WO2022137526A1 - Information processing program, information processing method, and information processing device - Google Patents

Abstract

The present invention makes it possible to evaluate the quality of data appropriately.　In the present invention, a storage unit stores history information indicating a history of input data and output data for each of a plurality of pieces of software. A processing unit extracts information of first input data, which serves as a start point of data processing executed by the plurality of pieces of software, on the basis of the history information stored in the storage unit. The processing unit evaluates the quality of first output data output through the data processing in accordance with a comparison of whether or not the information of the first input data matches the information of predetermined data input by a user.

Description

Information processing programs, information processing methods and information processing equipment

The present invention relates to an information processing program, an information processing method, and an information processing device.

In information processing systems, a large amount of data is processed by various software products. A series of data processing may be realized by combining multiple software products.
For example, a method of managing the flow of data processed in an information processing system by using data lineage information representing a relationship between the data has been proposed. In the proposed method, the relationship between the physical data element and the business data element is based on the first data lineage that represents the relationship between the physical data elements and the second data lineage that represents the relationship between the business data elements. Is detected.

It should be noted that data including a value indicating the strength of the received signal when the base station device receives the signal from the terminal device or the degree of error is acquired, and the quality index of the received signal of the base station device is derived based on the acquired data. There is a proposal for a control device to be used.

International Publication No. 2018/089633 Japanese Unexamined Patent Publication No. 2019-110497

When a series of data processing is realized by combining a plurality of software products, the problem is whether or not the data output by the data processing is generated through the process intended by the user. For example, if the source of the data to be processed is not intended, the reliability of the result of data processing is lowered. However, a quality control mechanism for data output through a series of data processing by such a plurality of software products has not been established.

In one aspect, it is an object of the present invention to provide an information processing program, an information processing method and an information processing apparatus for appropriately evaluating the quality of data.

In one aspect, an information processing program is provided. The information processing program extracts to the computer the information of the first input data which is the starting point of data processing by the plurality of software based on the history information indicating the history of the input data and the output data for each of the plurality of software. Processing that evaluates the quality of the first output data output by the data processing according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user. Let it run.

Further, in one aspect, an information processing method is provided.
Further, in one object, an information processing device is provided.

In one aspect, the quality of the data can be adequately evaluated.
The above and other objects, features and advantages of the invention will be apparent by the following description in connection with the accompanying drawings representing preferred embodiments of the invention.

It is a figure explaining the information processing apparatus of 1st Embodiment. It is a figure which shows the system example of the 2nd Embodiment. It is a figure which shows the hardware example of an information processing apparatus. It is a figure which shows the example of software in an information processing system. It is a figure which shows the functional example of an information processing apparatus. It is a figure which shows the example of the history information. It is a figure which shows the example of the provenance evaluation. It is a figure which shows the example of the security evaluation. It is a figure which shows the example of access authority prediction. It is a figure which shows the example of the up-to-dateness evaluation. It is a figure which shows the example of the comprehensive evaluation result table. It is a figure which shows the 1st example of the evaluation result screen. It is a figure which shows the 2nd example of the evaluation result screen. It is a flowchart which shows the processing example of an information processing apparatus. It is a flowchart which shows the history evaluation example. It is a flowchart which shows the security evaluation example. It is a flowchart which shows the latestness evaluation example. It is a flowchart which shows the evaluation result display control example.

Hereinafter, the present embodiment will be described with reference to the drawings.
[First Embodiment]
The first embodiment will be described.

FIG. 1 is a diagram illustrating an information processing apparatus according to the first embodiment.
The information processing device 10 has a storage unit 11 and a processing unit 12. The storage unit 11 may be a volatile storage device such as a RAM (Random Access Memory) or a non-volatile storage device such as an HDD (Hard Disk Drive) or a flash memory. The processing unit 12 may include a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and the like. The processing unit 12 may be a processor that executes a program. The "processor" here may include a set of a plurality of processors (multiprocessor).

