Information processing device, information processing method, and program

Abstract

To provide an information processing device, information processing method and program, which enable automatic computation of CO2 emissions associated with a product.SOLUTION: An information processing device according to an embodiment comprises computation means for outputting CO2 emissions of a first product derived by plugging data acquired from a data source into a formula prepared in advance, and the degree of reliability derived on the basis of the type of data plugged into the formula.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] CFP (Carbon Footprint) is an abbreviation for Carbon Footprint of Product, and is equivalent to the amount of greenhouse gases emitted throughout a product's life cycle, from raw material procurement to disposal and recycling, converted into CO2 emissions.

[0003] In recent years, it has become important to disclose and share the CFP of a product, for example by labeling the product with the CFP. For this reason, there is a demand for a system that automatically calculates the CFP (i.e., CO2 emissions) of a product. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] U.S. Patent Application Publication No. 2022 / 0101212 Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, an object of the present invention is to provide an information processing device, an information processing method, and a program that are capable of automatically calculating the CO2 emissions of a product. [Means for solving the problem]

[0006] The information processing device according to the embodiment includes a calculation means for outputting the CO2 emissions of a first product calculated by applying data acquired from a data source to a pre-prepared calculation formula, and a reliability calculated based on the type of data applied to the calculation formula. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the functional configuration of an information processing apparatus according to an embodiment. [Figure 2] FIG. 1 is a diagram showing an example of a hardware configuration of an information processing apparatus. [Figure 3] FIG. 10 is a diagram for explaining a product-related data source. [Figure 4] FIG. 10 is a diagram for explaining peripheral related data sources. [Figure 5] FIG. 10 is a diagram for explaining a secondary data source. [Figure 6] 10 is a flowchart showing an example of a processing procedure of an information processing device. [Figure 7] 10 is a flowchart showing an example of a processing procedure of a data acquisition process. [Figure 8] 10 is a flowchart showing an example of a processing procedure for calculating CO2 emissions. [Figure 9] 10 is a flowchart showing an example of a processing procedure for reliability calculation processing. [Figure 10] FIG. 10 is a diagram showing an example of evaluation axes for primary data. [Figure 11] FIG. 10 is a diagram showing an example of the correspondence between the evaluation result of primary data and the reliability. [Figure 12] FIG. 10 is a diagram showing an example of the correspondence between the evaluation result of similar data and the reliability. [Figure 13] FIG. 10 is a diagram showing an example of a display mode of the CO2 emissions and reliability of a product. [Figure 14] 10A and 10B are diagrams showing other examples of display modes of the CO2 emissions and reliability of a product. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments will be described with reference to the drawings. Fig. 1 is a block diagram showing an example of the functional configuration of an information processing device according to this embodiment. The information processing device 10 shown in Fig. 1 is an electronic device (an automatic CO2 emission calculation device) that is connected to a data source group 20 that manages various data used to calculate the amount of CO2 emitted in the life cycle of a product (hereinafter referred to as the CO2 emission amount of the product), for example, and is configured to automatically calculate the CO2 emission amount of the product based on the data acquired from the data source group 20.

[0009] In this embodiment, the CO2 emissions of a product calculated by the information processing device 10 include, for example, CFP (Carbon Footprint). In addition, the products for which CO2 emissions are calculated in this embodiment include, for example, devices such as batteries, but may be any products that emit CO2 during their life cycle, including manufacturing in a factory.

[0010] As shown in FIG. 1, the information processing device 10 includes a storage unit 11, a data acquisition unit 12, a first calculation unit 13, a second calculation unit 14, and a display processing unit 15.

[0011] The storage unit 11 stores (information about) calculation formulas prepared in advance for calculating the CO2 emissions of the above-mentioned products. In this embodiment, the calculation formulas stored in the storage unit 11 are defined to represent the CO2 emissions using variables into which data (values) acquired from the above-mentioned data source group 20 are substituted, for example.

[0012] C The data acquisition unit 12 acquires (collects) data necessary to calculate the CO2 emissions of a product from the data source group 20 based on variables (attributes of data substituted into the variables, etc.) used in the calculation formula stored in the storage unit 11. The data acquired by the data acquisition unit 12 is output to the first calculation unit 13.

[0013] The first calculation unit 13 calculates the CO2 emissions of the product by applying the data output from the data acquisition unit 12 to a calculation formula stored in the storage unit 11. The CO2 emissions of the product calculated by the first calculation unit 13 is output to the display processing unit 15.

[0014] The second calculation unit 14 calculates the reliability of the CO2 emissions of the product based on the type of data applied to the calculation formula by the first calculation unit 13 to calculate the CO2 emissions of the product. The reliability calculated by the second calculation unit 14 is output to the display processing unit 15.

[0015] The display processing unit 15 displays the CO 2 emission amount of the product output from the first calculation unit 13 and the reliability output from the second calculation unit 14.

[0016] Fig. 2 shows an example of the hardware configuration of the information processing device 10. As shown in Fig. 2, the information processing device 10 includes a CPU 101, a nonvolatile memory 102, a main memory 103, an input device 104, a display device 105, a communication device 106, and the like.

[0017] The CPU 101 is a hardware processor that controls the operation of each component in the information processing device 10. The CPU 101 may be composed of a single processor or multiple processors. The CPU 101 executes various programs loaded from the nonvolatile memory 102, which is a storage device, to the main memory 103. The programs executed by the CPU 101 include an operating system (OS) and various application programs.

[0018] The input device 104 is a device configured to input instructions and various data from a user, and includes, for example, a mouse and a keyboard. The display device 105 is a device configured to display various data, and includes, for example, a display. The communication device 106 is a device configured to perform, for example, wired or wireless communication with an external device (for example, the data source group 20, etc.).

[0019] Although only the nonvolatile memory 102 and the main memory 103 are shown in FIG. 2, the information processing device 10 may further include other storage devices such as an HDD (Hard Disk Drive) and an SSD (Solid State Drive).

[0020] In this embodiment, the storage unit 11 shown in FIG. 1 is realized by, for example, the nonvolatile memory 102 shown in FIG. 2 or other storage devices.

[0021] In this embodiment, some or all of the data acquisition unit 12, first calculation unit 13, second calculation unit 14, and display processing unit 15 shown in Fig. 1 are realized by causing the CPU 101 (i.e., the computer of the information processing device 10) shown in Fig. 2 to execute a predetermined program, that is, by software. This program may be downloaded to the information processing device 10 via a network, or may be stored in a storage medium and distributed.

[0022] Here, it has been described that some or all of the units 12 to 15 are realized by software, but some or all of the units 12 to 15 may also be realized by hardware such as an IC (Integrated Circuit), or may be realized by a configuration that combines software and hardware.

