EP4621696A1

EP4621696A1 - Information processing apparatus, information processing method and storage medium

Info

Publication number: EP4621696A1
Application number: EP25155984.5A
Authority: EP
Inventors: Koji Fujiwara
Original assignee: Toshiba Corp
Current assignee: Toshiba Corp
Priority date: 2024-03-18
Filing date: 2025-02-05
Publication date: 2025-09-24
Also published as: JP2025142813A

Abstract

According to an arrangement, an information processing apparatus (10) includes a processor (101). The processor (101) is configured to output the CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on the type of data applied to the calculation formula.

Description

FIELD

The present disclosure relates to an information processing apparatus, an information processing method and a storage medium.

BACKGROUND

CFP (carbon footprint of products) is an abbreviation for "carbon footprint of product" and refers to a numerical value that is equivalent to the amount of greenhouse gases emitted throughout the entire life cycle of a product, from the procurement of raw materials to disposal and recycling, converted into CO₂ emission amount.
In recent years, for example, it has become important to disclose and share the CFP of a product by displaying the CFP on the product as described above. For this reason, there is a demand for a system that automatically calculates the CFP (that is, CO₂ emission amount) of a product.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an example of a functional configuration of an information processing apparatus according to an arrangement.
FIG. 2 is a diagram showing an example of a hardware configuration of the information processing apparatus.
FIG. 3 is a diagram illustrating an example of a product-related data source.
FIG. 4 is a diagram illustrating an example of a peripheral relevant data source.
FIG. 5 is a diagram illustrating an example of a secondary data source.
FIG. 6 is a flowchart showing an example of a processing procedure of the information processing apparatus.
FIG. 7 is a flowchart showing an example of the processing procedure of a data acquisition process.
FIG. 8 is a flowchart showing an example of a processing procedure for calculating an amount of CO₂ emission amount.
FIG. 9 is a flowchart showing an example of a processing procedure for calculating reliability.
FIG. 10 is a diagram showing an example of an evaluation axis for primary data.
FIG. 11 is a diagram showing an example of a relationship between evaluation results of primary data and reliability.
FIG. 12 is a diagram showing an example of a relationship between evaluation results of similarity data and reliability.
FIG. 13 is a diagram showing an example of how to display the amount of CO₂ emission amount and reliability of a product.
FIG. 14 is a diagram showing another example of how to display the amount of CO₂ emission amount and reliability of a product.