The storage unit 11 stores the history information 20 indicating the history of the input data and the output data for each of the plurality of software. Provenance information 20 is obtained, for example, from an information processing system (not shown) that executes a plurality of software. For example, the information processing apparatus 10 may be connected to the information processing system via a network, acquire the history information 20 from the information processing system via the network, and store the history information 20 in the storage unit 11. Alternatively, the history information 20 may be input to the information processing apparatus 10 by the user and stored in the storage unit 11. Provenance information 20 may be data lineage information showing the history of data source, data processing, shaping, and the like.

The processing unit 12 extracts the information of the first input data which is the starting point of the data processing by the plurality of software based on the history information 20 stored in the storage unit 11. The processing unit 12 determines the quality of the first output data output by the data processing according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user. Make an evaluation.

As the information of the first input data, identification information such as a data name of the first input data, identification information of the data storage unit 41 storing the first input data, and the like can be considered. The identification information of the data storage unit 41 may be, for example, the DB name or directory path of the DB (Database) corresponding to the data storage unit 41, or the identification name of the storage device that provides the data storage unit 41. The information of the predetermined data is information about the data assumed as the input data by the user, such as the identification information of the data assumed as the original input by the user, the identification information of the data storage unit for storing the data, and the like. Can be considered.

For example, the history information 20 includes information related to data processing by software 31 and 32 executed in the information processing system. The data used for the data processing are data d1, d2, d3. For example, in the history information 20, the data d1 stored in the data storage unit 41 is input to the software 31, the data d2 is generated by the processing p1 of the software 31 based on the data d1, and the data d2 is stored in the data storage unit 42. Indicates that it will be stored.

Further, in the history information 20, the data d2 stored in the data storage unit 42 is input to the software 32, the data d3 is generated by the processing p2 of the software 32 based on the data d2, and the data d3 is stored in the data storage unit 43. Indicates that it will be stored. The data storage units 41, 42, and 43 may be realized by a storage device included in the information processing system, or may be realized by a storage device external to the information processing system.

For example, the processing unit 12 evaluates the quality of data as follows based on the history information 20. First, the processing unit 12 identifies the data d3 output by the data processing by the software 31 and 32 based on the history information 20. Then, the processing unit 12 specifies that the generation source data of the data d3 is the data d2 based on the history information 20. Further, the processing unit 12 specifies that the generation source data of the data d2 is the data d1 based on the history information 20.

The processing unit 12 detects that there is no source data in the previous stage of the data d1 based on the history information 20. Therefore, the processing unit 12 specifies that the input data at the start point of the data processing that outputs the data d3 is the data d1. Therefore, the processing unit 12 extracts the information of the data d1 as the information of the input data of the starting point for the data d3 based on the history information 20 (step S1). The data d1 is an example of the first input data.

The processing unit 12 evaluates the quality of the data d3 according to the comparison of whether or not the information of the data d1 matches the information of the predetermined data (step S2). For example, the processing unit 12 may compare whether or not the identification information of the data d1 matches the identification information of the predetermined data assumed by the user. In addition to or instead of comparing the data identification information, the processing unit 12 uses the identification information of the data storage unit 41 in which the data d1 is stored to be the identification information of the predetermined data storage unit assumed by the user. You may make a comparison as to whether or not they match.

When the information of the data d1 matches the information of the predetermined data, the processing unit 12 evaluates the quality of the data d3 higher than the case where the information does not match. For example, the processing unit 12 may provide the data d3 with a quality index value indicating that the larger the value, the higher the quality. In this case, the processing unit 12 adds a predetermined value to the index value when the information of the data d1 matches the information of the predetermined data, and prevents addition to the index value when the information does not match.

When comparing a plurality of items included in the information of the data d1 with a plurality of items included in the information of the predetermined data, the processing unit 12 sets the index value according to whether or not the plurality of items completely match. A predetermined value may be added, or the value to be added may be changed according to the number of matching items.

Further, the processing unit 12 may extract other data in addition to the data d1 as the input data of the starting point for the data d3. In that case, the quality of the data d3 is evaluated according to the comparison of whether or not the information of each of the input data of the plurality of start points matches the information of the predetermined data. The information of the predetermined data may include information of a plurality of data assumed by the user.

Note that the processing unit 12 may obtain the quality evaluation value by the point deduction method instead of the point addition method. Further, the quality index value may indicate that the smaller the value, the higher the quality. In that case, the above "addition" may be read as "subtraction".