[0023] An example of the data source group 20 assumed in this embodiment will be described below. In this embodiment, the CO2 emissions of a product are calculated as described above, and the data source group 20 from which data necessary to calculate the CO2 emissions of the product are obtained includes, for example, product-related data sources, peripheral-related data sources, and secondary data sources.

[0024] First, the product-related data sources included in the data source group 20 will be described with reference to Fig. 3. The product-related data source 201 shown in Fig. 3 is a data source that manages data (information) related to various products, and includes, for example, part configuration data 201a and product data 201b.

[0025] Generally, a product (for example, a battery) may be composed of multiple parts, and the part configuration data 201a is data indicating the multiple parts that compose the product.

[0026] The product data 201b includes, for example, the product number, serial number, type, weight, size, and CO2 emissions (direct emissions) during the manufacture of the product.

[0027] Next, the peripheral-related data sources included in the data source group 20 will be described with reference to Fig. 4. The peripheral-related data source 202 shown in Fig. 4 is a data source that manages data (information) related to the periphery of a product (for example, its life cycle), and includes, for example, procurement data 202a and manufacturing data 202b.

[0028] Generally, a product may be manufactured by procuring parts from other businesses (other companies) than the business that manufactures the product (your company), and the procurement data 202a is data related to parts procured from other companies to manufacture the product, and includes, for example, the CO2 emissions of the parts. The CO2 emissions of a part correspond to, for example, the amount of CO2 emitted during the life cycle of the part.

[0029] The manufacturing data 202b is data related to the manufacturing (production) of a product, and includes, for example, the amount of CO2 emissions (indirect emissions) associated with the consumption (use) of energy (e.g., electricity, heat, etc.) on the manufacturing line of the product, and the number of products manufactured on the manufacturing line.

[0030] Next, the secondary data sources included in the data source group 20 will be described with reference to Fig. 5. The secondary data source 203 shown in Fig. 5 is a data source that manages secondary data, and includes, for example, basic unit data 203a.

[0031] Generally, the term "basic unit" refers to the amount of fuel, labor, etc. required to manufacture (produce) a certain amount of product, but in this embodiment, the basic unit data 203a is data equivalent to an index of CO2 emissions, and indicates, for example, the amount of CO2 emissions per business activity amount (amount related to the scale of activity).

[0032] In this embodiment, the data source group 20 is described as including a product-related data source 201, a peripheral-related data source 202, and a secondary data source 203, but the data source group 20 may omit some of the data sources 201 to 203, or may further include data sources different from the data sources 201 to 203.

[0033] Furthermore, the data managed in the data source group 20 may be set with the provider of the data, the creation date and time, the expiration date, and the like.

[0034] An example of a processing procedure of the information processing device 10 according to this embodiment will be described below with reference to the flowchart of FIG.

[0035] First, in the information processing device 10, a product (hereinafter referred to as a target product) for which CO2 emissions are to be calculated is determined from, for example, a plurality of products (step S1). Note that the target product may be designated (instructed) by a user using, for example, the input device 104, or may be determined in advance.

[0036] When the process of step S1 is executed, the data acquisition unit 12 executes a process (hereinafter referred to as a data acquisition process) of acquiring (collecting) data necessary for calculating the CO2 emissions of the target product determined in step S1 from the data source group 20 (step S2). The data acquired in the data acquisition process includes primary data, similar data, and secondary data. The primary data, similar data, and secondary data will be described later.

[0037] Next, the first calculation unit 13 executes a process (hereinafter referred to as a CO2 emission calculation process) to calculate the CO2 emission amount of the target product by applying the data acquired in step S2 to the calculation formula stored in the storage unit 11 (step S3). In the CO2 emission calculation process, the CO2 emission amount is calculated by substituting the data acquired in step S2 for the variables used in the calculation formula.

[0038] Furthermore, the second calculation unit 14 executes a process (hereinafter referred to as a reliability calculation process) for calculating the reliability of the CO2 emissions based on the type of data substituted for the variables in step S3 (i.e., the data used to calculate the CO2 emissions) (step S4). In the reliability calculation process, a reliability is calculated according to whether the primary data, similar data, or secondary data was used to calculate the CO2 emissions of the target product.

[0039] When the processes of steps S3 and S4 are executed, the display processing unit 15 displays the CO2 emission amount calculated in step S3 and the reliability calculated in step S4 on the display device 105 (step S5).

[0040] Although the description here is given assuming that the CO2 emissions and reliability are displayed on the display device 105, the CO2 emissions and reliability may be transmitted (output) to a terminal device other than the information processing device 10 for display on the terminal device, or may be transmitted (output) to an external server device or the like for use in other processing.

[0041] The data acquisition process, CO2 emission calculation process, and reliability calculation process will be described in detail below.

[0042] First, an example of the processing procedure of the data acquisition processing (the processing of step S2 shown in FIG. 6) will be described with reference to the flowchart of FIG.

[0043] In this embodiment, the CO2 emissions of the target product are calculated using a calculation formula stored in the storage unit 11, which corresponds to a formula that expresses the CO2 emissions using a plurality of variables into which data acquired from the data source group 20 is substituted, for example. Note that the calculation formula may have a configuration that allows it to be expanded, a specific example of which will be described later.

[0044] The data acquisition unit 12 acquires the calculation formula stored in the storage unit 11, and identifies a plurality of variables used in the calculation formula (attributes of data to be substituted into the variables) (step S11).

[0045] The data acquisition unit 12 acquires data to be substituted for each of the multiple variables identified in step S11 from the data source group 20. Note that the data managed in the data source group 20 includes not only data from the business (our company) that manufactures the target product described above, but also data from other businesses that manufacture other products, publicly available data, and the like.

[0046] Here, as described above, the data acquired in the data acquisition process includes primary data, similar data, and secondary data. Primary data is, for example, data obtained directly from the target product or components by actually measuring the target product or the components that make up the target product. In this embodiment, the primary data corresponds to, for example, data managed in the product-related data source 201 and the peripheral-related data source 202 included in the data source group 20. Similar data is, for example, data (primary data) obtained directly from products similar to the target product (hereinafter referred to as similar products). Secondary data is existing data that has been prepared in advance and is not obtained from the target product. In this embodiment, the secondary data corresponds to, for example, data managed in the secondary data source 203 included in the data source group 20.

[0047] Of the above-mentioned primary data, similar data, and secondary data, it can be said that the primary data is the most reliable, so it is preferable to calculate the CO2 emissions of the target product using this primary data.

