Data processing device, data processing method, data processing program, and learning device

Abstract

To make it possible to easily generate a data specification for converting raw data into use data.SOLUTION: A specification generation unit 23 applies an application rule 34 including a processing rule 32 of input data 31 to item definition information 35 defining a data item of the input data 31 to generate a data specification 36 indicating processing content for the input data 31. A specification managing unit 24 receives correction to the data specification 36. A rule generation unit 25 adds an additional rule 37 representing the received correction to the application rule 34.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to a technique for converting collected data into a format that is easy to visualize, analyze, or the like. [Background technology]

[0002] Raw data, which is data collected by sensors etc., is not suitable for applications such as visualization or analysis. Therefore, the raw data is converted into usable data, which is data in a format suitable for the application, before being used.

[0003] In this case, a data specification for converting the raw data into the usage data is defined, a conversion program is generated based on the data specification, and the conversion program is applied to the raw data to convert the raw data into the usage data. The burden of creating data specifications and conversion programs is large, making it difficult to respond when the number of types of raw data increases or when the number of changes increases.

[0004] Patent Document 1 describes a technology for converting data based on a meta definition of source data and a meta definition of destination data, which aims to reduce the burden of data conversion. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2011-34246 A Summary of the Invention [Problem to be solved by the invention]

[0006] In the technology described in Patent Document 1, meta definition of the converted data is necessary for data conversion. However, there are cases where the type of data to convert is considered while modifying raw data. In such cases, the meta definition of the converted data is not completed until the conversion work has progressed to a certain extent. For this reason, it is difficult to apply the technology described in Patent Document 1. The present disclosure aims to enable easy generation of data specifications for converting raw data into usable data. [Means for solving the problem]

[0007] The data processing device according to the present disclosure comprises: a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a rule generating unit that adds an additional rule representing a modification accepted by the specification managing unit to the application rules; Equipped with. Effect of the Invention

[0008] In the present disclosure, modifications to the data specifications are accepted, and additional rules representing the modifications are added to the application rules. As a result, when generating new data specifications, the application rules to which the additional rules have been added are used. Therefore, even in cases where raw data is modified while considering what kind of data it should be converted into, it is possible to easily generate data specifications. As a result, it is possible to reduce the burden of generating usage data from raw data. [Brief description of the drawings]

[0009] [Figure 1] 1 is a configuration diagram of a data processing device 10 according to a first embodiment. [Diagram 2] FIG. 2 is an explanatory diagram of the operation of the data processing device 10 according to the first embodiment. [Diagram 3]3 is a flowchart showing the operation of the data processing device 10 according to the first embodiment. [Figure 4] FIG. 3 is an explanatory diagram of item definition information 35 according to the first embodiment. [Diagram 5] FIG. 3 is an explanatory diagram of a data specification 36 according to the first embodiment. [Figure 6] FIG. 2 is an explanatory diagram of a specification management process according to the first embodiment. [Figure 7] FIG. 4 is an explanatory diagram of generation of usage data 41 according to the first embodiment. [Figure 8] 10 is a flowchart showing the operation of the data processing device 10 according to the first modification. [Figure 9] 10 is a flowchart showing the operation of the data processing device 10 according to the second modification. [Figure 10] FIG. 11 is a configuration diagram of a data processing device 10 according to a third modified example. [Figure 11] FIG. 11 is a configuration diagram of a data processing device 10 according to a second embodiment. [Figure 12] FIG. 11 is an explanatory diagram of the operation of the data processing device 10 according to the second embodiment. [Figure 13] 10 is a flowchart showing the operation of the data processing device 10 according to the second embodiment. [Figure 14] FIG. 11 is a diagram showing a registration screen for modeling specifications 39 according to the second embodiment. [Figure 15] FIG. 11 is a configuration diagram of a data processing device 10 according to a third embodiment. [Figure 16] 11 is a flowchart showing the operation of the data processing device 10 according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Embodiment 1 ***Configuration Description*** The configuration of a data processing device 10 according to the first embodiment will be described with reference to FIG. The data processing device 10 is a computer. The data processing device 10 includes the following hardware components: a processor 11, a memory 12, a storage 13, and a communication interface 14. The processor 11 is connected to other hardware components via signal lines and controls the other hardware components.