According to the information processing apparatus 10, the information of the first input data which is the starting point of the data processing by the plurality of software is extracted based on the history information indicating the history of the input data and the output data for each of the plurality of software. .. The quality of the first output data output by the data processing is evaluated according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user.

This makes it possible to appropriately evaluate the quality of the data.
In the information processing system, various softwares are executed, and in a series of data processing by a plurality of softwares, the quality of the data output by the data processing changes depending on whether or not the data intended by the user is processed. For example, when performing data processing such as analysis, if input data not intended by the user is processed, the input data may contain unnecessary information or incorrect information, resulting in data processing. Is more likely to be wrong, which reduces the reliability of the result.

Therefore, the information processing apparatus 10 identifies the data d1 at the start point of data processing by the plurality of software based on the history information 20, and confirms whether or not the data d1 is the input intended by the user. The quality of the data d3 output by the processing can be appropriately evaluated.

The processing unit 12 can perform the above quality evaluation on a plurality of output data including the data d3 output by the information processing system. The processing unit 12 may display the result of quality evaluation for each of the plurality of output data including the data d3 on the display device. For example, the processing unit 12 may display a data flow diagram from the input data of the start point corresponding to each output data to the output data on the display device for each output data. In this case, the processing unit 12 may highlight the data flow diagram relating to the output data whose quality is evaluated to be lower than the standard. In this way, it is possible to support the user in reviewing the data flow in the information processing system.

Hereinafter, the function of the information processing apparatus 10 will be described in detail by showing a more specific example.
[Second Embodiment]
Next, a second embodiment will be described.

FIG. 2 is a diagram showing a system example of the second embodiment.
The system of the second embodiment includes an information processing system 50 and an information processing device 100. The information processing system 50 and the information processing apparatus 100 are connected to the network 60. The network 60 may be the Internet, a WAN (Wide Area Network), or a LAN (Local Area Network).

The information processing system 50 executes various software and executes various data processing in which a plurality of software are combined. The software may be referred to as a product or a software product. The information processing system 50 includes server devices 200, 300, .... Server devices 200, 300, ... Each is a server computer that executes software. The server devices 200, 300, ... Each are connected to the internal network of the information processing system 50. Each of the server devices 200, 300, ... may execute a plurality of software. In addition, software executed on one server device may be linked with other software executed on another server device. The information processing system 50 may include a storage device that stores data and is used for exchanging data between server devices.

The information processing device 100 is a server computer that utilizes data lineage information in the information processing system 50 to perform data quality evaluation across a plurality of software in the information processing system 50. The information processing device 100 is an example of the information processing device 10 of the first embodiment.

FIG. 3 is a diagram showing a hardware example of the information processing device.
The information processing device 100 includes a CPU 101, a RAM 102, an HDD 103, a GPU (Graphics Processing Unit) 104, an input interface 105, a medium reader 106, and a NIC (Network Interface Card) 107. The CPU 101 is an example of the processing unit 12 of the first embodiment. The RAM 102 or the HDD 103 is an example of the storage unit 11 of the first embodiment.

The CPU 101 is a processor that executes a program instruction. The CPU 101 loads at least a part of the programs and data stored in the HDD 103 into the RAM 102 and executes the program. The CPU 101 may include a plurality of processor cores. Further, the information processing device 100 may have a plurality of processors. The processes described below may be performed in parallel using multiple processors or processor cores. Also, a set of multiple processors may be referred to as a "multiprocessor" or simply a "processor".

The RAM 102 is a volatile semiconductor memory that temporarily stores a program executed by the CPU 101 and data used by the CPU 101 for calculation. The information processing apparatus 100 may include a type of memory other than the RAM, or may include a plurality of memories.

The HDD 103 is a non-volatile storage device that stores software programs such as an OS (Operating System), middleware, and application software, and data. The information processing device 100 may be provided with other types of storage devices such as a flash memory and an SSD (Solid State Drive), or may be provided with a plurality of non-volatile storage devices.

The GPU 104 outputs an image to the display 61 connected to the information processing apparatus 100 in accordance with a command from the CPU 101. As the display 61, any kind of display such as a CRT (Cathode RayTube) display, a liquid crystal display (LCD: Liquid Crystal Display), a plasma display, and an organic EL (OEL: Organic Electro-Luminescence) display can be used.