[0048] For this reason, the data acquiring unit 12 searches for primary data corresponding to the variable identified in step S11 (primary data that can be substituted for the variable) from the above-mentioned primary data (for example, data managed in the product-related data source 201 or the peripheral-related data source 202, etc.) (step S12). The data acquiring unit 12 acquires the data searched for in step S12 from the data source group 20.

[0049] The data acquisition unit 12 determines whether or not all the data necessary to calculate the amount of CO2 emissions has been acquired (step S13).

[0050] If it is determined that all the data has been acquired (YES in step S13), the data acquiring unit 12 outputs the data acquired by executing the process of step S12 to the first calculation unit 13, and ends the data acquisition process.

[0051] On the other hand, if it is determined that all the data has not been acquired (NO in step S13), the data acquisition unit 12 searches for similar data (similar data that can be assigned to the variable) corresponding to the variable identified in step S11 and for which the primary data has not been acquired from the above-mentioned similar data (for example, data managed in the product-related data source 201 or the peripheral-related data source 202, etc.) (step S14).

[0052] Here, the similar data is primary data obtained from similar products, and the similar products are identified based on their similarity to the target product. The similarity may be calculated, for example, based on attributes that can be considered similar to the target product. Specifically, attributes that can be considered similar to the target product include, for example, lot number and model number, and the similarity may be calculated based on the number of attributes that match the target product. The similarity may also be calculated, for example, based on the degree of match in parts configuration (i.e., the number of parts that match the target product). Furthermore, the similarity may be calculated, for example, based on whether the similar product belongs to the same product family as the target product (i.e., whether the similar product is a series product of the target product). Note that the method for calculating the similarity described here is merely an example, and the similarity may be calculated using other methods.

[0053] In this embodiment, for example, the product with the highest similarity calculated as described above is defined as the similar product, and in step S14, data corresponding to variables for which primary data has not been acquired is searched from the primary data (similar data) obtained from such similar products. The data acquisition unit 12 acquires the data searched in step S14 from the data source group 20.

[0054] If the similar data is data from another company, it may be impossible to search for the similar data because the labels assigned to the attributes defined in the data are different between the company's data and the other company's data. In this case, it may be possible to search for similar data by, for example, using a semantic information identifier to associate the company's data with the other company's data, which have different labels assigned to the attributes.

[0055] The data acquisition unit 12 determines whether or not all the data necessary to calculate the amount of CO2 emissions has been acquired (step S15).

[0056] If it is determined that all the data has been acquired (YES in step S15), the data acquisition unit 12 outputs the data acquired by executing the processes of steps S12 and S14 to the first calculation unit 13, and ends the data acquisition process.

[0057] On the other hand, if it is determined that all the data has not been acquired (NO in step S15), the data acquiring unit 12 searches for secondary data (secondary data that can be assigned to the variable) corresponding to the variable identified in step S11 and for which the primary data and similar data have not been acquired from the above-mentioned secondary data (for example, data managed in the secondary data source 203, etc.) (step S16). The data acquiring unit 12 acquires the data searched in step S16 from the data source group 20.

[0058] When the process of step S16 is executed, the data acquisition unit 12 outputs the data acquired by executing the processes of steps S12, S14, and S16 to the first calculation unit 13, and ends the data acquisition process.

[0059] 7 is executed, the data output from the data acquisition unit 12 to the first calculation unit 13 is assumed to have information indicating the type of data (hereinafter referred to as data type information) added thereto. The data type information includes, for example, identification information (hereinafter referred to as data source ID) for identifying the data source from which the data was acquired. If the data output from the data acquisition unit 12 to the first calculation unit 13 is similar data, the data type information added to the data further includes the degree of similarity between the target product and similar products. Such data type information makes it possible to identify whether the data output from the data acquisition unit 12 to the first calculation unit 13 is primary data, similar data, or secondary data.

[0060] Furthermore, for example, when a plurality of primary data are searched for in step S12, the plurality of primary data may be presented to the user, and the user may select the primary data to be used for calculating the CO2 emissions. Here, step S12 has been described, but the same applies to steps S14 and S16.

[0061] According to the above-mentioned data acquisition process, if it is not possible to acquire (search) all the data used to calculate the CO2 emissions of the target product from the primary data, similar data or secondary data can be acquired as a substitute for the primary data.

[0062] An example of the procedure of the CO2 emission amount calculation process (the process of step S3 shown in FIG. 6) will be described with reference to the flowchart of FIG.

[0063] Here, the calculation formula stored in the storage unit 11 as described above corresponds to a formula that is the starting point for calculating the CO2 emissions. Hereinafter, for convenience, the variables used in such calculation formulas will be referred to as first variables.

[0064] The first calculation unit 13 acquires the calculation formula stored in the storage unit 11. The first calculation unit 13 assigns the data output from the data acquisition unit 12 (i.e., the data acquired in the data acquisition process) to a plurality of first variables used in the calculation formula acquired from the storage unit 11 (step S21).

[0065] When the process of step S21 is executed, it is determined whether data has been substituted for all first variables used in the calculation formula (step S22).

[0066] If it is determined that data has been substituted for all the first variables (YES in step S22), the first calculation unit 13 calculates the CO2 emissions of the target product according to the calculation formula in which data has been substituted for the first variables (step S23).

[0067] The CO 2 emission amount calculated in step S23 is output from the first calculation unit 13 to the display processing unit 15.

[0068] Here, the above-described formula expresses the CO2 emissions using a plurality of first variables, but there are cases where the first variables can be expressed by a formula using other variables (hereinafter, second variables), for example.

[0069] According to this, when it is determined that data has not been assigned to all the first variables (that is, there are first variables to which data cannot be assigned) (NO in step S22), the first calculation unit 13 expands the calculation formula (step S24). Note that in step S24, a process is executed in which the first variables to which data has not been assigned are replaced with a formula using a plurality of second variables, for example.

[0070] After the process of step S24 is executed, the process returns to step S21 and is repeated. In this case, in step S21, the process of substituting data into the second variables is executed, and if it is determined in step S22 that data has been substituted into all the second variables, the CO2 emissions of the target product are calculated according to the calculation formula in which data has been substituted into the second variables.

[0071] It is assumed here that the data to be assigned to the second variable used in the expanded calculation formula has already been acquired in the data acquisition process as data necessary to calculate CO2 emissions, but the data to be assigned to the second variable may also be acquired from the data source group 20 after the processing of step S24 is executed.

[0072] According to the above-described CO2 emission calculation process, even if it is not possible to substitute the data acquired in the data acquisition process into all of the variables used in the calculation formula (i.e., it is not possible to calculate the CO2 emission amount using the calculation formula), it is possible to calculate the CO2 emission amount by expanding the calculation formula.