DETAILED DESCRIPTION

According to one arrangement, an information processing apparatus includes a processor. The processor is configured to output the CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on the type of data applied to the calculation formula.
Various arrangement will be described hereinafter with reference to the accompanying drawings.
FIG. 1 is a block diagram showing an example of the functional configuration of an information processing apparatus of this arrangement. The information processing apparatus 10 shown in FIG. 1 is an electronic device (CO₂ emission amount automatic calculation device) configured to be connected to a data source group 20 that manage various data used to calculate the amount of CO₂ emitted during the life cycle of a product (hereinafter referred to as the CO₂ emission amount of the product), and to automatically calculate the CO₂ emission amount of the product based on the data acquired from the data source group 20.
Note that in this arrangement, the CO₂ emission amount of the product calculated by the information processing apparatus 10 includes, for example, the carbon footprint (CFP). Further, the product for which the CO₂ emission amount is calculated in this arrangement includes, for example, equipment such as batteries, but it should suffice if the product is of such a type that emits CO₂ in its life cycle, including manufacturing at a factory and the like.
As shown in FIG. 1, the information processing apparatus 10 includes a storage 11, a data acquisition module 12, a first calculation module 13, a second calculation module 14, and a display processing module 15.
The storage 11 stores the (information of) calculation formula prepared in advance for calculating the CO₂ emission amount of the product described above. In this arrangement, the calculation formula stored in the storage 11 is defined so as to express the CO₂ emission amount using, for example, variables to which data (values) acquired from the (values of) data source group 20 described above are assigned.
The data acquisition module 12 acquires (collects), from the data source group 20, data necessary for calculating the CO₂ emission amount of a product based on the variables (such as the attributes of the data assigned to the variables or the like) used in the formula stored in the storage 11. The data acquired by the data acquisition module 12 is output to the first calculation module 13.
The first calculation module 13 calculates the CO₂ emission amount of the product by applying the data output from the data acquisition module 12 to the calculation formula stored in the storage 11. The CO₂ emission amount of the product calculated by the first calculation module 13 are output to the display processing module 15.
The second calculation module 14 calculates the reliability of the CO₂ emission amount of the product based on the type of data applied to the calculation formula by the first calculation module 13 in order to calculate the CO₂ emission amount of the product. The reliability calculated by the second calculation module 14 is output to the display processing module 15.
The display processing module 15 displays the CO₂ emission amount of the product output from the first calculation module 13 and the reliability output from the second calculation module 14.
FIG. 2 shows an example of the hardware configuration of the information processing apparatus 10. As shown in FIG. 2, the information processing apparatus 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.
The CPU 101 is a hardware processor that controls the operation of each component in the information processing apparatus 10. The CPU 101 may be constituted by a single processor or multiple processors. The CPU 101 executes various programs that are loaded from the nonvolatile memory 102, which is a storage device, to the main memory 103. The programs to be executed by the CPU 101 include an operating system (OS), various application programs and the like.
The input device 104 is a device configured to input instructions and various data from the user, and includes, for example, a mouse, a keyboard and the like. The display device 105 is a device configured to display various data, and includes, for example, a display and the like. The communication device 106 is a device configured to perform communication with an external device (for example, the data source group 20 or the like) by, for example, wired or wireless communication.
In FIG. 2, only the nonvolatile memory 102 and the main memory 103 are shown, but the information processing apparatus 10 may further include other storage devices such as a hard disk drive (HDD) and a solid state drive (SSD).
Further, in this arrangement, the storage 11 shown in FIG. 1 is realized, for example, by the nonvolatile memory 102 shown in FIG. 2 or other storage devices.
Furthermore, in this arrangement, part or all of the data acquisition module 12, the first calculation module 13, the second calculation module 14 and the display processing module 15 shown in FIG. 1 are supposed to be realized by software, that is, by causing the CPU 101 shown in FIG. 2 (that is, the computer of the information processing apparatus 10) to execute a predetermined program. This program may be downloaded to the information processing apparatus 10 via a network, or it may be stored on a storage medium and distributed.
Here, the explanation is provided in connection with such a case where some or all of the modules 12 to 15 are realized by software, but some or all of the modules 12 to 15 may be realized by hardware such as an integrated circuit (IC), or may be realized by a configuration in which software and hardware are combined.
An example of the data source group 20 assumed in this arrangement will now be described. In this arrangement, as described above, the CO₂ emission amount of a product is calculated, and the data source group 20 from which the data necessary for calculating the CO₂ emission amount of the product is acquired includes, for example, a product-related data source, a peripheral relevant data source, and a secondary data source.
First, with reference to FIG. 3, a product-related data source included in the data source group 20 will be explained. A product-related data source 201 shown in FIG. 3 is a data source that manages data (information) related to various products, and include, for example, a part composition data 201a, product data 201b and the like.
Generally, a product (for example, a battery) may be composed of multiple parts, and the part composition data 201a is data that indicates the multiple parts that constitutes the product.
The product data 201b includes, for example, the product number, manufacturing number, type, weight, size, and the CO₂ emission amount (direct emission amount) at the time of manufacture of the product.
Next, with reference to FIG. 4, the peripheral relevant data source included in the data source group 20 will now be explained. The peripheral relevant data source 202 shown in FIG. 4 is a data source that manages data (information) related to the periphery (for example, life cycle) of a product, and contains, for example, procurement data 202a, manufacturing data 202b and the like.
Generally, products are in some cases manufactured by procuring parts from other businesses (other companies) other than the business that manufactures the product (the company itself), and the procurement data 202a is data related to the parts that are procured from other companies in order to manufacture the product, and includes, for example, the CO₂ emission amount of the parts. Note that the CO₂ emission amount of the parts, for example, is equivalent to the amount of CO₂ emitted during the life cycle of the parts.
The manufacturing data 202b is data related to the manufacture (production) of the product, and includes, for example, the amount of CO₂ emission (indirect emission amount) associated with the consumption (use) of energy (for example, electricity, heat, etc.) on the manufacturing line for the product, as well as the number of products manufactured on the manufacturing line, etc.
Next, with reference to FIG. 5, the secondary data source included in the data source group 20 will now be explained. The secondary data source 203 shown in FIG. 5 is a data source that manages secondary data, and includes, for example, emission intensity data 203a.
Generally, the term "emission intensity" refers to the amount of fuel, labor, etc. required to manufacture (produce) a certain amount of product, but in this arrangement, the emission intensity data 203a is data equivalent to an indicator of CO₂ emission amount, and indicates, for example, the amount of CO₂ emission per unit of activity (that is, the amount related to the scale of the activity) of the business operator.
Note that in this arrangement, it is explained that the data source group 20 includes the product-related data source 201, the peripheral relevant data source 202, and the secondary data source 203, but some of the data sources 201 to 203 may be omitted from the data source group 20, and data sources different from the data sources 201 to 203 may be further included.
Further, the data managed in the data source group 20 may include information such as the provider of the data, the date and time of creation, the expiration date and the like.
With reference to the flowchart in FIG. 6, an example of the processing procedure of the information processing apparatus 10 according to this arrangement will be explained.
First, in the information processing apparatus 10, for example, a product for which the CO₂ emission amount is to be calculated is determined from among a plurality of products (hereinafter referred to as a target product) (Step S1). Note that the target product may be specified (indicated) by the user using the input device 104, for example, or it may be predetermined.
When the processing of Step S1 is executed, the data acquisition module 12 executes the processing of acquiring (collecting), from the data source group 20, the data necessary for calculating the CO₂ emission amount of the target product determined in the Step S1 (hereinafter referred to as the data acquisition process) (Step S2). Note that the data acquired in the data acquisition processing includes primary data, similarity data, and secondary data. The primary data, similarity data, and secondary data will be described later.