[0011] The processor 11 is an IC that performs processing. IC is an abbreviation for Integrated Circuit. Specific examples of the processor 11 include a CPU, a DSP, and a GPU. CPU is an abbreviation for Central Processing Unit. DSP is an abbreviation for Digital Signal Processor. GPU is an abbreviation for Graphics Processing Unit.

[0012] The memory 12 is a storage device that temporarily stores data. Specific examples of the memory 12 include SRAM and DRAM. SRAM is an abbreviation for Static Random Access Memory. DRAM is an abbreviation for Dynamic Random Access Memory.

[0013] The storage 13 is a storage device that stores data. A specific example of the storage 13 is an HDD. HDD is an abbreviation for Hard Disk Drive. The storage 13 may also be a portable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. SD is an abbreviation for Secure Digital. DVD is an abbreviation for Digital Versatile Disk.

[0014] The communication interface 14 is an interface for communicating with an external device. Specific examples of the communication interface 14 include Ethernet (registered trademark), USB, and HDMI (registered trademark) ports. USB is an abbreviation for Universal Serial Bus. HDMI is an abbreviation for High-Definition Multimedia Interface.

[0015] The data processing device 10 includes, as functional components, a rule registration unit 21, a profiling unit 22, a specification generation unit 23, a specification management unit 24, a rule generation unit 25, and a code generation unit 26. The functions of the functional components of the data processing device 10 are realized by software. The storage 13 stores a program for realizing the function of each functional component of the data processing device 10. The program is loaded into the memory 12 by the processor 11 and executed by the processor 11. In this way, the function of each functional component of the data processing device 10 is realized.

[0016] 1 shows only one processor 11. However, there may be a plurality of processors 11, and the plurality of processors 11 may cooperate to execute programs that realize the respective functions.

[0017] ***Explanation of Operation*** The operation of the data processing device 10 according to the first embodiment will be described with reference to FIGS. The operation procedure of the data processing device 10 according to the embodiment 1 corresponds to the data processing method according to the embodiment 1. Moreover, the program for realizing the operation of the data processing device 10 according to the embodiment 1 corresponds to the data processing program according to the embodiment 1.

[0018] The overall operation of the data processing device 10 according to the first embodiment will be described with reference to Fig. 2 and Fig. 3. In Fig. 2, the solid arrows indicate the flow of processing, and the dotted arrows indicate the flow of data. (Step S11: Rule registration process) The rule registration unit 21 registers application rules 34 including processing rules 32 for input data 31 and validation rules 33 for determining the validity of the input data 31 .

[0019] The input data 31 is raw data collected by a sensor etc. However, the input data 31 is not limited to raw data, and may be data that has been processed in some way. The processing rules 32 are rules that indicate the processing content of the input data 31, such as standardizing the format of the timestamp, converting the character code, converting the time zone, replacing characters, flattening the data, and converting to a file format suitable for analysis. For example, the processing rule 32 is a rule that "the format of the date and time column shall be unified to the format YYYY-MM-DD HH:MM:SS.fffffffff." Flattening data means that, when data has a hierarchical structure, the hierarchical structure is eliminated to make it into single-level data. The validation rule 33 is a rule that indicates the confirmation content for confirming the validity of the input data 31. A specific example of the validation rule 33 is a check for duplication or missing data in the input data 31. For example, the validation rule 33 is a rule that "items that include an ID are unique." ID is an abbreviation for IDentifier.