The input interface 105 acquires an input signal from the input device 62 connected to the information processing device 100 and outputs the input signal to the CPU 101. As the input device 62, a pointing device such as a mouse, a touch panel, a touch pad, a trackball, a keyboard, a remote controller, a button switch, or the like can be used. Further, a plurality of types of input devices may be connected to the information processing apparatus 100.

The medium reader 106 is a reading device that reads programs and data recorded on the recording medium 63. As the recording medium 63, for example, a magnetic disk, an optical disk, a magneto-optical disk (MO: Magneto-Optical disk), a semiconductor memory, or the like can be used. The magnetic disk includes a flexible disk (FD: Flexible Disk) and an HDD. Optical discs include CDs (Compact Discs) and DVDs (Digital Versatile Discs).

The medium reader 106 copies, for example, a program or data read from the recording medium 63 to another recording medium such as the RAM 102 or the HDD 103. The read program is executed by, for example, the CPU 101. The recording medium 63 may be a portable recording medium and may be used for distribution of programs and data. Further, the recording medium 63 and the HDD 103 may be referred to as a computer-readable recording medium.

NIC107 is an interface that is connected to the network 60 and communicates with other computers via the network 60. The NIC 107 is connected to a communication device such as a switch or a router by a cable.

The server devices 200, 300, ... Are also realized by the same hardware as the information processing device 100.
FIG. 4 is a diagram showing an example of software in an information processing system.

The information processing system 50 includes data acquisition software 51, data processing software 52, data storage unit 53, and data shaping software 54. The software mentioned here is an example, and the information processing system 50 may have other software that performs other processing in place of or in addition to at least a part of these software. .. The data storage unit 53 is realized by a storage device included in the information processing system 50.

For example, the data acquisition software 51, the data processing software 52, and the data shaping software 54 acquire the data processed by the software in the previous stage in this order, and output the processing result data.

The data acquisition software 51 acquires the input data A1 from the input data storage unit 70 and provides it to the data processing software 52. The data processing software 52 generates the accumulated data A2 from the input data A1 by the data processing processing s1. The data processing software 52 stores the stored data A2 in the data storage unit 53.

Further, the data acquisition software 51 acquires the input data B1 from the input data storage unit 71 and provides it to the data processing software 52. The data processing software 52 generates the accumulated data B2 from the input data B1 by the data processing processing s2. The data processing software 52 stores the stored data B2 in the data storage unit 53. The number of input data used to generate a certain stored data may be plural.

The data shaping software 54 acquires the stored data A2 and B2 stored in the data storage unit 53. The data shaping software 54 generates the utilization data A3 from the accumulated data A2 by the data shaping process s3, and stores the utilization data A3 in the utilization data storage unit 80. The data shaping software 54 generates the utilization data AB from the accumulated data A2 and B2 by the data shaping process s4, and stores the utilization data AB in the utilization data storage unit 80. The data shaping software 54 generates the utilization data AB from the accumulated data A2 and B2 by the data shaping process s5, and stores the utilization data AB in the utilization data storage unit 80. It can be said that the utilization data is output data that is finally output by a series of data processing.

At least a part of the input data storage units 70 and 71 and the utilization data storage unit 80 may be realized by the storage device included in the information processing system 50. Further, at least a part of the input data storage units 70 and 71 and the utilization data storage unit 80 may be realized by a storage device external to the information processing system 50 and accessible from the information processing system 50 via the network 60. .. Further, since the "accumulated data" is intermediate data for creating "utilization data" from "input data", it can also be called "intermediate data". Further, the "data" may be a unit of information called a file, a table, a record, or the like.

FIG. 5 is a diagram showing a functional example of the information processing apparatus.
The information processing apparatus 100 includes a storage unit 110, a history information analysis unit 130, an evaluation unit 140, and a display control unit 150. The storage area of the RAM 102 or the HDD 103 is used for the storage unit 110. The history information analysis unit 130, the evaluation unit 140, and the display control unit 150 are realized by executing the program stored in the RAM 102 by the CPU 101.