[0073] When the CO2 emission calculation process is executed, the data used to calculate the CO2 emission of the target product (i.e., the data substituted into the variables) is output (notified) from the first calculation unit 13 to the second calculation unit 14.

[0074] Furthermore, in Figure 8, we have explained a case where it is possible to calculate CO2 emissions by expanding a calculation formula, but if, for example, data cannot be substituted into all variables even when the calculation formula is expanded, the user may be notified that the CO2 emissions of the target product cannot be calculated due to insufficient data (i.e., an error).

[0075] Here, a specific example of the calculation formula used in this embodiment will be described. Here, the calculation formula (starting formula) is assumed to be "CO2 emissions = Scope1 + Scope2 + Scope3".

[0076] Scope 1 is a variable that represents the amount of CO2 emitted directly by a business (your own company) during the manufacture of the target product (direct emissions). Scope 2 is a variable that represents the CO2 emissions associated with the energy consumption in the manufacture of the target product (indirect emissions). Scope 3 is a variable that represents the CO2 emissions of related businesses (other companies) throughout the target product's life cycle. In other words, Scope 3 is a variable that represents the amount of CO2 emitted indirectly by suppliers, etc., excluding Scope 1 and 2. For example, according to the GHG (GreenHouse Gas) Protocol, Scope 3 is divided into 15 categories, such as procurement and transportation. If the period before and after the manufacture of the target product is described as upstream and downstream, categories 1 to 8 of the 15 categories correspond to upstream, and categories 9 to 15 correspond to downstream.

[0077] Scope 2 can be expressed, for example, by an equation using a variable representing the CO2 emissions associated with energy consumption on a production line and a variable representing the number of products on the production line. Specifically, Scope 2 can be expressed, for example, by the equation "CO2 emissions associated with energy consumption on a production line / number of products on the production line."

[0078] Furthermore, Scope 3 can be expressed by an equation using variables that represent the CO2 emissions of each part procured to manufacture the target product. If the parts procured to manufacture the target product are parts 1 to 3, Scope 3 can be expressed by the equation, for example, "CO2 emissions of part 1 + CO2 emissions of part 2 + CO2 emissions of part 3." Note that the fact that the target product is composed of parts 1 to 3 can be determined from part configuration data 201a included in product-related data source 201.

[0079] In other words, the above formula "CO2 emissions = Scope 1 + Scope 2 + Scope 3" can be expanded into a formula using the variables "Scope 1," "CO2 emissions associated with energy consumption on the production line," "number of products on the production line," "CO2 emissions of the first part," "CO2 emissions of the second part," and "CO2 emissions of the third part."

[0080] In this case, in the data acquisition process, for example, product data 201b is acquired from the product-related data source 201 as data corresponding to the variable "Scope1." Furthermore, in the data acquisition process, data corresponding to the variable "Scope2" (i.e., data that can be directly assigned to the variable) is not acquired, but, for example, manufacturing data 202b is acquired from the peripheral-related data source 202 as data corresponding to the variables "CO2 emissions associated with energy consumption on the production line" and "number of products manufactured on the production line" used in the formula representing the variable "Scope2." Furthermore, in the data acquisition process, data corresponding to the variable "Scope3" (i.e., data that can be directly assigned to the variable) is not acquired, but, for example, procurement data 202a is acquired from the peripheral-related data source 202 as data corresponding to the variables "CO2 emissions of the first part," "CO2 emissions of the second part," and "CO2 emissions of the third part" used in the formula representing "Scope3."

[0081] In this case, the CO2 emissions of the target product can be calculated by substituting the data (values) acquired as described above into each variable. Specifically, if the value assigned to the variable "Scope 1 (direct emissions)" is 100, the value assigned to the variable "CO2 emissions associated with energy consumption on the production line" is 1000, the value assigned to the variable "number of products manufactured on the production line" is 20, the value assigned to the variable "CO2 emissions of the first part" is 20, the value assigned to the variable "CO2 emissions of the second part" is 30, and the value assigned to the variable "CO2 emissions of the third part" is 40, then the CO2 emissions of the target product = 100 (Scope 1) + 50 (Scope 2 = 1000 / 20) + 90 (Scope 3 = 20 + 30 + 09) = 240 is calculated.

[0082] The calculation formula described here is just an example, and a different formula may be used to calculate the CO2 emissions of the target product. Specifically, when calculating the CO2 emissions over the life cycle of the target product as described above, a more complex formula may be used.

[0083] Next, an example of the procedure of the reliability calculation process (the process of step S4 shown in FIG. 6) will be described with reference to the flowchart of FIG.

[0084] First, the second calculation unit 14 acquires the data output from the first calculation unit 13 as described above. The data acquired by the second calculation unit 14 in this way is the data substituted for the variables in the calculation formula in the CO2 emission amount calculation process described above. The second calculation unit 14 evaluates (acquires) the reliability of the data substituted for the variables in this way (the data corresponding to the variables) (step S31). Hereinafter, the data to be evaluated in step S31 will be referred to as evaluation target data for convenience.

[0085] In step S31, the reliability of the evaluation target data is evaluated based on the type of the evaluation target data. Specifically, the type of evaluation target data can be identified based on data type information added to the evaluation target data. If the evaluation target data is primary data, the reliability of the evaluation target data is defined (evaluated) as 100, if the evaluation target data is similar data, the reliability of the evaluation target data is 50, and if the evaluation target data is secondary data, the reliability of the evaluation target data is defined (evaluated) as 0. Note that in this embodiment, when the evaluation target data (data substituted into a variable) is secondary data, this includes the case where a value calculated using, for example, basic unit data corresponding to the secondary data is substituted into the variable.

[0086] When the process of step S31 is executed, it is determined whether or not the process of step S31 has been executed for all data substituted into variables used in the calculation formula (step S32).

[0087] If it is determined that the process has not been performed for all the data (NO in step S32), the process returns to step S31 and is repeated. In other words, in the reliability calculation process, the process of step S31 is repeated until the reliability of all the data substituted into the variables used in the calculation formula is obtained.

[0088] If it is determined that processing has been performed on all data (i.e., the reliability of all data has been obtained) (YES in step S32), the second calculation unit 14 calculates the reliability of the CO2 emissions of the target product based on the reliability of all the data (step S33).

[0089] An example of the processing in step S33 will be described below. If the calculation formula is the above-mentioned "CO2 emissions = Scope1 + Scope2 + Scope3," then in step S33, the reliability of each of the variables "Scope1," "Scope2," and "Scope3" used in the calculation formula is calculated, and the average value of the calculated reliability can be calculated as the reliability of the CO2 emissions of the target product.