Next, the first calculation module 13 executes the processing for calculating the CO₂ emission amount of the target product by applying the data acquired in Step S2 to the calculation formula stored in the storage 11 (hereinafter referred to as the CO₂ emission amount calculation process) (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.
Further, the second calculation module 14 executes the process of calculating the reliability of the CO₂ emission amount (hereinafter referred to as the "reliability calculation process") based on the type of data substituted for the variable in Step S3 (that is, the data used to calculate the CO₂ emission amount) (Step S4). In the reliability calculation process, the reliability is calculated according to the view point as to which of the primary data, similarity data, or secondary data was used to calculate the CO₂ emission amount of the target product.
When the processes of Steps S3 and S4 is executed, the display processing module 15 displays the CO₂ emission amount calculated in Step S3 and the reliability calculated in Step S4 on the display device 105 (Step S5).
Here, the explanation is made in connection with the case where the CO₂ emission amount and reliability are displayed on the display device 105, but the CO₂ emission amount and reliability may be transmitted (output) to a terminal device different from the information processing apparatus 10 for display on that terminal device, or may be transmitted (output) to an external server device or the like, for use in other processing.
The data acquisition process, the CO₂ emission amount calculation process, and the reliability calculation process described above will now be explained in detail.
First, with reference to the flowchart in FIG. 7, an example of the processing procedure for the data acquisition process (the processing in Step S2 shown in FIG. 6) will be explained.
In this arrangement, the CO₂ emission amount of the target product is calculated using a calculation formula stored in storage 11, and the calculation formula is equivalent to a formula that expresses the CO₂ emission amount using multiple variables to which data acquired from data source group 20 are substituted. Note that the calculation formula may have a structure that can be expanded, as will be described later in more detail.
The data acquisition module 12 acquires the calculation formula stored in the storage 11 and identifies the multiple variables (the attributes of the data to be substituted for the variables) used in the calculation formula (Step S11).
The data acquisition module 12 acquires data to be substituted for each of the multiple variables specified in Step S11 from the data source group 20.
It is assumed here that the data managed in the data source group 20 include not only data of the business operator (the company itself) that manufactures the target product described above, but also data of other business operators that manufacture other products and the like, and data that is publicly available and the like.
Here, as described above, the data acquired in the data acquisition process includes the primary data, similarity data, and the secondary data. The primary data is data that is directly obtained from the target product or its components, for example by actually measuring the target product or its components. In this arrangement, for example, the data managed by the product-related data source 201 and the peripheral relevant data source 202 included in the data source group 20 correspond to the primary data. The similarity data is data (primary data) obtained directly from a product similar to the target product (hereafter referred to as a "similar product"). The secondary data is existing data that has been prepared in advance and is not obtained from the target product. In this arrangement, for example, the data managed by the secondary data source 203 included in the data source group 20 corresponds to the secondary data.
Of the primary data, similarity data and secondary data described above, for example, it can be said that the primary data is the most reliable data, and therefore it is preferable to calculate the CO₂ emission amount of the target product using the primary data.
For this reason, the data acquisition module 12 searches for the primary data corresponding to the variable specified in Step S11 (primary data that can be substituted for the variable in question) from the primary data described above (for example, data managed in the product-related data source 201 or the peripheral relevant data source 202) (Step S12). The data acquisition module 12 acquires the data searched for in Step S12 from the data source group 20.
The data acquisition module 12 determines whether or not all of the data necessary for calculating CO₂ emission amount has been acquired (Step S13).
When it is determined that all of the data has been acquired (YES in Step S13), the data acquisition module 12 outputs the data acquired by executing the processing of Step S12 to the first calculation module 13, and ends the data acquisition process.
On the other hand, when it is determined that all the data has not been acquired (NO in Step S13), the data acquisition module 12 searches for similarity data corresponding to the variable identified in Step S11 and for which the primary data described above has not been acquired (similarity data that can be substituted for the variable) from the similarity data described above(, for example, data managed in the product-related data source 201 or the peripheral relevant data source 202, or the like) (Step S14).
Here, the similarity data is the primary data obtained from the similar product, and the similar product is identified based on the degree of similarity with respect to the target product. The degree of similarity can be calculated based on attributes that can be considered similar to the target product. Specifically, the attributes that can be considered similar to the target product include, for example, lot numbers and model numbers, and the degree of similarity may be calculated according to the number of attributes that match those of the target product. Further, the similarity may be calculated according to the degree of match of the component configuration (that is, the number of components that match those of the target product). Furthermore, the similarity may be calculated according to whether or not the product is in the same product family as that of the target product (that is, whether or not it is a series product of the target product). Note that the method of calculating the similarity described here is only an example, and the similarity may as well be calculated according to some other method.
In this arrangement, for example, the product having the highest degree of similarity calculated as described above is defined as a similar product, and in Step S14, data corresponding to the variables for which no primary data has been obtained is searched for among the primary data (similarity data) obtained from such similar products. The data acquisition module 12 acquires the data searched for in Step S14 from the data source group 20.
Incidentally, in the case where the similarity data is data from some other company, the labels assigned to the attributes defined in the data of the company may differ from that of the data used in the other company. Then, it may not be possible to search for the similarity data. But, in this case, for example, an identifier of semantic information can be used to associate the data of the company and the data of the other company with each other, which have different labels assigned to the attributes thereof. In this way, the similarity data can be searched.
The data acquisition module 12 determines whether or not all of the data necessary for calculating the CO₂ emission amount has been acquired (Step S15).
When it is determined that all of the data has been acquired (YES in Step S15), the data acquisition module 12 outputs the data acquired by executing the processes of Steps S12 and S14 to the first calculation module 13, and ends the data acquisition process.
On the other hand, when it is determined that all of the data has not been acquired (NO in Step S15), the data acquisition module 12 searches for secondary data (secondary data that can be substituted for the variable) that corresponds to the variable specified in Step S11 and for which the above-described primary data and similarity data have not been acquired, from among the above-described secondary data (for example, data managed in the secondary data source 203, etc.) (Step S16). The data acquisition module 12 acquires the data searched in Step S16 from the data source group 20.
When the processing of Step S16 is executed, the data acquisition module 12 outputs the data acquired by executing the processing of steps S12, S14, and S16 to the first calculation module 13, and ends the data acquisition process.
Note here that the data output from the data acquisition module 12 to the first calculation module 13 as a result of the processing shown in FIG. 7 includes 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. In addition, when the data output from the data acquisition module 12 to the first calculation module 13 is similarity data, it is assumed that the data type information attached to the data further include the degree of similarity between the target product and the similar product. With such data type information, it is possible to identify whether the data output from the data acquisition module 12 to the first calculation module 13 is primary data, similarity data, or secondary data.
Further, when multiple primary data are searched in Step S12, for example, these multiple primary data may be presented to the user, so as to let the user select the primary data to be used for calculating the CO₂ emission amount. Here, the contents of Step S12 are explained, but the same applies to Steps S14 and S16.
According to the data acquisition process described above, when it is not possible to acquire (search) all the data used to calculate the CO₂ emission amount of the target product from the primary data, similarity data or secondary data may be acquired as a substitute for the primary data.