[0020] (Step S12: Profiling process) The profiling unit 22 analyzes the input data 31 to identify information such as the schema of the input data 31. As a result, the profiling unit 22 generates item definition information 35. As shown in FIG. 4, the item definition information 35 is information that defines the data items of the input data 31. In other words, the item definition information 35 is information that indicates the item name, type name, and the like for each data item of the input data 31. Specific examples of the type name are string, number, and date. Note that the item definition information 35 may further indicate the presence or absence of null, the maximum, minimum, variance, average, median, and the like.

[0021] (Step S13: Specification generation process) The specification generating unit 23 applies the application rules 34 registered in step S11 to the item definition information 35 identified in step S12 to generate a data specification 36. The data specification 36 indicates the processing content for the input data 31.

[0022] As shown in Fig. 5, suppose that application rule 34 indicates processing rule 32 that "date and time columns should be in the format of YYYY-MM-DD HH:MM:SS.fffffffff" and validation rule 33 that "items containing IDs should be unique." Regarding the processing rule 32, the specification generating unit 23 identifies an item in the date and time format from the data items indicated by the item definition information 35. In Fig. 5, an item "registered_date" is identified as an item in the date and time format from the item name. Then, the specification generating unit 23 sets that the identified item in the date and time format is changed to the YYYY-MM-DD HH:MM:SS.fffffffff format. Regarding the validation rule 33, the specification generating unit 23 identifies an item including an ID from the data items indicated by the item definition information 35. In Fig. 5, an item called "customer_id" is identified as an item including an ID from the item name. Then, the specification generating unit 23 sets that a duplication check is performed on the item including the identified ID.

[0023] (Step S14: Specification management process) The specification management unit 24 accepts modifications to the data specification 36 generated in step S13. Specifically, as shown in Fig. 6, the specification management unit 24 displays the data specification 36 generated in step S13 and allows the user to edit the item name, type name, processing rule, and validation. In this way, the specification management unit 24 accepts modifications to the data specification 36.

[0024] (Step S15: Rule generation process) The rule generation unit 25 adds the additional rule 37 representing the correction received in step S14 to the application rule 34 registered in step S11. Specifically, the rule generation unit 25 extracts common matters from the correction received in step S14 and generalizes them to generate the additional rule 37. In this way, the rule generation unit 25 updates the application rule 34. For example, suppose that multiple items including amount are modified to be changed to int type. In this case, the rule generation unit 25 generates the processing rule 32, which changes the items including amount to int type, as the additional rule 37. Then, the rule generation unit 25 adds this additional rule 37 to the application rule 34 to update the application rule 34.

[0025] (Step S16: Code generation process) The code generating unit 26 generates application code 38 that executes the processing content indicated by the data specification 36 after the correction received in step S14. The application code 38 includes processing code 381 in which the processing content indicated by the processing rules 32 is implemented, and validation code 382 in which the confirmation content indicated by the validation rules 33 is implemented.

[0026] In parallel with the process of step S16, the user creates modeling specifications 39 from the data specifications 36 after the corrections received in step S14. The modeling specifications 39 represent specifications for converting data obtained by executing the processing content indicated by the data specifications 36 on the input data 31 into a data structure indicated by a data model. The data model is a model indicating a data structure such as a star schema and a wide table. Then, the user creates modeling code 40 based on the modeling specifications 39.

[0027] 7, the application code 38 generated in step S16 and the modeling code 40 created by the user are implemented in the code execution unit. As a result, the validation code 382, ​​the processing code 381, and the modeling code 40 are applied in order to the input data 31, and data 41 to be used for analysis or the like is generated. The data processing device 10 may be provided with a code execution unit. In addition, when a problem is found in the input data 31 in the check by the validation code 382, ​​the generation of the usage data 41 is stopped, or a warning is issued while generating the usage data 41. Whether to stop the generation of the usage data 41 or to issue a warning while generating the usage data 41 is specified by the validation rules 33.

[0028] In step S11, the rule registration unit 21 registers the application rule 34 generated in step S15 the previous time the process shown in Fig. 3 was executed, thereby gradually brushing up the application rule 34.