[0090] Here, for example, assume that the data to be evaluated assigned to the variable "Scope1 (direct emissions)" is primary data. In this case, the reliability of the data to be evaluated assigned to "Scope1 (direct emissions)" is 100, and the reliability of the data to be evaluated is set to the reliability of the variable "Scope1".

[0091] Also, for example, assume that the variable "Scope 2" is expressed by an equation using the variables "CO2 emissions associated with energy consumption on the production line" and "number of products on the production line," and that the data to be evaluated substituted into the variable "CO2 emissions associated with energy consumption on the production line" is similar data, and the data to be evaluated substituted into the variable "number of products on the production line" is primary data. In this case, for example, the reliability of the data to be evaluated substituted into the variable "CO2 emissions associated with energy consumption on the production line" is 50, and the reliability of the data to be evaluated substituted into the variable "number of products on the production line" is 100, and the average of the reliability of the two data to be evaluated (i.e., 75) is set to the reliability of the variable "Scope 2."

[0092] Furthermore, assume that the variable "Scope3" is expressed by an equation using the variables "CO2 emissions of the first part," "CO2 emissions of the second part," and "CO2 emissions of the third part," and that the data to be evaluated assigned to the variable "CO2 emissions of the first part" is primary data, the data to be evaluated assigned to the variable "CO2 emissions of the second part" is similar data, and the data to be evaluated assigned to the variable "CO2 emissions of the third part" is secondary data. In this case, the reliability of the data to be evaluated assigned to the variable "CO2 emissions of the first part" is 100, the reliability of the data to be evaluated assigned to the variable "CO2 emissions of the second part" is 50, and the reliability of the data to be evaluated assigned to the variable "CO2 emissions of the third part" is 0, and the average of the reliability of the three pieces of data to be evaluated (i.e., 50) is set to the reliability of the variable "Scope3."

[0093] According to this, the reliability of the CO2 emissions of the target product calculated according to the formula using the variables "Scope 1," "Scope 2," and "Scope 3" is calculated to be 75, which is the average value of the reliability of each of the variables "Scope 1," "Scope 2," and "Scope 3."

[0094] As described above, the reliability calculated in step S33 is output from the second calculation unit 14 to the display processing unit 15, and the reliability calculation process ends.

[0095] When the reliability calculation process described above is executed, a high reliability is calculated when primary data is applied to the calculation formula, a lower reliability is calculated when similar data is applied to the calculation formula, and an even lower reliability is calculated when secondary data is applied to the calculation formula.

[0096] The method for calculating the reliability of the CO2 emissions of the target product described here is merely an example, and the reliability of the CO2 emissions of the target product may be calculated by other methods. Also, although the reliability of the CO2 emissions of the target product is mainly calculated using the average value of the reliability of the evaluation target data, the reliability of the CO2 emissions of the target product may also be calculated using a weighted average value of the reliability of the evaluation target data.

[0097] Furthermore, it has been explained here that if the data to be evaluated is primary data, the reliability of the data to be evaluated is 100, if the data to be evaluated is similar data, the reliability of the data to be evaluated is 50, and if the data to be evaluated is secondary data, the reliability of the data to be evaluated is 0, but the reliability of each data may be a different value.

[0098] Specifically, for example, when the evaluation target data is primary data, the reliability of the evaluation target data may be further evaluated along another evaluation axis (perspective).

[0099] Figure 10 shows an example of evaluation axes for primary data. Here, an evaluation axis related to data quality is assumed, and the example shown in Figure 10 shows that the data to be evaluated is evaluated from the perspectives of "provider" and "time."

[0100] Specifically, from the perspective of the "provider," the reliability of the data to be evaluated is evaluated based on the condition that the provider of the data to be evaluated is certified as being able to provide data for calculating CO2 emissions (hereinafter referred to as the first condition) and the condition that the provider of the data to be evaluated has a track record of transactions with the business (your company) that manufactures the target product (hereinafter referred to as the second condition).

[0101] Furthermore, from the perspective of "time," the reliability of the data to be evaluated is evaluated based on the condition that the expiration date set for the data to be evaluated has not expired (i.e., the data to be evaluated is data within the expiration date) (hereinafter referred to as the third condition) and the creation date and time set for the data to be evaluated (the date and time the data to be evaluated was created) is within the last six months (hereinafter referred to as the fourth condition).

[0102] According to this, the reliability of the evaluation target data (primary data) can be determined according to the number of conditions that the evaluation target data satisfies among the first to fourth conditions that are predetermined as the evaluation axes of the above-mentioned primary data.

[0103] Here, Fig. 11 shows an example of the correspondence relationship (correspondence table) between the number of conditions satisfied by the evaluation target data (i.e., the evaluation result of the primary data) and the reliability of the evaluation target data. Note that "04" to "00" in the evaluation result of the primary data in Fig. 11 represent the number of conditions satisfied by the evaluation target data described above.

[0104] Fig. 11 shows that the reliability of evaluation target data that satisfies all of the first to fourth conditions is 100. Fig. 11 also shows that the reliability of evaluation target data that satisfies three of the first to fourth conditions is 80, the reliability of evaluation target data that satisfies two of the conditions is 60, the reliability of evaluation target data that satisfies one condition is 40, and the reliability of evaluation target data that does not satisfy all of the first to fourth conditions is 20.

[0105] That is, the example shown in FIG. 11 indicates that the reliability of the evaluation target data (primary data) takes on different values ​​depending on whether the evaluation target data satisfies each of the first to fourth conditions.

[0106] The correspondence relationship between the evaluation results of the primary data and the reliability shown in FIG. 11 is an example, and the reliability corresponding to the evaluation results may be a different value.

[0107] In addition, although the reliability of the evaluation target data, which is primary data, has been described here as being evaluated on evaluation axes based on the perspectives of "provider" and "time," the reliability of the evaluation target data may be evaluated on different evaluation axes or on more evaluation axes. Furthermore, the evaluation axes for evaluating the reliability of the evaluation target data (primary data) may be set based on a perspective that contributes to determining the reliability (a perspective that is useful for determining the reliability).

[0108] Here, the case where the evaluation target data is primary data has been described. However, if the evaluation target data is similar data, the reliability of the evaluation target data may be further evaluated, for example, based on the similarity between the target product and the similar product from which the evaluation target data (similar data) was obtained (hereinafter referred to as the similarity of the evaluation target data). In other words, the reliability of the evaluation target data (similar data) can be determined according to the similarity of the evaluation target data. Note that the similarity of the evaluation target data is included in, for example, data type information added to the evaluation target data, and is acquired from the data type information. Note that the similarity of the evaluation target data (the similarity between the target product and similar products) has been described above, and therefore a detailed description thereof will be omitted here.