With reference to the flowchart in FIG. 8, an example of the processing procedure for the CO₂ emission amount calculation process (the processing of Step S3 shown in FIG. 6) will be explained.
As described above, the formula stored in storage 11 corresponds to the starting point for calculating CO₂ emission amount. For convenience, the variables used in such a formula are referred to as "first variables" below.
The first calculation module 13 acquires the calculation formula stored in the storage 11. The first calculation module 13 substitutes the data output from the data acquisition module 12 (that is, the data acquired in the data acquisition process) for the multiple first variables used in the calculation formula acquired from the storage 11 (Step S21).
When the processing in Step S21 is executed, it is determined whether or not data has been assigned to all of the first variables used in the calculation formula (Step S22).
When it is determined that data has been substituted for all of the first variables (YES in Step S22), the first calculation module 13 calculates the CO₂ emission amount of the target product according to the calculation formula in which data has been substituted for the first variables (Step S23).
The CO₂ emission amount calculated in Step S23 is output from the first calculation module 13 to the display processing module 15.
The above-explained calculation formula expresses CO₂ emission amount using multiple first variables, but in some cases, the first variables can be expressed using a formula that uses, for example, other variables (hereinafter referred to as second variables).
According to this, when it is determined that data has not been substituted for all of the first variables (in other words, there are first variables for which data cannot be substituted) (NO in Step S22), the first calculation module 13 expands the calculation formula (Step S24). Note that in Step S24, such processing is executed as to replace the first variable for which data has not been substituted with a formula using multiple second variables, for example.
Once the processing in Step S24 is executed, the operation is returned to Step S21 and the processing is repeated. In this case, the processing of substituting data for the second variables described above is executed in Step S21. Further, when it is determined in Step S22 that data have been substituted for all the second variables, the CO₂ emission amount of the target product is calculated according to the calculation formula in which the data have been substituted for the second variables.
Note that here, such a case is assumed that the data to be substituted for the second variables used in the expanded calculation formula have already been obtained in the data acquisition process as data necessary for calculating the CO₂ emission amount. But, the data to be substituted for the second variable may be obtained from the data source group 20 after the processing of Step S24 has been executed.
According to the CO₂ emission calculation process described above, even in the case where the data acquired in the data acquisition process cannot be substituted for all of the variables used in the calculation formula (in other words, the CO₂ emission amount cannot be calculated using the calculation formula), it is still possible to calculate the CO₂ emission amount by expanding the calculation formula.
When the CO₂ emission calculation process is executed, the data used to calculate the CO₂ emission amount of the target product (that is, the data substituted into the variables) is output (notified) from the first calculation module 13 to the second calculation module 14.
Further, in FIG. 8, a case where the CO₂ emission amount can be calculated by expanding the calculation formula is illustrated. But when, for example, data for all variables cannot be substituted even if the calculation formula is expanded, a notification may be made to the user that it is not possible to calculate the CO₂ emission amount of the target product due to a lack of data (that is, an error).
Here, a specific example of the calculation formula used in this arrangement will be explained. Here, it is assumed that the calculation formula (starting formula) is "CO₂ emission amount = Scope 1 + Scope 2 + Scope 3".
Scope 1 is a variable that expresses the amount of CO₂ (direct emission amount) emitted directly by the business operator (the company itself) during the manufacturing of the target product. Scope 2 is a variable that expresses the amount of CO₂ emission (indirect emission amount) associated with the consumption of energy during the manufacturing of the target product. Scope 3 is a variable that expresses the amount of CO₂ emission by related business operators (other companies) during the life cycle of the target product. In other words, Scope 3 is a variable that expresses the amount of CO₂ emitted indirectly by suppliers and the like, excluding Scopes 1 and 2. For example, according to the Greenhouse Gas (GHG) Protocol, Scope 3 is divided into 15 categories, including procurement, transportation and the like. When the periods before and after the manufacturing of the target product are referred to as upstream and downstream, categories 1 to 8 of the 15 categories correspond to the upstream, and categories 9 to 15 correspond to the downstream.
Further, it is assumed here that Scope 2 can be represented by a formula that uses a variable that expresses the amount of CO₂ emission associated with energy consumption in the manufacturing line and a variable that expresses the number of products in the manufacturing line. More specifically, Scope 2 is assumed to be represented by a formula of "CO₂ emission amount associated with energy consumption in the manufacturing line / number of products in the manufacturing line".
Furthermore, it is assumed that Scope 3 can be expressed by a formula that uses variables expressing the CO₂ emission amounts of respective parts procured to manufacture the target product. Here, let us suppose that the parts procured to manufacture the target product are the first component to the third component, then Scope 3 can be expressed by a formula of "CO₂ emission amount from first component + CO₂ emission amount from second component + CO₂ emission amount from third component". Not that the fact that the target product is constituted by the first component to the third component can be ascertained from the part composition data 201a contained in the product-related data source 201.
In other words, the above-provided calculation formula "CO₂ emission amount = Scope 1 + Scope 2 + Scope 3" can be expanded into a calculation formula using the variables "Scope 1", "CO₂ emission amount associated with energy consumption in the manufacturing line", "number of products in the manufacturing line", "CO₂ emission amount of the first component", "CO₂ emission amount of the second component" and "CO₂ emission amount of the third component".
In this case, in the data acquisition process, for example, the product data 201b is acquired from the product-related data source 201 as the data corresponding to the variable "Scope 1". Further, in the data acquisition process, the data corresponding to the variable "Scope 2" (that is, data that can be directly substituted into the variable) is not acquired, but as the data corresponding to the variables "CO₂ emission amount associated with energy consumption in the manufacturing line" and "number of products manufactured in the manufacturing line" used in the expression representing the variable "Scope 2", for example, the manufacturing data 202b is acquired from the peripheral relevant data source 202. Furthermore, in the data acquisition process, the data corresponding to the variable "Scope 3" (that is, data that can be directly substituted into the variable) is not acquired, but, for example, the procurement data 202a is acquired from the peripheral relevant data source 202 as the data corresponding to the variables "CO₂ emission amount of the first component", "CO₂ emission amount of the second component", and "CO₂ emission amount of the third component" used in the formula representing the "Scope 3".
In this case, the data (values thereof) acquired as described above are substituted into the respective variables, and thus the CO₂ emission amount of the target product can be calculated. Specifically, when the value to be substituted into the variable "Scope 1 (direct emission amount)" is 100, the value to be substituted into the variable "CO₂ emission amount associated with energy consumption in the production line" is 1000, the value to be substituted to the variable "number of products manufactured in the production line" is 20, the value to be substituted to the variable "CO₂ emission amount of the first component" is 20, the value to be substituted to the variable "CO₂ emission amount of the second component" is 30, and the value to be substituted to the variable "CO₂ emission amount of the third component" is 40, then the CO₂ emission amount of the target product is calculated as follows: 100 (Scope 1) + 50 (Scope 2 = 1000 / 20) + 90 (Scope 3 = 20 + 30 + 09) = 240.
Note that the calculation formula explained here is only an example, and some other formula may as well be used to calculate the CO₂ emission amount of the target product. Specifically, when calculating the CO₂ emission amount of the target product over its life cycle as described above, a more complex calculation formula may as well be used.
Next, with reference to the flowchart of FIG. 9, an example of the processing procedure for the reliability calculation process (the processing of Step S4 shown in FIG. 6) will be explained.
First, the second calculation module 14 acquires the data output from the first calculation module 13 as described above. The data thus acquired by the second calculation module 14 is the data substituted for the variables in the calculation formula in the CO₂ emission calculation process described above. The second calculation module 14 evaluates (acquires) the reliability of the data thus substituted for the variables (data corresponding to the variables) (Step S31). Hereinafter, the data to be evaluated in Step S31 will be referred to as the evaluation target data for convenience.