[0029] ***Advantages of the First Embodiment*** As described above, the data processing device 10 according to the first embodiment accepts a correction to the data specification 36, and adds the additional rule 37 representing the correction to the application rule 34. As a result, when a new data specification 36 is generated, the application rule 34 to which the additional rule 37 has been added is used. Therefore, even in cases where raw data is being modified while considering what kind of data it should be converted into, it is possible to easily generate a data specification. As a result, it is possible to reduce the burden of generating usage data from raw data.

[0030] ***Other configurations*** <Variation 1> In the first embodiment, the additional rules 37 generated in step S15 are used when next generating the data specification 36. However, after step S15, the process may be returned to step S13, and the data specification 36 may be regenerated using the additional rules 37.

[0031] This will be specifically described with reference to FIG. The processes from step S21 to step S25 are the same as the processes from step S11 to step S15 in Fig. 3. The process from step S27 is the same as the process from step S16 in Fig. 3.

[0032] (Step S26: Regeneration determination process) The specification management unit 24 receives an input as to whether or not the data specification 36 is to be regenerated. If the specification management unit 24 decides to regenerate the data specification 36, the process returns to step S23. On the other hand, if the specification management unit 24 decides not to regenerate the data specification 36, the process proceeds to step S27.

[0033] When the process returns to step S23, the specification generating unit 23 applies the application rules 34 to which the additional rules 37 have been added in step S25 to the item definition information 35 to regenerate the data specifications 36.

[0034] <Variation 2> In the first modification, the additional rule 37 generated in step S15 was not applied to the previously generated data specification 36. However, the application rule 34 to which the additional rule 37 has been added may be applied to the previously generated data specification 36 to regenerate the data specification 36.

[0035] This will be specifically described with reference to FIG. The processes from step S31 to step S36 are the same as the processes from step S11 to step S16 in Fig. 3. The processes from step S37 onwards are executed with each previously generated data specification 36 as the target data specification 36. It is assumed that for each data specification 36 generated in the past, the contact information of the corresponding user is registered in the data processing device 10. The contact information is an email address or the like.

[0036] (Step S37: Change determination process) The specification management unit 24 determines whether the contents of the target data specification 36 will change when the application rule 34 to which the additional rule 37 has been added in step S35 is applied to the item definition information 35. Specifically, the specification management unit 24 applies the application rules 34 to which the additional rules 37 have been added in step S35 to the original item definition information 35 for the target data specification 36 to generate a new data specification 36. Then, the specification management unit 24 compares the target data specification 36 generated in the past with the new data specification 36. If there is a difference, the specification management unit 24 determines that the content will change. If the content has changed, the specification management unit 24 advances the process to step S38. On the other hand, if the content has not changed, the specification management unit 24 ends the process for the target data specification 36.

[0037] (Step S38: Notification process) The specification management unit 24 notifies the user that the content of the target data specification 36 will change by applying the application rule 34 to which the additional rule 37 has been added. Specifically, the specification management unit 24 sends a message or the like to the user's contact information corresponding to the target data specification 36. Upon receiving the notification, the user determines whether or not to regenerate the data specification 36 by applying the application rule 34 to which the additional rule 37 has been added. If the data specification 36 is to be regenerated, the specification management unit 24 replaces the target data specification 36 with the new data specification 36 generated in step S37.

[0038] <Modification 3> In the first embodiment, each functional component is realized by software. However, as a third modification, each functional component may be realized by hardware. The following describes the third modification, focusing on the differences from the first embodiment.

[0039] The configuration of a data processing device 10 according to the third modification will be described with reference to FIG. When each functional component is realized by hardware, the data processing device 10 includes an electronic circuit 15 instead of the processor 11, the memory 12, and the storage 13. The electronic circuit 15 is a dedicated circuit for realizing the functions of each functional component, the memory 12, and the storage 13.

[0040] The electronic circuit 15 may be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, or an FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array. Each functional component may be realized by one electronic circuit 15, or each functional component may be distributed across multiple electronic circuits 15.