The storage unit 110 stores information used for processing of the history information analysis unit 130, the evaluation unit 140, and the display control unit 150. The information stored in the storage unit 110 includes the history information. Provenance information is acquired from the information processing system 50 by the user and stored in the storage unit 110. Alternatively, the history information may be created by analyzing the query execution log acquired from the information processing system 50 by the history information analysis unit 130 and stored in the storage unit 110.

The history information analysis unit 130 analyzes the history information stored in the storage unit 110. The history information analysis unit 130 has an input data extraction unit 131, an access authority prediction unit 132, and a delay time calculation unit 133.

The input data extraction unit 131 extracts the input data of the start point of the data processing realized by the plurality of software in the information processing system 50 based on the history information, and stores the information of the input data of the start point in the storage unit 110. .. The input data extraction unit 131 extracts the input data of the starting point corresponding to the utilization data by tracing back the generation flow of the utilization data based on the history information.

The access authority prediction unit 132 predicts the access authority of the accumulated data generated based on the input data and the utilization data generated based on the accumulated data based on the history information and the information of the input data of the start point. .. The access authority prediction unit 132 stores the predicted access authority information in the storage unit 110. The access authority prediction unit 132 specifies processing contents such as data processing and data shaping based on the history information. The access authority prediction unit 132 predicts the access authority of the data output by the data processing or the data shaping based on the access authority of the data which is the input of the data processing or the data shaping and the specified processing content.

The delay time calculation unit 133 calculates the delay time from input to output in a series of data processing based on the history information and the data generation log processed by the information processing system 50, and stores the calculated delay time information. It is stored in the unit 110.

The evaluation unit 140 evaluates the quality of the data generated by the data processing using the plurality of software in the information processing system 50 based on the analysis result by the history information analysis unit 130. The evaluation unit 140 evaluates the quality of data according to the following three evaluation types.

The first evaluation type is data history. The evaluation unit 140 evaluates the data history based on the information of the input data of the starting point extracted by the input data extraction unit 131. Specifically, the evaluation unit 140 evaluates the data history based on whether or not the input data of the starting point matches the data intended by the user.

The second evaluation type is security. The evaluation unit 140 evaluates the security of the data based on the prediction result of the access authority by the access authority prediction unit 132. Specifically, the evaluation unit 140 determines whether or not the access authority of the data generated by the information processing system 50 is an appropriate access authority predicted from the access authority of the data from which the data is generated. Evaluate the security of.

The third evaluation type is up-to-date. The evaluation unit 140 evaluates the latestness of the data based on the data generation delay time calculated by the delay time calculation unit 133. Specifically, the evaluation unit 140 evaluates the up-to-dateness of the data based on whether or not the data generated by the information processing system 50 is generated within an allowable delay time from the generation of the generation source data.

The evaluation unit 140 gives evaluation values for each evaluation type of data history, security, and up-to-dateness. The evaluation value is an index showing the degree of high quality. The larger the evaluation value, the higher the quality, and the smaller the evaluation value, the lower the quality. A predetermined value such as "1" may be set as an upper limit for the evaluation value for each evaluation type. The evaluation unit 140 stores the evaluation value assigned to each data for each evaluation type in the storage unit 110. Further, the evaluation unit 140 performs a comprehensive evaluation of the utilization data based on the evaluation value for each effect item for each data, and stores the result of the comprehensive evaluation in the storage unit 110. The result of the comprehensive evaluation of the utilization data is also used as the result of the evaluation for the data processing that generated the utilization data.

The display control unit 150 displays the evaluation result by the evaluation unit 140 on the display 61, or transmits the evaluation result to another computer via the network 60. The display control unit 150 outputs a data flow diagram in the information processing system 50, and controls the display mode of the icon indicating the data in the data flow diagram according to the evaluation value of the data. For example, the display control unit 150 distinguishes and displays data having an evaluation value higher than the reference and data having an evaluation value lower than the reference. Further, the display control unit 150 controls to narrow down the display to the data flow corresponding to the icon designated by the user among the plurality of data flows included in the data flow diagram.

FIG. 6 is a diagram showing an example of history information.
Provenance information 111 is stored in the storage unit 110 in advance. In the example of the history information 111, a JSON (JavaScript Object Notation) format is shown as the data format, but other data formats may be used. JAVASCRIPT is a registered trademark.