In Step S31, the reliability of the evaluation target data is evaluated based on the type of evaluation target data. Specifically, the type of the evaluation target data can be identified based on the data type information attached to the evaluation target data. Note here that the reliability of the evaluation target data is defined (evaluated) as 100 when the evaluation target data is primary data, the reliability of the evaluation target data is evaluated as 50 when the evaluation target data is similarity data, and the reliability of the evaluation target data is evaluated as 0 when the evaluation target data is secondary data. Note that in this arrangement, the case where the data to be evaluated (data substituted into variables) is secondary data is assumed to include cases where values calculated using, for example, emission intensity data corresponding to the secondary data are substituted into variables.
When the processing of Step S31 is executed, it is determined whether or not the processing of Step S31 has been executed for all the data substituted into the variables used in the calculation formula (Step S32).
When it is determined that the processing has not been executed for all the data (NO in Step S32), the operation is returned to Step S31 and the processing is repeated. In other words, in the reliability calculation processing, the processing in Step S31 is repeated until the reliabilities of all the data substituted into the variables used in the calculation formula are obtained.
When it is determined that processing has been executed for all the data (that is, the reliabilities of all the data have been obtained) (YES in Step S32), the second calculation module 14 calculates the reliability of the CO₂ emission amount of the target product based on the reliabilities of all of the data (Step S33).
Now, an example of the processing in Step S33 will be explained. When it is assumed that the calculation formula is "CO₂ emission amount = Scope 1 + Scope 2 + Scope 3" provided above, then, in Step S33, the reliability of each of the variables "Scope 1", "Scope 2" and "Scope 3" used in the calculation formula can be calculated, and the average of the calculated reliability values can be calculated as the reliability of the CO₂ emission amount of the target product.
Here, let us assume, for example, that the evaluation target data substituted into the variable "Scope 1 (direct emission amount)" is primary data. In this case, for example, the reliability of the evaluation target data substituted into "Scope 1 (direct emission amount)" is 100, and the reliability of the evaluation target data is taken as the reliability of the variable "Scope 1".
Further, let us assume, for example, that the variable "Scope 2" is expressed by a formula using the variables "CO₂ emission amount associated with energy consumption in the production line" and "number of products in the production line", that the evaluation target data substituted into the variable "CO₂ emission amount associated with energy consumption in the production line" is similarity data, and that the evaluation target data substituted into the variable "number of products in the production line" is primary data. In this case, for example, the reliability of the evaluation target data substituted into the variable "CO₂ emission amount associated with energy consumption in the production line" is 50, and the reliability of the evaluation target data substituted into the variable "number of products in the production line" is 100, and the average value of the reliability of the two evaluation target data (that is, 75) is taken as the reliability of the variable "Scope 2".
Furthermore, let us assume, for example, the variable "Scope 3" is expressed by a formula using the variables "CO₂ emission amount of the first component", "CO₂ emission amount of the second component" and "CO₂ emission amount of the third component", and the evaluation target data substituted into the variable "CO₂ emission amount of the first component" is the primary data, the evaluation target data substituted into the variable "CO₂ emission amount of the second component" is the similarity data, and the evaluation target data substituted into the variable "CO₂ emission amount of the third component" is the secondary data. In this case, the reliability of the evaluation target data substituted into the variable "CO₂ emission amount of the first component" is 100, the reliability of the evaluation target data substituted into the variable "CO₂ emission amount of the second component" is 50, and the reliability of the evaluation target data substituted into the variable "CO₂ emission amount of the third component" is 0, and the average value of the reliability of the three evaluation target data (that is, 50) is taken as the reliability of the variable "Scope 3".
According to this, the reliability of the CO₂ emission amount of the target product calculated according to the calculation formula using the variables "Scope 1", "Scope 2" and "Scope 3" is calculated to be 75, which is the average of the reliability of each of the variables "Scope 1", "Scope 2" and "Scope 3".
As described above, the reliability calculated in Step S33 is output from the second calculation module 14 to the display processing module 15, and the reliability calculation process is finished.
In the case where the reliability calculation process described above is executed, a high reliability can be obtained by calculation when the primary data is applied to the calculation formula, a reliability lower than this reliability is obtained when the similarity data is applied to the calculation formula, and a reliability even lower than the reliability is obtained when the secondary data is applied to the calculation formula.
Note here that the method for calculating the reliability of CO₂ emission amount for the target product described here is only an example, and the reliability of the CO₂ emission amount for the target product may be calculated using some other methods. Further, it is explained here that the reliability of the CO₂ emission amount for the target product can be calculated mainly using the average value of the reliability of the evaluation target data, but the reliability of CO₂ emission amount for the target product may be calculated using a weighted average value of the reliability of the evaluation target data.
Further, the explained is made here on the assumption that the reliability of the evaluation target data is set to 100 when the evaluation target data is primary data, the reliability of the evaluation target data is 50 when the evaluation target data is similarity data, and the reliability of the evaluation target data is 0 when the evaluation target data is secondary data, but the reliability of these data may be set to different values, respectively.
Specifically, for example, when the evaluation target data is primary data, the reliability of the evaluation target data may as well be further evaluated by some other evaluation axis (perspective).
FIG. 10 shows an example of an evaluation axis for primary data. Here, an evaluation axis related to data quality is assumed, and the example shown in FIG. 10 shows that the evaluation target data is evaluated from the perspectives of "provider" and "time".
Specifically, from the perspective of "provider", the reliability of the evaluation target data is evaluated based on, for example, the following conditions, that is, the provider of the evaluation target data is certified as being able to provide data for calculating the CO₂ emission amount (hereinafter referred to as the first condition), and the provider of the evaluation target data has a track record of transactions with the business operator (the company itself) that manufactures the target product (hereinafter referred to as the second condition).
Further, from the perspective of "time", the reliability of the evaluation target data is evaluated based on the following conditions, that is, the validity period set for the evaluation target data has not expired (that is, the evaluation target data is data that is within the validity period) (hereinafter referred to as the third condition) and the creation date and time set for the evaluation target data (the date and time when the evaluation target data was created) is within six months (hereinafter referred to as the fourth condition).
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 out of the first to fourth conditions that have been predetermined described above, as the evaluation axis for the primary data.
Here, FIG. 11 shows an example of the correspondence relationship (correspondence table) between the number of conditions satisfied by the evaluation target data (that is, the evaluation result of the primary data) and the reliability of the evaluation target data. Note here that symbols "o4" to "o0" in the evaluation results for the primary data in FIG. 11 each represent the number of conditions satisfied by the evaluation target data described above.
According to FIG. 11, the reliability of the evaluation target data that satisfies all of the first to fourth conditions described above is represented by 100. Further, FIG. 11 indicates that the reliability of the evaluation target data that satisfies three of the first to fourth conditions is 80, the reliability of the evaluation target data that satisfies two of the first to fourth conditions is 60, the reliability of the evaluation target data that satisfies one of the first to fourth conditions is 40, and the reliability of the evaluation target data that does not satisfy any of the first to fourth conditions is 20.
In other words, the example shown in FIG. 11 indicates that the reliability of the evaluation target data (primary data) takes a different value depending on whether or not the evaluation target data satisfies the first to fourth conditions in each respective case.
Note that the correspondence relationship between the evaluation results of the primary data and the reliability shown in FIG. 11 is only an example, and the reliability corresponding to each of the evaluation results may take a different value.