[0041] <Variation 4> As a fourth modification, some of the functional components may be realized by hardware, and other functional components may be realized by software.

[0042] The processor 11, the memory 12, the storage 13, and the electronic circuit 15 are collectively referred to as a processing circuit. In other words, the functions of the respective functional components are realized by the processing circuit.

[0043] Embodiment 2 The second embodiment differs from the first embodiment in that, when the data specification 36 is changed, it is determined whether or not the change affects the modeling specification 39. In the second embodiment, this difference will be described, and the description of the same points will be omitted.

[0044] ***Configuration Description*** The configuration of a data processing device 10 according to the second embodiment will be described with reference to FIG. 1 in that the data processing device 10 includes, as a functional component, an influence determining unit 27. The function of the influence determining unit 27 is realized by software or hardware, like the other functional components.

[0045] ***Explanation of Operation*** The operation of the data processing device 10 according to the second embodiment will be described with reference to FIGS. An operation procedure of the data processing device 10 according to the second embodiment corresponds to a data processing method according to the second embodiment. Moreover, a program for realizing the operation of the data processing device 10 according to the second embodiment corresponds to a data processing program according to the second embodiment.

[0046] The overall operation of the data processing device 10 according to the first embodiment will be described with reference to Fig. 12 and Fig. 13. In Fig. 12, the solid arrows indicate the flow of processing, and the dotted arrows indicate the flow of data.

[0047] It is assumed that when the modeling specifications 39 are created, the modeling specifications 39 are registered in the data processing device 10. For example, the modeling specifications 39 are registered using a registration screen such as that shown in Fig. 14. At this time, the name of the modeling specifications 39 and the contact information of the creator are also registered. The contact information is an email address, etc.

[0048] The processes from step S41 onwards are executed with any of the previously generated data specifications 36 as the target data specifications 36.

[0049] (Step S41: Regeneration process) 3, the target data specification 36 is regenerated. The process of step S15 is also executed, and the application rule 34 is updated.

[0050] (Step S42: Influence determination process) The influence determination unit 27 determines whether or not the regeneration of the data specification 36 in step S41 has an influence on the modeling specification 39 that was created in the past based on the target data specification 36. Specifically, the presence or absence of an impact on the modeling specification 39 is set in advance for each change in the data specification 36. The impact determination unit 27 compares the regenerated data specification 36 with the data specification 36 generated in the past to identify the changes in the data specification 36. Then, the impact determination unit 27 determines whether the identified changes have an impact on the modeling specification 39 in accordance with the setting of the presence or absence of an impact. If there is an impact, the impact determination unit 27 advances the process to step S43. On the other hand, if there is no impact, the impact determination unit 27 advances the process to step S44.

[0051] Changes to the data specifications 36 include, for example, the addition of a column, the deletion of a column, and changes to the validation content. For example, in the case of the addition of a column, there is no impact if the column is not used in the usage data 41, so it can be considered that there is no impact. On the other hand, in the case of the deletion of a column, it can be considered that there is an impact because it is possible that a column used in the usage data 41 has disappeared. In the case of a change in the validation content, there is a possibility that the content of the usage data 41 will change, so it can be considered that there is an impact.

[0052] (Step S43: Impact notification process) The influence determination unit 27 notifies the creator of the modeling specification 39 generated from the target data specification 36 that there is an influence due to the change in the target data specification 36. Then, the creator modifies the modeling specifications 39 in accordance with the changes in the data specifications 36, and modifies the modeling code 40. Then, the modeling specifications 39 are registered in the data processing device 10. Once the modeling specifications 39 are registered, the process proceeds to step S44.

[0053] (Step S44: Code generation process) The code generator 26 generates application code 38 that executes the processing content indicated by the regenerated data specification 36 .

[0054] Then, the application code 38 generated in step S44 and the modeling code 40 modified by the user are implemented in the code execution unit. As a result, the validation code 382, ​​the processing code 381, and the modified modeling code 40 are applied in this order to the input data 31, and usage data 41 to be used for analysis or the like is generated.