[0109] Here, Fig. 12 shows the correspondence relationship (correspondence table) between the similarity of the data to be evaluated (i.e., the evaluation result of similar data) and the reliability of the data to be evaluated. Note that "△4" to "△0" in the evaluation result of similar data in Fig. 12 indicate the (range of) similarity of the data to be evaluated. In this case, the range of values ​​that the similarity can take is 0 to 100 (i.e., the minimum value of similarity is 0 and the maximum value is 100).

[0110] According to Figure 12, "Δ4" indicates that the range of similarity is, for example, 90 to 100, and if the similarity of the data to be evaluated falls within the range indicated by "Δ4", the reliability of the data to be evaluated is set to 90.

[0111] Furthermore, according to Figure 12, "Δ3" indicates that the range of similarity is, for example, 80 to 90, and if the similarity of the data to be evaluated falls within the range indicated by "Δ3", the reliability of the data to be evaluated is set to 70.

[0112] Furthermore, according to Figure 12, "Δ2" indicates that the range of similarity is, for example, 70 to 80, and if the similarity of the data to be evaluated falls within the range indicated by "Δ2", the reliability of the data to be evaluated is set to 50.

[0113] Furthermore, according to Figure 12, "Δ1" indicates that the range of similarity is, for example, 60 to 70, and indicates that if the similarity of the data to be evaluated falls within the range indicated by "Δ1", the reliability of the data to be evaluated is set to 30.

[0114] 12, "Δ0" indicates that the range of similarity is, for example, 50 to 60, and indicates that when the similarity of the data to be evaluated falls within the range indicated by "Δ0", the reliability of the data to be evaluated is set to 10. Here, it is assumed that data to be evaluated with a similarity of less than 50 will not be used to calculate CO2 emissions, but "Δ0" may indicate a range of similarity from 0 to 60.

[0115] That is, the example shown in FIG. 12 indicates that the reliability of the evaluation target data (similar data) takes on different values ​​depending on the similarity between the target product and the similar product.

[0116] The correspondence between the evaluation results and reliability of similar data shown in FIG. 12 is an example, and the reliability corresponding to the evaluation results may be different values.

[0117] Also, although the reliability of the evaluation target data, which is similar data, has been described here as being evaluated based on the similarity, the reliability of the evaluation target data (similar data) may be further evaluated from a different perspective.

[0118] Here, the case where the data to be evaluated is primary data and similar data has been described, but when the data to be evaluated is secondary data, the reliability of the data to be evaluated can be a fixed value such as 0 as described above. Note that the reliability of the data to be evaluated, which is secondary data, may be a fixed value other than 0 (for example, 40), or may be further evaluated from other perspectives (that is, it may be a different value depending on the evaluation result).

[0119] According to the reliability calculation process described above, the reliability of the CO2 emissions of the target product calculated according to the calculation formula can be calculated depending on the type of data (primary data, similar data, and secondary data) substituted into the variables used in the calculation formula.

[0120] Note that the reliability calculation process is a process for calculating the reliability of the CO2 emission amount of the target product based on the type of data used to calculate the CO2 emission amount in the CO2 emission calculation process (i.e., a process related to the CO2 emission calculation process), and therefore the reliability calculation process may be incorporated into and executed in the CO2 emission calculation process. Specifically, the reliability calculation process may be executed as part of the CO2 emission calculation process, or may be executed in parallel with the CO2 emission calculation process.

[0121] Here, in this embodiment, the CO2 emission amount of the target product calculated by executing the CO2 emission calculation process and the reliability calculated by executing the reliability calculation process are displayed.

[0122] In this embodiment, it is sufficient if at least the CO2 emissions and reliability of the target product are displayed, but it is considered that the CO2 emissions and reliability of the target product will be more useful to the user if they are displayed together with other information.

[0123] Hereinafter, with reference to FIG. 13, an example of a display mode of the CO2 emission amount and reliability of the target product in this embodiment will be described.

[0124] In the example shown in Figure 13, the CO2 emissions and reliability of the target product are displayed in a table format. Note that the CO2 emissions of the target product are assumed to be calculated according to the formula "Scope1+Scope2+Scope3", for example.

[0125] 13 shows that the target product is composed of parts 1 to 3. Note that the CO2 emissions of each of the parts 1 to 3 can be calculated in the same way as the CO2 emissions of the target product, for example, according to the formula "Scope1+Scope2+Scope3".

[0126] In the example shown in FIG. 13, the first part is composed of three parts a and two parts c. Here, it is assumed that the CO2 emissions (unit CO2 emissions) of part a are 10, and the CO2 emissions (unit CO2 emissions) of part c are 30. In this case, the value substituted for the variable "Scope3" used in the calculation formula for calculating the CO2 emissions of the first part is 10×3+30×2=90. Note that, although a detailed explanation will be omitted, in FIG. 13, if the value substituted for the variable "Scope1" used in the calculation formula for calculating the CO2 emissions of the first part is 10, and the value substituted for the variable "Scope2" used in the calculation formula is 20, the CO2 emissions of the first part will be 10+20+90=120.

[0127] Furthermore, the second part is composed of one part b and one part c. Here, it is assumed that the CO2 emissions of part b are 20 and the CO2 emissions of part c are 30. In this case, the value substituted for the variable "Scope3" used in the calculation formula for calculating the CO2 emissions of the second part is 20 + 30 = 50. Although a detailed explanation will be omitted, in FIG. 13, if the value substituted for the variable "Scope1" used in the calculation formula for calculating the CO2 emissions of the second part is 20 and the value substituted for the variable "Scope2" used in the calculation formula is 40, the CO2 emissions of the second part will be 20 + 40 + 50 = 110.

[0128] Furthermore, the third part is composed of one part a, one part c, one part d, and one part e. Here, it is assumed that the CO2 emissions of part a are 10, the CO2 emissions of part c are 30, the CO2 emissions of part d are 40, and the CO2 emissions of part e are 50. In this case, the value substituted for the variable "Scope3" used in the calculation formula for calculating the CO2 emissions of the third part is 10 + 30 + 40 + 50 = 130. Note that, although a detailed explanation will be omitted, in FIG. 13, if the value substituted for the variable "Scope1" used in the calculation formula for calculating the CO2 emissions of the third part is 30 and the value substituted for the variable "Scope2" used in the calculation formula is 60, the CO2 emissions of the third part will be 30 + 60 + 130 = 220.

[0129] The total CO2 emissions of the first to third parts (120+110+220=450) corresponds to the value substituted for "Scope 3" used in the formula for calculating the CO2 emissions of the target product. Although a detailed explanation will be omitted, if the value substituted for the variable "Scope 1" used in the formula for calculating the CO2 emissions of the target product is 50 and the value substituted for the variable "Scope 2" used in the formula is 100, the CO2 emissions of the target product will be 50+100+450=600.

[0130] As described above, in the example shown in FIG. 13, the user can easily grasp not only the CO2 emissions of the target product, but also the values ​​substituted into the variables used in the calculation formula to calculate the CO2 emissions of the target product, the CO2 emissions of each part that makes up the target product, etc.

[0131] Furthermore, in the example shown in Fig. 13, reliability is displayed in association with the target product and the parts (of which CO2 emissions) that constitute the target product. Note that Fig. 13 displays the average reliability calculated using the average value of the reliability of the data used to calculate the CO2 emissions and the weighted average reliability calculated using the weighted average value of the reliability of the data, but it is also possible to display only one of the average reliability and the weighted average reliability.

[0132] 13, a data source ID for identifying the data source from which the data substituted for the variables used in the formula for calculating the CO2 emissions was obtained (collected), a reliability symbol, and the type of the data (primary data, similar data, or secondary data) are also displayed. Note that the reliability symbols correspond to "04" to "00" shown in FIG. 11 and "04" to "00" shown in FIG. 12.

[0133] Furthermore, when the reliability of the data (primary data) substituted into the variables used in the calculation formula as described above is determined according to the number of conditions satisfied by the data, information on whether or not the data satisfies each of the first to fourth conditions described above may be further displayed, as shown in Fig. 13. Although omitted in Fig. 13, when the reliability of the data (similar data) substituted into the variables used in the calculation formula is determined according to the similarity of the data (the similarity between the target product and similar products), information on the similarity of the data may further be displayed.

[0134] Note that, although Figure 13 describes a case where the CO2 emissions and reliability of the target product are displayed in a table format, the CO2 emissions and reliability of the target product may also be displayed in a format (tree structure format) in which each part that makes up the target product is arranged at each level.

[0135] Furthermore, although FIG. 13 shows an example in which relatively detailed information is displayed, as shown in FIG. 14, it is also acceptable to display only, for example, "component composition," "total," "average reliability," "weighted average reliability," and "reliability symbol."

[0136] As described above, the information processing device 10 according to this embodiment outputs the CO2 emissions of the target product (first product) calculated by applying data acquired from a data source to a pre-prepared calculation formula, and the reliability calculated based on the type of data applied to the calculation formula. In this embodiment, this configuration makes it possible to automatically calculate the CO2 emissions of the target product.

[0137] For example, disclosing and sharing the CO2 emissions (CFP) of a product throughout its life cycle is important. However, the data needed to calculate the CO2 emissions is scattered across various data sources, making it difficult to collect data from such a group of data sources. Furthermore, if the data needed to calculate the CO2 emissions is not available, the CO2 emissions cannot be calculated.

[0138] However, in this embodiment, the data acquired from the data source group 20 includes at least one of the primary data of the target product, similar data which is primary data of a similar product (second product) similar to the target product, and secondary data of the target product. That is, in this embodiment, even if the data required to calculate CO2 emissions is not included in the primary data, it is possible to automatically collect similar data or secondary data and calculate the CO2 emissions.

[0139] Furthermore, in this embodiment, since the primary data of the target product is highly reliable and data other than the primary data of the target product (similar data and secondary data) is considered to be less reliable than the primary data of the target product, a reliability is defined according to the type of data used to calculate the CO2 emissions, and the reliability is output together with the CO2 emissions. This allows the user to easily understand the reliability of the CO2 emissions of the target product calculated by the information processing device 10, and makes it possible to appropriately use the CO2 emissions according to the reliability.

[0140] In this embodiment, the CO2 emissions of the target product are calculated by substituting (the values ​​of) data acquired from the data source group 20 into the variables used in the calculation formula. However, if it is not possible to acquire data to be substituted into all of the variables used in the calculation formula from the data source group 20, the calculation formula is expanded and data is substituted into the variables used in the expanded calculation formula to calculate the CO2 emissions of the target product. This makes it possible to appropriately calculate the CO2 emissions using the data acquired from the data source group 20. Note that the target product may be composed of multiple parts, and the variables used in the calculation formula may include, for example, data (e.g., CO2 emissions) of the multiple parts.

[0141] Furthermore, in this embodiment, primary data to be substituted for the variables used in the calculation formula is searched for, and if the primary data is found, the searched primary data is acquired. Also, in this embodiment, if primary data is not found, similar data to be substituted for the variables used in the calculation formula is searched for, and the searched similarity data is acquired. Furthermore, in this embodiment, if similar data is not found, secondary data to be substituted for the variables used in the calculation formula is searched for, and the searched secondary data is acquired. In this embodiment, with this configuration, highly reliable primary data necessary for calculating CO2 emissions is preferentially acquired (collected), and if the highly reliable data is not obtained, it is possible to calculate CO2 emissions by substituting less reliable similar data or secondary data.

[0142] In this embodiment, when similar data is applied to the calculation formula, a reliability (second reliability) lower than the reliability (first reliability) calculated when the primary data is applied is calculated. Also, in this embodiment, when secondary data is applied to the calculation formula, a reliability (third reliability) lower than the reliability (second reliability) calculated when the similar data is applied is calculated.

[0143] Furthermore, the reliability when primary data is applied to the calculation formula may be a different value depending on whether the primary data satisfies predetermined conditions (for example, the first to fourth conditions described above). Furthermore, the reliability when similar data is applied to the calculation formula may be a different value depending on the similarity between the target product and similar products described above.

[0144] Furthermore, in this embodiment, the CO2 emissions and reliability of the target product can be displayed, but in addition to the CO2 emissions and reliability, the type of data applied to the calculation formula to calculate the CO2 emissions (i.e., the data substituted into the variables used in the calculation formula) may also be displayed. This allows the user to easily understand the type of data that forms the basis of the reliability of the CO2 emissions (the type of data used to calculate the CO2 emissions).

[0145] Furthermore, together with the CO2 emissions and reliability, a data source ID for identifying the data source from which the data for calculating the CO2 emissions was obtained may also be displayed. With this configuration, data (e.g., primary data) that is lacking for calculating the CO2 emissions with high reliability becomes clear, and it is possible to provide feedback to the data source group 20 to improve the reliability, for example. Furthermore, it is considered that such a data source ID can be used, for example, as traceability information regarding data collection.