Further, here the explanation is made on the assumption that the reliability of the evaluation target data, which is the primary data is evaluated on an evaluation axis based on the perspectives of "provider" and "time", but the reliability of the evaluation target data may as well be evaluated on a different evaluation axis or on more evaluation axes. Moreover, the evaluation axis for evaluating the reliability of the evaluation target data (primary data) should only be set based on the perspective that contributes to the determination of the reliability (a perspective that is useful for determining the reliability).
Here, the explanation is made in connection with the case where the evaluation target data is primary data, but when the evaluation target data is similarity data, the reliability of the evaluation target data may be further evaluated based on, for example, the similarity between the target product and the similar product from which the evaluation target data (similarity data) was obtained (hereinafter referred to as the similarity of the evaluation target data). In other words, the reliability of the evaluation target data (similarity data) can be determined according to the similarity of the evaluation target data. It is assumed here that the similarity of the evaluation target data is included in data type information attached to the evaluation target data, for example, and is obtained from the data type information. As the similarity of the evaluation target data (the similarity between the target product and the similar product) has been explained above, a detailed explanation thereof is omitted here.
Here, FIG. 12 shows the correspondence relationship (correspondence table) between the similarity of the evaluation target data (that is, the evaluation results of similarity data) and the reliability of the evaluation target data. In FIG. 12, symbols "Δ4" to "Δ0" in the evaluation results of similarity data indicate the similarity of the evaluation target data (the range thereof). In this case, it is assumed that the range of possible similarity values is 0 to 100 (that is, the minimum similarity value is 0 and the maximum similarity value is 100).
According to FIG. 12, the symbol "Δ4" indicates that the similarity range is, for example, 90 to 100, and when the similarity of the evaluation target data falls within the range indicated by "Δ4", the reliability of the evaluation target data is supposed to be 90.
Further, according to FIG. 12, the symbol "Δ3" indicates that the range of similarity is, for example, 80 to 90, and when the similarity of the evaluation target data falls within the range indicated by "Δ3", the reliability of the evaluation target data is supposed to be 70.
Furthermore, according to FIG. 12, the symbol "Δ2" indicates that the range of similarity is, for example, 70 to 80, and when the similarity of the evaluation target data falls within the range indicated by "Δ2", the reliability of the evaluation target data is supposed to be 50.
Moreover, according to FIG. 12, the symbol "Δ1" indicates that the range of similarity is, for example, 60 to 70, and when the similarity of the evaluation target data falls within the range indicated by "Δ1", the reliability of the evaluation target data is supposed to be 30.
Furthermore, according to FIG. 12, the symbol "Δ0" indicates that the range of similarity is, for example, 50 to 60, and when the similarity of the evaluation target data falls within the range indicated by "Δ0", the reliability of the evaluation target data is supposed to be 10. Here, it is assumed that evaluation target data having a similarity of less than 50 is not used in the calculation of the CO₂ emission amount, but the symbol "Δ0" may indicate a range of similarity of 0 to 60.
That is, the example shown in FIG. 12 indicates that the reliability of the evaluation target data (similarity data) takes different values depending on the similarity between the target product and similar products.
Note that the correspondence relationship between the evaluation results of the similarity data and the reliability shown in FIG. 12 is only an example, and the reliability corresponding to the evaluation results may have a different value in each case.
Further, the explanation is made on the assumption that the reliability of the evaluation target data, which is similarity data, is evaluated in terms of similarity, but the reliability of the evaluation target data (similarity data) may as well be further evaluated from a different perspective.
Here, the case where the evaluation target data is primary data and similarity data is explained, but in the case where the evaluation target data is secondary data, the reliability of the evaluation target data can be set to a fixed value such as 0 as described above. Note that the reliability of the evaluation target data, which is secondary data, can be a fixed value other than 0 (for example, 40), or it can be further evaluated from other perspectives (that is, it can be a different value depending on the evaluation results).
According to the reliability calculation process described above, the reliability of the CO₂ emission amount of the target product calculated according to the formula can be obtained according to the type of data (primary data, similarity data, and secondary data) substituted for the variables used in the formula.
Further, 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 amount calculation process (that is, it is a process related to the CO₂ emission amount calculation process). Therefore, the reliability calculation process may be incorporated into the CO₂ emission amount calculation process and executed. Specifically, the reliability calculation process may be executed as part of the CO₂ emission calculation process, or it may be executed in parallel with the CO₂ emission calculation process.
Note that in this arrangement, the CO₂ emission amount of the target product calculated by executing the CO₂ emission calculation process described above and the reliability calculated by executing the reliability calculation process are displayed.
In this arrangement, at least the CO₂ emission amount and reliability of the target product should only be displayed, but it is considered to be more useful for the user if the CO₂ emission amount and reliability of the target product are displayed together with other information.
An example of how the CO₂ emission amount and reliability of the target product are displayed in this arrangement, will be explained with reference to FIG. 13.
In the example shown in FIG. 13, the CO₂ emission amount and reliability of the target product are displayed in a tabular format. It is assumed here that the CO₂ emission amount of the target product is calculated according to the calculation formula "Scope 1 + Scope 2 + Scope 3", for example.
FIG. 13 shows that the target product is constituted by the first to third components. It is assumed here that the CO₂ emission amount of each of the first to third components can be calculated in a manner similar to that of the case of the CO₂ emission amount of the target product, for example, according to the calculation formula "Scope 1 + Scope 2 + Scope 3".
In the example shown in FIG. 13, the first component is constituted by three parts and two parts c. Here, it is assumed that the CO₂ emission amount (unit CO₂ emission amount) of the part a is 10, and the CO₂ emission amount (unit CO₂ emission amount) of the part c is 30. In this case, the value that is substituted for the variable "Scope 3" used in the formula for calculating the CO₂ emission amount of the first component is obtained by: 10 × 3 + 30 × 2 = 90. Although a detailed explanation thereof will be omitted, in FIG. 13, when the value substituted for the variable "Scope 1" used in the formula for calculating the CO₂ emission amount of the first component is 10, and the value substituted for the variable "Scope 2" used in the formula is 20, the CO₂ emission amount of the first component will be given by: 10 + 20 + 90 = 120.
The second component is constituted by one part b and one part c. Here, it is assumed that the CO₂ emission amount of the part b is 20 and the CO₂ emission amount of the part c is 30. In this case, the value substituted for the variable "Scope 3" used in the formula for calculating the CO₂ emission amount of the second component is given by: 20 + 30 = 50. Although a detailed explanation thereof will be omitted, in FIG. 13, it is assumed that when the value substituted for the variable "Scope 1" used in the formula for calculating the CO₂ emission amount of the second component is 20, and the value substituted for the variable "Scope 2" used in the formula is 40, the CO₂ emission amount of the second component is given by: 20 + 40 + 50 = 110.
Further, the third component is constituted by one part a, one part c, one part d and one part e. Here, it is assumed that the CO₂ emission amount of the part a is 10, the CO₂ emission amount of the part c is 30, the CO₂ emission amount of the part d is 40, and the CO₂ emission amount of the part e is 50. In this case, the value to be substituted for the variable "Scope 3" used in the formula for calculating the CO₂ emission amount of the third component is given by: 10 + 30 + 40 + 50 = 130. Although a detailed explanation thereof will be omitted, in FIG. 13, when the value substituted for the variable "Scope 1" used in the formula for calculating the CO₂ emission amount of the third component is 30, and the value substituted for the variable "Scope 2" used in the formula is 60, then the CO₂ emission amount of the third component is given by: 30 + 60 + 130 = 220.
Note that the total value of the CO₂ emission amounts for the first to third components (120 + 110 + 220 = 450) described above is equivalent to the value to be substituted for "Scope 3" used in the formula for calculating the CO₂ emission amount of the target product. Although a detailed explanation thereof will be omitted, when the value substituted for the variable "Scope 1" used in the formula for calculating the CO₂ emission amount of the target product is 50, and the value substituted for the variable "Scope 2" used in the formula is 100, then the CO₂ emission amount of the target product is given by: 50 + 100 + 450 = 600.