[0055] ***Effects of the second embodiment*** As described above, when the data specification 36 is changed, the data processing device 10 according to the second embodiment determines whether or not there is an effect on the modeling specification 39. If there is an effect, the data processing device 10 notifies the creator of the modeling specification 39. This prevents an inconsistency from occurring when the modeling specification 39 and modeling code 40 remain unchanged even though the data specification 36 and application code 38 have been changed.

[0056] Embodiment 3 The third embodiment differs from the first and second embodiments in that a rule generation model that outputs the application rule is generated using the corrections to the data specification 36 as learning data. In the third embodiment, this difference will be explained, and explanations of the same points will be omitted.

[0057] ***Configuration Description*** The configuration of a data processing device 10 according to the third embodiment will be described with reference to FIG. 1 in that the data processing device 10 includes a learning unit 28 as a functional component. The function of the learning unit 28 is realized by software or hardware, like the other functional components. The data processing device 10 equipped with the learning unit 28 is called a learning device.

[0058] ***Explanation of Operation*** The operation of the data processing device 10 according to the third embodiment will be described with reference to FIG. An operation procedure of the data processing device 10 according to the embodiment 3 corresponds to a learning method according to the embodiment 3. Moreover, a program for realizing the operation of the data processing device 10 according to the embodiment 3 corresponds to a learning program according to the embodiment 3.

[0059] (Step S51: Learning data acquisition process) The learning unit 28 acquires the correction accepted in the process of step S14 as learning data.

[0060] (Step S52: Learning process) The learning unit 28 performs machine learning using the learning data acquired in step S51, and generates a rule generation model that outputs the application rule 34. The rule generation model is, for example, a model configured using a neural network.

[0061] In step S15, the additional rules 37 are generated using the rule generation model, and the application rules 34 are updated.

[0062] ***Effects of the Third Embodiment*** As described above, the data processing device 10 according to the third embodiment generates a rule generation model using the received corrections as learning data. This makes it possible to generate appropriate application rules 34 by receiving many corrections.

[0063] In addition, the word "part" in the above description may be read as a "circuit," "step," "procedure," "processing," or "processing circuit."

[0064] Various aspects of the present disclosure are summarized below as appendices. (Appendix 1) a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a rule generating unit that adds an additional rule representing a modification accepted by the specification managing unit to the application rules; A data processing device comprising: (Appendix 2) The specification management unit displays the data specifications and accepts modifications. 2. A data processing device as described in appendix 1. (Appendix 3) The data processing device further comprises: a specification generating section that applies the application rule to the item definition information to generate a data specification indicating a processing content for the input data; 3. The data processing device according to claim 1 or 2, comprising: (Appendix 4) The specification generation unit applies the application rules to which the additional rules have been added to the item definition information to regenerate the data specifications. 4. A data processing device as described in appendix 3. (Appendix 5) The specification generating unit notifies a user when the content of a previously generated data specification changes when the application rule to which the additional rule is added is applied to the item definition information. 4. A data processing device as described in appendix 3. (Appendix 6) The rule generating unit extracts and generalizes common matters from the modifications accepted by the specification managing unit to generate the additional rules. 6. A data processing device according to any one of appendix 1 to 5. (Appendix 7) The application rules include validation rules for determining the validity of the input data, The specification generating unit applies the application rule to the item definition information to generate the data specification indicating the content of a judgment of the validity of the input data. 6. A data processing device according to any one of appendix 3 to 5. (Appendix 8) The data processing device further comprises: an influence determination unit that, when the data specification is changed, determines whether or not there is an influence on a modeling specification generated based on the data specification, the modeling specification representing a specification for converting data obtained by executing a process content indicated by the data specification on the input data into a data structure indicated by a data model; 8. The data processing device according to claim 1, further comprising: (Appendix 9) The data processing device further comprises: a code execution section that executes, on input data, application code indicating processing contents indicated by data specifications generated by applying the application rules to which the additional rules have been added by the rule generation section to the item definition information; 9. The data processing device according to claim 1, further comprising: (Appendix 10) a data specification generated by a computer by applying application rules including processing rules for input data to item definition information that defines data items of the input data, the data specification indicating processing details for the input data being accepted; The method of processing data, wherein the computer adds additional rules representing accepted modifications to the applied rules. (Appendix 11) a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a rule generating unit that adds an additional rule representing a modification accepted by the specification managing unit to the application rules; A data processing program that causes a computer to function as a data processing device that performs the above. (Appendix 12) a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a learning unit that uses the corrections accepted by the specification management unit as learning data to generate a rule generation model that outputs the application rule; A learning device comprising:

[0065] The above describes the embodiments and modifications of the present disclosure. Some of these embodiments and modifications may be combined and implemented. Also, one or some of them may be partially implemented. Note that the present disclosure is not limited to the above embodiments and modifications, and various modifications are possible as necessary. [Explanation of symbols]

[0066] 10 data processing device, 11 processor, 12 memory, 13 storage, 14 communication interface, 15 electronic circuit, 21 rule registration unit, 22 profiling unit, 23 specification generation unit, 24 specification management unit, 25 rule generation unit, 26 code generation unit, 27 impact judgment unit, 31 input data, 32 processing rule, 33 validation rule, 34 application rule, 35 item definition information, 36 data specification, 37 additional rule, 38 application code, 381 processing code, 382 validation code, 39 modeling specification, 40 modeling code, 41 used data.

Claims

1. a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a rule generating unit that adds an additional rule representing a modification accepted by the specification managing unit to the application rules; A data processing device comprising:

2. The specification management unit displays the data specifications and accepts modifications.

2. The data processing device according to claim 1.

3. The data processing device further comprises: a specification generating section that applies the application rule to the item definition information to generate a data specification indicating a processing content for the input data; The data processing device according to claim 1 .

4. The specification generation unit applies the application rules to which the additional rules have been added to the item definition information to regenerate the data specifications.

4. The data processing device according to claim 3.

5. The specification generating unit notifies a user when the content of a previously generated data specification changes when the application rule to which the additional rule is added is applied to the item definition information.

4. The data processing device according to claim 3.

6. The rule generating unit extracts and generalizes common matters from the modifications accepted by the specification managing unit to generate the additional rules.

2. The data processing device according to claim 1.

7. The application rules include validation rules for determining the validity of the input data, The specification generating unit applies the application rule to the item definition information to generate the data specification indicating the content of a judgment of the validity of the input data.

4. The data processing device according to claim 3.

8. The data processing device further comprises: an influence determination unit that, when the data specification is changed, determines whether or not there is an influence on a modeling specification generated based on the data specification, the modeling specification representing a specification for converting data obtained by executing a process content indicated by the data specification on the input data into a data structure indicated by a data model; The data processing device according to claim 1 .

9. The data processing device further comprises: a code execution section that executes, on input data, application code indicating processing contents indicated by data specifications generated by applying the application rules to which the additional rules have been added by the rule generation section to the item definition information; The data processing device according to claim 1 .

10. a data specification generated by a computer by applying application rules including processing rules for input data to item definition information that defines data items of the input data, the data specification indicating processing details for the input data being accepted; The method of processing data, wherein the computer adds additional rules representing accepted modifications to the applied rules.

11. a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a rule generating unit that adds an additional rule representing a modification accepted by the specification managing unit to the application rules; A data processing program that causes a computer to function as a data processing device that performs the above.

12. a specification management unit that receives modifications to a data specification that indicates a processing content for the input data, the data specification being generated by applying an application rule including a processing rule for the input data to item definition information that defines a data item of the input data; and a learning unit that uses the corrections accepted by the specification management unit as learning data to generate a rule generation model that outputs the application rule; A learning device comprising:

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