[0146] In this embodiment, it is assumed that the amount of CO2 emitted over the entire life cycle of a product (CFP) is calculated, but this embodiment may also be applied to calculating the amount of CO2 emitted over a part of the life cycle of the product.

[0147] Furthermore, in the present embodiment, the information processing device 10 has been described as including the units 11 to 15 shown in Fig. 1, but the information processing device 10 may have a configuration different from that shown in Fig. 1. Specifically, the information processing device 10 may have a configuration in which some of the units 11 to 15 are arranged externally, or may further include functional units other than the units 11 to 15. Furthermore, although the information processing device 10 according to the present embodiment is assumed to be realized by a single device, it may also be realized by multiple devices.

[0148] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention described in the claims and their equivalents.

[0149] The following additional notes are provided regarding the above-described embodiment. [1] An information processing device comprising a calculation means for outputting the CO2 emissions of a first product calculated by applying data acquired from a data source to a pre-prepared calculation formula, and a reliability calculated based on the type of data applied to the calculation formula. [2] The information processing device according to [1], wherein the data acquired from the data source includes at least one of primary data of the first product, similar data which is primary data of a second product similar to the first product, and secondary data of the first product. [3] applying the data obtained from the data source to the calculation formula includes substituting the data for variables used in the calculation formula; When the calculation means cannot substitute the data acquired from the data source into all of the variables used in the calculation formula, the calculation means expands the calculation formula and calculates the CO2 emissions of the first product by substituting the data acquired from the data source into the variables used in the expanded calculation formula. [1] or [2]. [4] The information processing device according to [3], wherein the data substituted into the variables used in the calculation formula includes data on a plurality of parts that make up the first product. [5] a first acquisition means for searching for the primary data to be substituted into the variables used in the calculation formula, and acquiring the searched primary data when the primary data is found; a second acquisition means for searching for the similar data to be substituted into the variables used in the calculation formula when the primary data is not searched for, and for acquiring the searched similar data when the similar data is searched for; a third acquisition means for searching for the secondary data to be substituted into the variable used in the calculation formula when the similar data is not found, and for acquiring the searched secondary data when the secondary data is found; The information processing device according to any one of [2] to [4], further comprising: [6] The information processing device according to any one of [2] to [5], wherein the calculation means calculates a first reliability when the primary data is applied to the calculation formula, calculates a second reliability lower than the first reliability when the similar data is applied to the calculation formula, and calculates a third reliability lower than the second reliability when the secondary data is applied to the calculation formula. [7] The information processing device according to [6], wherein the first reliability has a different value depending on whether the primary data satisfies a predetermined condition. [8] The information processing device according to [6] or [7], wherein the second reliability has a different value depending on the similarity between the first product and the second product. [9] The information processing device according to any one of [6] to [8], wherein the third reliability is a fixed value.

[10] The information processing device according to any one of [1] to [9], further comprising a display processing means for displaying the CO2 emission amount and the reliability of the first product.

[11] The information processing device according to

[10] , wherein the display processing means further displays a data source ID for identifying the data source from which the data applied to the calculation formula was obtained.

[12] An information processing method comprising: outputting a CO2 emission amount of a first product calculated by applying data acquired from a data source to a pre-prepared calculation formula, and a reliability calculated based on the type of data applied to the calculation formula.

[13] A program for causing a computer to function as a calculation means for outputting the CO2 emissions of a first product calculated by applying data obtained from a data source to a pre-prepared calculation formula, and the reliability calculated based on the type of data applied to the calculation formula. [Explanation of symbols]

[0150] 10...information processing device, 11...storage unit, 12...data acquisition unit, 13...first calculation unit, 14...second calculation unit, 15...display processing unit, 20...data source group, 101...CPU, 102...non-volatile memory, 103...main memory, 104...input device, 105...display device, 106...communication device, 201...product-related data source, 202...peripheral-related data source, 203...secondary data source.

Claims

1. CO2 of the first product calculated by applying data obtained from the data source to a pre-prepared calculation formula ２ An information processing device comprising a calculation means for outputting an emission amount and a reliability calculated based on the type of data applied to the calculation formula.

2. 2. The information processing device according to claim 1, wherein the data acquired from the data source includes at least one of primary data of the first product, similar data which is primary data of a second product similar to the first product, and secondary data of the first product.

3. applying the data obtained from the data source to the calculation formula includes substituting the data for variables used in the calculation formula; When the calculation means cannot substitute data acquired from the data source into all variables used in the calculation formula, the calculation means expands the calculation formula and calculates the CO₂ of the first product by substituting data acquired from the data source into variables used in the expanded calculation formula. ２ Calculate emissions 3. The information processing device according to claim 1.

4. 4. The information processing apparatus according to claim 3, wherein the data substituted into the variables used in the calculation formula includes data on a plurality of parts that make up the first product.

5. a first acquisition means for searching for the primary data to be substituted into the variables used in the calculation formula, and acquiring the searched primary data when the primary data is found; a second acquisition means for searching for the similar data to be substituted into the variables used in the calculation formula when the primary data is not searched for, and for acquiring the searched similar data when the similar data is searched for; a third acquisition means for searching for the secondary data to be substituted into the variable used in the calculation formula when the similar data is not found, and for acquiring the searched secondary data when the secondary data is found; The information processing apparatus according to claim 2, further comprising:

6. 3. The information processing device according to claim 2, wherein the calculation means calculates a first reliability when the primary data is applied to the formula, calculates a second reliability lower than the first reliability when the similar data is applied to the formula, and calculates a third reliability lower than the second reliability when the secondary data is applied to the formula.

7. The information processing device according to claim 6 , wherein the first reliability has a different value depending on whether the primary data satisfies a predetermined condition.

8. The information processing apparatus according to claim 6 , wherein the second reliability has a value that varies depending on the degree of similarity between the first product and the second product.

9. The information processing apparatus according to claim 6 , wherein the third reliability is a fixed value.

10. CO of the first product ２ 3. The information processing apparatus according to claim 1, further comprising a display processing means for displaying the discharge amount and the reliability.

11. 11. The information processing apparatus according to claim 10, wherein the display processing means further displays a data source ID for identifying a data source from which the data applied to the formula was obtained.

12. CO2 of the first product calculated by applying data obtained from the data source to a pre-prepared calculation formula ２ outputting an emission amount and a reliability calculated based on the type of data applied to the formula.

13. The computer calculates the CO2 of the first product by applying the data acquired from the data source to a pre-prepared calculation formula. ２ a program for causing the program to function as a calculation means for outputting an emission amount and a reliability calculated based on the type of data applied to the calculation formula;

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