As described above, in the example shown in FIG. 13, the user can easily grasp, in addition to the CO₂ emission amount of the target product, the values substituted for the variables used in the calculation formula to calculate the CO₂ emission amount of the target product, the CO₂ emission amount of each component that constitutes the target product and the like.
Further, in the example shown in FIG. 13, the reliability is displayed in relation to the target product and the components that constitute the target product (the CO₂ emission amount thereof). Note that in FIG. 13, the average reliability calculated by using the average value of the reliabilities of the data used to calculate the CO₂ emission amount and the weighted average reliability calculated using the weighted average reliability of the data are displayed, but only one of the average reliability and the weighted average reliability may be displayed.
In the example shown in FIG. 13, the data source ID, reliability symbol, and the type of the data (primary data, similarity data, or secondary data) are also displayed to identify the data source from which the data substituted for the variables used in the calculation formula for calculating the CO₂ emission amount are obtained (collected). Note that the reliability symbol corresponds to each of "o4" to "o0" shown in FIG. 11 and each of "Δ4" to "Δ0" shown in FIG. 12.
Further, when the reliability of the data (primary data) substituted for the variables used in the calculation formula as described above is determined according to the number of conditions satisfied by the data, information as to whether or not the data satisfies each of the first to fourth conditions described above may be further displayed. Note that although it is omitted in FIG. 13, when the reliability of the data (similarity data) substituted for the variable used in the calculation formula is determined according to the similarity of the data (similarity between the target product and similar products), the information on the similarity of the data may be further displayed.
Note that the explanation is made in connection with the case where the CO₂ emission amount and reliability of the target product are displayed in a tabular format as shown in FIG. 13, but the CO₂ emission amount and reliability of the target product may as well be displayed in, for example, a format that arranges the parts that constitute the target product in layers (in a tree structure format).
Further, FIG. 13 shows an example of displaying relatively detailed information, but as shown in FIG. 14, for example, only "component composition", "total", "average reliability", "weighted average reliability" and "reliability symbol" may be displayed.
As described above, the information processing apparatus 10 of this arrangement outputs the CO₂ emission amount of the target product (first product) calculated by applying the data acquired from a data source to a calculation formula prepared in advance, and the reliability calculated based on the type of data applied to the calculation formula. In this arrangement, with such a configuration, it is possible to automatically calculate the CO₂ emission amount of the target product.
Here, for example, it is regarded as important to disclose and share the CO₂ emission amount (CFP) of a product over its life cycle. However, the data used to calculate the CO₂ emission amount is scattered over various data sources, and it is difficult to collect data from such a group of data sources. Further, when the data required to calculate the CO₂ emission amount is not available, the CO₂ emission amount cannot be calculated out.
However, in this arrangement, the data acquired from the data source group 20 includes at least one of the primary data of the target product, the similarity data, which is the primary data of a similar product (the second product) similar to the target product, and the secondary data of the target product. That is, in this arrangement, even if, for example, the data necessary to calculate the CO₂ emission amount is not included in the primary data, the similarity data or secondary data can be automatically collected to calculate the CO₂ emission amount.
Further, in this arrangement, it is considered that the primary data of the target product is highly reliable, and the data other than the primary data of the target product (similarity data and secondary data) is less reliable than the primary data of the target product, and therefore the reliability according to the type of data used to calculate the CO₂ emission amount is defined, and the reliability is output together with the CO₂ emission amount. Accordingly, the user can easily grasp whether high or low is the reliability of the CO₂ emission amount of the target product calculated by the information processing apparatus 10, and it becomes possible to appropriately use the CO₂ emission amount according to the reliability.
Note that in this arrangement, the CO₂ emission amount of the target product is calculated by substituting the data (values thereof) obtained from the data source group 20 into the variables used in the calculation formula. However, when the data to be substituted for all the variables used in the calculation formula cannot be obtained from the data source group 20, the calculation formula is expanded and the CO₂ emission amount of the target product is calculated out by substituting the data into the variables used in the expanded calculation formula. In this way, the CO₂ emission amount can be calculated appropriately by using the data acquired from the data source group 20. Note that the target product may in some cases be constituted by multiple components, and the variables used in the calculation formula may include data (for example, CO₂ emission amount) for these multiple components.
Further, in this arrangement, the primary data to be substituted for the variable used in the calculation formula is searched, and when the primary data is searched, the primary data thus searched is acquired. Further, in this arrangement, when the primary data is not found, the similarity data to be substituted for the variable used in the calculation formula is searched, and the similarity data thus searched is acquired. Furthermore, in this arrangement, when the similarity data is not found, the secondary data to be substituted for the variable used in the calculation formula is searched and the secondary data thus searched is obtained. In this arrangement, with this structure, the primary data having a high level of reliability that is necessary for calculating the CO₂ emission amount is obtained (collected) on a priority basis. Here, when such highly reliable data is not obtained, it is possible to calculate the CO₂ emission amount by the substitution by low-reliability similarity data or secondary data.
Note that in this arrangement, when the similarity data is applied to the calculation formula, it is assumed that a lower reliability (second reliability) than the reliability calculated when the primary data is applied (first reliability) is calculated. Further, when the secondary data is applied to the calculation formula in this arrangement, it is assumed that a lower reliability (third reliability) than the reliability calculated when the similarity data is applied (second reliability) is calculated.
Further, the reliability in the case where the primary data is applied to the calculation formula may be a different value depending on whether or not the primary data satisfies the predetermined conditions (for example, the first to fourth conditions described above). Furthermore, the reliability in the case where the similarity data is applied to the calculation formula may be a different value depending on the similarity between the target product and the similar product described above.
Moreover, in this arrangement, the CO₂ emission amount and reliability of the target product can be displayed, but in addition to the CO₂ emission amount and reliability, the type of data (that is, the data substituted for the variables used in the calculation formula) applied to the calculation formula to calculate the CO₂ emission amount may be further displayed. With this configuration, the user can easily grasp the type of data (that is, the type of data used to calculate the CO₂ emission amount) that forms the basis for the reliability of the CO₂ emission amount.
Furthermore, the data source ID for identifying the data source from which the data used to calculate the relevant CO₂ emission amount was obtained may be displayed together with the CO₂ emission amount and reliability. With such a configuration, the data that is lacking (for example, primary data) for calculating highly reliable CO₂ emission amount can be identified, and feedback can be provided to, for example, the data source group 20 to improve the reliability. Moreover, it is considered that such data source IDs can be used as the information for traceability regarding the collection of data, for example.
Note that in this arrangement, it is assumed that the amount of CO₂ emission (CFP) of a product over the entire life cycle is calculated, but this arrangement may as well be applied to cases where the amount of CO₂ emission of the product in part of the life cycle is calculated.
In this arrangement, the explanation is made on the assumption that the information processing apparatus 10 includes the storage 11 and the modules 12 to 15 shown in FIG. 1, but the information processing apparatus 10 may have a configuration that differs from the configuration shown in FIG. 1. Specifically, the information processing apparatus 10 may have a configuration in which some of the storage 11 and the modules 12 to 15 are disposed outside, or a configuration that further includes functional parts other than the modules 12 to 15. Further, it is assumed that the information processing apparatus 10 of this arrangement is realized by a single device, but it may as well be realized by a plurality of devices.
While certain arrangements have been described, these arrangements have been presented by way of example only, and are not intended to limit the scope of the claims. Indeed, the apparatuses, methods and storage mediums described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the apparatuses, methods and storage mediums described herein may be made.
The arrangements as described above include clauses below.

Clause 1

An information processing apparatus characterized by including a processor configured to output a CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on a type of the data applied to the calculation formula.

Clause 2

The information processing apparatus of clause 1, characterized in that data acquired from the data source includes at least one of primary data of the first product, similarity data, which is the primary data of a second product similar to the first product, and secondary data of the first product.

Clause 3

The information processing apparatus of clause 1 or 2, characterized in that

the applying of the data acquired from the data source to the calculation formula includes substituting the data for variables used in the calculation formula, and
the processor is configured to calculate the CO₂ emission amount of the first product by, when the data obtained from the data source cannot be substituted for all of the variables used in the calculation formula, expanding the calculation formula, and substituting the data obtained from the data source for the variables used in the expanded calculation formula.

Clause 4

The information processing apparatus of clause 3, characterized in that the data substituted for the variables used in the calculation formula includes data for a plurality of components that constitute the first product.

Clause 5

The information processing apparatus of any one of clauses 2 to 4, characterized in that the processor is configured to:

search the primary data to be substituted for the variables used in the calculation formula and acquire the primary data when the primary data is searched;
search the similarity data to be substituted for the variable used in the calculation formula when the primary data is not found, and acquire the similarity data when the similarity data is searched;
search the secondary data to be substituted for the variable used in the calculation formula when the secondary data is not found, and acquire the secondary data when the secondary data is searched.

Clause 6

The information processing apparatus of any one of clauses 2 to 5, characterized in that the processor is configured to calculate a first reliability when the primary data is applied to the calculation formula, calculate a second reliability lower than the first reliability when the similarity data is applied to the calculation formula, and calculate a third reliability lower than the second reliability when the secondary data is applied to the calculation formula.

Clause 7

The information processing apparatus of clause 6, characterized in that the first reliability is a value which takes a different value depending on whether or not the primary data satisfies a predetermined condition.

Clause 8

The information processing apparatus of clause 6 or 7, characterized in that the second reliability is a value which takes a different value depending on the similarity between the first product and the second product.

Clause 9

The information processing apparatus of any one of clauses 6 to 8, characterized in that a third reliability is a fixed value.

Clause 10

The information processing apparatus of any one of clauses 1 to 9, characterized in that
the processor is configured to display the CO₂ emission amount of the first product and the reliability.

Clause 11

The information processing apparatus of clause 10, characterized in that the processor is configured to display a data source ID for identifying the data source from which the data applied to the calculation formula is obtained.

Clause 12

An information processing method characterized by including:
outputting a CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on a type of data applied to the calculation formula.

Clause 13

A non-transitory computer-readable storage medium having stored thereon a program which is executed by a computer, the program including instructions capable of causing the computer to execute functions of:
outputting a CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance and a reliability calculated based on a type of data applied to the calculation formula.

Claims

An information processing apparatus (10) characterized by comprising:
a processor (101) configured to output a CO₂ emission amount of a first product calculated by applying data acquired from a data source (20) to a calculation formula prepared in advance, and a reliability calculated based on a type of the data applied to the calculation formula.
The information processing apparatus (10) of claim 1, characterized in that
data acquired from the data source (20) includes at least one of primary data of the first product, similarity data, which is the primary data of a second product similar to the first product, and secondary data of the first product.
The information processing apparatus (10) of claim 1 or 2, characterized in that
the applying of the data acquired from the data source (20) to the calculation formula includes substituting the data for variables used in the calculation formula, and

the processor (101) is configured to calculate the CO₂ emission amount of the first product by, when the data obtained from the data source (20) cannot be substituted for all of the variables used in the calculation formula, expanding the calculation formula, and substituting the data obtained from the data source (20) for the variables used in the expanded calculation formula.
The information processing apparatus (10) of claim 3, characterized in that
the data substituted for the variables used in the calculation formula includes data for a plurality of components that constitute the first product.
The information processing apparatus (10) of any one of claims 2 to 4, characterized in that the processor (101) is configured to:
search the primary data to be substituted for the variables used in the calculation formula and acquire the primary data when the primary data is searched;

search the similarity data to be substituted for the variable used in the calculation formula when the primary data is not found, and acquire the similarity data when the similarity data is searched;

search the secondary data to be substituted for the variable used in the calculation formula when the secondary data is not found, and acquire the secondary data when the secondary data is searched.
The information processing apparatus (10) of any one of claims 2 to 5, characterized in that
the processor (101) is configured to calculate a first reliability when the primary data is applied to the calculation formula, calculate a second reliability lower than the first reliability when the similarity data is applied to the calculation formula, and calculate a third reliability lower than the second reliability when the secondary data is applied to the calculation formula.
The information processing apparatus (10) of claim 6, characterized in that
the first reliability is a value which takes a different value depending on whether or not the primary data satisfies a predetermined condition.
The information processing apparatus (10) of claim 6 or 7, characterized in that
the second reliability is a value which takes a different value depending on the similarity between the first product and the second product.
The information processing apparatus (10) of any one of claims 6 to 8, characterized in that a third reliability is a fixed value.
The information processing apparatus (10) of any one of claims 1 to 9, characterized in that
the processor (101) is configured to display the CO₂ emission amount of the first product and the reliability.
The information processing apparatus (10) of Claim 10, characterized in that
the processor (101) is configured to display a data source ID for identifying the data source from which the data applied to the calculation formula is obtained.
An information processing method characterized by comprising:
outputting a CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on a type of data applied to the calculation formula.
A non-transitory computer-readable storage medium having stored thereon a program which is executed by a computer, the program comprising instructions capable of causing the computer to execute functions of:
outputting a CO₂ emission amount of a first product calculated by applying data acquired from a data source to a calculation formula prepared in advance, and a reliability calculated based on a type of data applied to the calculation formula.