The history information 111 records the history of data processed by a plurality of software in the information processing system 50. As an example, FIG. 6 shows a portion of the history information 111 showing that the accumulated data “data-A4” is aggregated by the data aggregation software and the utilization data “data-A5” is output.

The value "XXX_script1" of the variable "typeName" indicates that the processing type of the data aggregation is a script generated using a predetermined script language such as Python (registered trademark). "XXX" may represent the name of the script language or the like. The variable name "createdBy" and the value "create-user" indicate that the name of the user who created the corresponding script is "create-user".

The value "XXX_Aggression application" of the variable "attributes.qualifiedName" indicates that the qualified name of the corresponding software is "XXX_Aggression application".

The value "Aggression application" of the variable "description" indicates that the processing content of the corresponding software is "Aggression application", that is, data aggregation.

The value "sample_user" of the variable "attributes.run_user" indicates that the name of the execution user of the corresponding data aggregation is "sample_user".

The value "sample_server" of the variable "attributes.server" indicates that the name of the execution server that executes the corresponding data aggregation software is "sample_server".

The value "data-A4" of the variable "attributes.inputs.name" indicates that the name of the input data for the data aggregation is "data-A4".
The value "hdfs_path" of the variable "attributes.inputs.typeName" indicates that the input data type is "hdfs_path". In addition, hdfs is an abbreviation for Hadoop (registered trademark) Distributed File System.

For example, the information of the storage unit of the acquisition source of the accumulated data "data-A4" may be included in the value of the variable "attributes.imputs.name" or included in the value of the variable "attributes.imputs.typeName". You may.

The value "data-A5" of the variable "attributes.outputs.name" indicates that the name of the output data corresponding to the data aggregation for the accumulated data "data-A4" is "data-A5".

The value "hdfs_path" of the variable "attributes.outputs.typeName" indicates that the output data type is "hdfs_path".
For example, the information in the storage unit of the output destination of the utilization data "data-A5" may be included in the value of the variable "attributes.outputs.name" or included in the value of the variable "attributes.outputs.typeName". You may.

In the history information 111, information indicating the history of the processed data is recorded by the same data structure for the processing of other software.
Next, a method of evaluating data based on the history information 111 will be described. First, the evaluation of the data history, that is, the history evaluation will be described. In the provenance evaluation, the output data is evaluated based on the information of the input data of the starting point for the data processing.

FIG. 7 is a diagram showing an example of provenance evaluation.
For example, the history information 111 includes information indicating the history from the input data A1 to the utilization data A3. Further, the history information 111 includes information indicating the history from the stored data By stored in the data storage unit 53a to the utilization data Bz stored in the utilization data storage unit 81. The history information 111 indicates that the utilization data Bz is generated by the data shaping process s6 of the data shaping software 54 for the stored data By.

The user-owned input data list 112 is input to the information processing apparatus 100 by the user and stored in the storage unit 110. The user-possessed input data list 112 shows information of data assumed by the user as input data of a start point of data processing. For example, the user-owned input data list 112 includes data names and acquisition source items. The data name is the name of the data. The acquisition source is the name of the storage unit of the acquisition source of the data. For example, "DB_A1" is the name of the input data storage unit 70.

The input data extraction unit 131 generates an input data list 113 for the user corresponding to the user possessed input data list 112 based on the history information 111. The input data list 113 shows information on the input data of the starting point in the data processing used by the user. The input data extraction unit 131 acquires the identification information of the user corresponding to the user-owned input data list 112. The input data extraction unit 131 identifies a process (for example, "description") in which the identification information of the corresponding user is recorded as an execution user (for example, "run_user") from the history information 111. The history information 111 may be information including only the history of data related to data processing used by the user. In this case, the input data extraction unit 131 can omit the process of distinguishing the provenance between the corresponding user and another user.

The input data extraction unit 131 specifies, for example, the history from the input data A1 to the utilization data A3 by tracing the input data and the output data of the process specified for the corresponding user in order from the input data to the output data. do. Similarly, the input data extraction unit 131 specifies the history from the accumulated data By to the inflection data Bz. Note that FIG. 7 omits the illustration of the history of other data for the corresponding user. