into core data assets, standard data assets, inefficient data assets, and invalid data assets according to the value assessment scores. Data assets with a value assessment score between 0.9 and 1.0 and including 0.9 are recorded as core data assets; scores between 0.75 and 0.9 and including 0.75 are recorded as standard data assets, scores between 0.6 and 0.75 and including 0.6 are recorded as inefficient data assets, and scores below 0.6 are recorded as invalid data assets; through different aggregation methods, it is possible to further achieve the technical effect of facilitating enterprises to grasp the specific situation of assets, understand the dynamics of data value-added, and the value of internal empowerment and external circulation of data.

[0067] Step 7: Obtain the data asset value assessment report.

[0068] Specifically, based on the evaluation results, and combined with the description of data asset information elements, determined characteristic dimensions, evaluation indicators, weights and measurement process, a valuation conclusion is finally formed and an evaluation report is formed.

[0069] Furthermore, the present invention studies data value based on the four-dimensional data value characteristics, and studies the internal value and market value of data horizontally, which can clearly demonstrate the value of data to internal business empowerment and external transaction circulation value; vertically, data is divided into original data assets and value-added data assets according to the development of the entire life cycle of data. It can clearly show the value growth of data based on a certain period of time, forming a more standardized data value assessment model. The present invention proposes to classify and summarize data assets according to the value assessment score, which improves the efficiency of data management, makes data storage clearer, and enables enterprises to clearly understand their own asset status.

[0070] Embodiment 2

[0071] This embodiment also provides another four-dimensional data value assessment method, taking the existing desensitized physical examination data of users of Shaanxi Aopu Digital Medical Co., Ltd. as an example to estimate the data value, as follows:

[0072] Specifically, the user's cardiovascular and cerebrovascular physical examination data table can provide cardiovascular and cerebrovascular physical examination related data, and the specific indicators are shown in Table 2.

[0073] Table 2. User desensitized cardiovascular and cerebrovascular physical examination data table

[0074]

[0075]

[0076] The value assessment process for the above data assets is as follows:

[0077] S1: Get the data asset table and describe the relevant information elements in detail, including the table name, user desensitized cardiovascular and cerebrovascular physical examination data table, data security level is confidential, data asset type is intangible asset, data size is 3.5MB, rights data is owned by Aupu Digital Medical Co., Ltd., which has the right to hold resources, and the specific person in charge is Zhang San, etc.

[0078] S2: Determine the four-dimensional data asset value characteristic dimension. This time, we choose to calculate the internal value of the data asset of the data table value-added category.

[0079] S3: Configure corresponding value assessment indicators based on the four-dimensional data asset value characteristic dimensions determined in S2. Specific indicators include data scale, data quality, planning cost, acquisition cost, storage cost, processing cost, and management cost;

[0080] S4: According to the value assessment dimension selected in S2 and the corresponding value assessment indicator configured in S3, weights are configured for the indicator; because the calculation is the internal value of the original data asset, only the data quality part needs to be configured with corresponding weights, and data quality includes accuracy, consistency, completeness, standardization, timeliness, and accessibility; the specific weight setting is given according to expert experience, and the sum of the six weights is equal to 1. Specifically, the accuracy weight is 0.3, the consistency weight is 0.15, the completeness weight is 0.2, the standardization weight is 0.15, the timeliness weight is 0.1, and the accessibility weight is 0.1;

[0081] S5: Calculate the data asset value assessment score based on the value assessment dimension selected in S2, the value assessment indicator configured in S3, and the indicator weight determined in S4, and output the calculated score;

[0082] The specific calculation process is as follows:

[0083] S51: Based on the normalized indicators, the internal value of the data asset is calculated. The specific calculation formula is as follows:

[0084] P 内部价值 =(TC+I+S) / 3;

[0085]

[0086] Among them, TC = planning cost + acquisition cost + processing cost + storage cost + management cost; P 内部价值 is the evaluation value, TC is the total cost of data assets, I is the total score of data quality, S is the data scale, and I i Represents the evaluation value of indicators related to data quality, W i represents the weight of the indicator;

[0087] Table 3 below shows the specific scores and standardized results of each indicator, including the scale of acquired data, quality evaluation score, and the original value of each cost and the standardized calculation results are as follows:

[0088]

[0089] Based on the above records and the internal data asset value calculation formula:

[0090] P=(0.78+0.8115+0.9962) / 3=0.8632;

[0091] After calculation, the value score of the user's cardiovascular and cerebrovascular physical examination data table is 0.8632;

[0092] S6: Identify and classify data assets based on the obtained value assessment scores.

[0093] Since the value score of the user's cardiovascular and cerebrovascular physical examination data table is 0.8632, compared with the classification parameters, the score is between 0.75 and 0.9. Therefore, this asset belongs to the standard data asset;

[0094] S7: Obtain data value assessment report;

[0095] Based on the evaluation results, and in combination with the description of data asset information elements, determined characteristic dimensions, evaluation indicators, weights and measurement process, a valuation conclusion is formed and an evaluation report is formed.

[0096] Embodiment 3

[0097] On the other hand, this embodiment further provides a four-dimensional data value assessment system. In a specific implementation, the four-dimensional data value assessment system includes:

[0098] A data acquisition unit, the data acquisition unit is used to obtain the data assets to be evaluated and the data asset related information elements;

[0099] A four-dimensional data asset value characteristic dimension determination unit, the four-dimensional data asset value characteristic dimension determination unit is used to determine the four-dimensional data asset value characteristic dimension according to the data asset to be evaluated and the data asset related information elements;

[0100] A data value assessment indicator configuration unit, the data value assessment indicator configuration unit is used to match corresponding value assessment indicators according to the data assets to be assessed and the data asset related information elements and the four-dimensional data asset value characteristic dimensions;

[0101] An indicator weight setting unit, the indicator weight setting unit is used to configure weights for the value assessment indicators according to the four-dimensional data asset value feature dimensions and the value assessment indicators;

[0102] A data asset value evaluation calculation unit, the data asset value evaluation calculation unit is used to calculate the data asset value evaluation score and output the calculated score according to the four-dimensional data asset value characteristic dimension, the value evaluation index and the configured weight;

[0103] A data asset classification and summary unit, the data asset classification and summary unit is used to identify and classify data assets according to the data asset value assessment score, and classify the data into core data assets, standard data assets, inefficient data assets, and invalid data assets according to the value assessment score;

[0104] A data asset value assessment report acquisition unit, wherein the data asset value assessment report acquisition unit is used to obtain the data asset value assessment report, and to form a valuation conclusion and an assessment report based on the assessment results and in combination with the data asset information element description, determined characteristic dimensions, evaluation indicators, weights and measurement process.

[0105] Furthermore, an embodiment of the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the four-dimensional data value assessment method.

[0106] Furthermore, an embodiment of the present invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the four-dimensional data value assessment method.

[0107] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0108] It should be noted that, in this document, relational terms such as “first” and “second” are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0109] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0110] The above one or more technical solutions in the embodiments of the present invention have at least one or more of the following technical effects:

[0111] A four-dimensional data value assessment method and system provided in an embodiment of the present invention includes step 1: obtaining data assets to be assessed and data asset related information elements; step 2: determining the four-dimensional data asset value characteristic dimension according to the data assets to be assessed and the data asset related information elements; step 3: matching the corresponding value assessment index according to the four-dimensional data asset value characteristic dimension; step 4: configuring weights for the value assessment index according to the four-dimensional data asset value characteristic dimension and the value assessment index; step 5: calculating the data asset value assessment score according to the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 6: matching the corresponding value assessment index according to the four-dimensional data asset value characteristic dimension and the value assessment index; step 7: configuring weights for the value assessment index according to the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 8: configuring weights for the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 4 and outputting the calculated score; step 9: configuring weights for the four-dimensional data asset value characteristic dimension, the value assessment index and the weights configured in step 10 Data asset value assessment score, identification and classification of data assets; Step 7: Obtain the data asset value assessment report, thereby solving the problem that the prior art does not conduct appropriate data classification and organization of data value assessment results, resulting in chaotic and inefficient data asset management, and is unable to formulate effective management strategies for data assets of different values, resulting in imperfect technical problems in data asset maintenance, updating, and utilization. It achieves the technical effect of being able to clearly display the value of data to internal business empowerment and external transaction circulation, and being able to clearly display the value growth of data based on a certain period of time, forming a more standardized data value assessment model, improving data management efficiency, and enabling enterprises to clearly understand their own asset status.

[0112] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0113] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the embodiments of the present invention. Thus, if these modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A four-dimensional data value assessment method, characterized in that: The method comprises: Step 1: Obtain the data assets to be evaluated and the relevant information elements of the data assets; Step 2: Determine the four-dimensional data asset value characteristic dimensions based on the data assets to be evaluated and the relevant information elements of the data assets; Step 3: Match the corresponding value assessment indicators according to the four-dimensional data asset value characteristic dimensions; Step 4: According to the four-dimensional data asset value characteristic dimension and the value assessment indicator, weights are configured for the value assessment indicator; Step 5: Calculate the data asset value assessment score based on the four-dimensional data asset value feature dimension, the value assessment index and the weight configured in step 4 and output the calculated score; Step 6: Identify and classify data assets according to the data asset value assessment score; Step 7: Obtain the data asset value assessment report.

2. The four-dimensional data value assessment method according to claim 1, characterized in that: In step 1, the data assets to be evaluated include original data assets and value-added data assets, wherein the original data assets are detailed data obtained through external acquisition or internal collection, and the value-added data assets are based on the original data assets and are summary data, personalized statistical data or data products obtained through data processing, handling, analysis, aggregation and mining.

3. The four-dimensional data value assessment method according to claim 1, characterized in that: In step 2, the four-dimensional data asset value feature dimensions include internal value features of original data assets, internal value features of value-added data assets, market value features of original data assets, and market value features of value-added data assets.

4. The four-dimensional data value assessment method according to claim 3, characterized in that: In step 3, matching corresponding value assessment indicators according to the four-dimensional data asset value feature dimension includes: The internal value characteristics of the original data assets are matched with the internal value assessment indicators of the original data assets, the market value characteristics of the original data assets are matched with the market value assessment indicators of the original data assets, the internal value characteristics of the value-added data assets are matched with the internal value assessment indicators of the value-added data assets, and the market value characteristics of the value-added data assets are matched with the market value assessment indicators of the value-added data assets; The internal value assessment indicators of the original data assets include: data scale, data quality, planning cost, acquisition cost, storage cost, and management cost, and the data quality includes accuracy, consistency, completeness, standardization, timeliness, and accessibility; The market value assessment indicators of the original data assets include: data application, data market, data security, and data risk; The internal value assessment indicators of value-added data assets include: data scale, data quality, planning cost, storage cost, processing cost, and management cost; The market value assessment indicators of value-added data assets include: data application, data market, data security, data risk, return on investment, decision-making value, commercial value, strategic value, and industrial value.

5. The four-dimensional data value assessment method according to claim 1, characterized in that: In step 4, the weight configuration method is a hierarchical analysis method or a neural network.

6. The four-dimensional data value assessment method according to claim 4, characterized in that: In step 5, the calculation of the data asset value assessment score includes: Step 51: The value evaluation index, obtains the corresponding value of the value evaluation index, and performs standardization on the corresponding value of the value evaluation index, and uniformly converts it into an evaluation value between 0 and 1, wherein: The standardization processing formula is: Step 52: Calculate the internal value of the data asset based on the evaluation value of step 51. The formula is: P 内部价值 =(TC+I+S) / 3; Among them, the TC is planning cost + acquisition cost + processing cost + storage cost + management cost, and the P 内部价值 is the evaluation value, TC is the total cost of data assets, I is the total score of data quality, S is the data scale, and I i is the evaluation value of the index related to data quality, the W i is the weight of the indicator; Step 53: Calculate the market value of the data asset based on the evaluation value of step 51. The formula is: P 外部价值 =(YES 数据应用 +DM 数据市场 +DS 数据安全 +DR 数据风险 +RI 投资回报 +DV 决策价值 +CV 商业价值 +SV 战略价值 +V 产业价值 ) / 9; Among them, the DA 数据应用 , the DM 数据市场 , the DS 数据安全 , the DR 数据风险 , the RI 投资回报 、The DV 决策价值 、The CV 商业价值 , the SV 战略价值 、The IV 产业价值 The scores of each indicator respectively.

7. The four-dimensional data value assessment method according to claim 1, characterized in that: In step 6, the identification and classification of data assets includes: The data asset value assessment scores are divided into core data assets, standard data assets, inefficient data assets, and invalid data assets, wherein data asset value assessment scores between 0.9 and 1.0 (including 0.9) are marked as core data assets; data asset value assessment scores between 0.75 and 0.9 (including 0.75) are marked as standard data assets; data asset value assessment scores between 0.6 and 0.75 (including 0.6) are marked as inefficient data assets; and data asset value assessment scores below 0.6 are marked as invalid data assets.

8. A four-dimensional data value assessment system, characterized in that: The system comprises: A data acquisition unit, the data acquisition unit is used to obtain the data assets to be evaluated and the data asset related information elements; A four-dimensional data asset value characteristic dimension determination unit, the four-dimensional data asset value characteristic dimension determination unit is used to determine the four-dimensional data asset value characteristic dimension according to the data asset to be evaluated and the data asset related information elements; A data value assessment indicator configuration unit, the data value assessment indicator configuration unit is used to match corresponding value assessment indicators according to the data assets to be assessed and the data asset related information elements and the four-dimensional data asset value characteristic dimensions; An indicator weight setting unit, the indicator weight setting unit is used to configure weights for the value assessment indicators according to the four-dimensional data asset value feature dimensions and the value assessment indicators; A data asset value evaluation calculation unit, the data asset value evaluation calculation unit is used to calculate the data asset value evaluation score and output the calculated score according to the four-dimensional data asset value characteristic dimension, the value evaluation index and the configured weight; A data asset classification and summary unit, the data asset classification and summary unit is used to identify and classify data assets according to the data asset value assessment score; A data asset value assessment report acquisition unit, wherein the data asset value assessment report acquisition unit is used to obtain the data asset value assessment report.

9. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the computer program is executed by the processor, the processor executes the steps of the four-dimensional data value assessment method as described in any one of claims 1 to 7 above.

10. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, it is used to implement the steps of the four-dimensional data value assessment method as described in any one of claims 1 to 7 above.

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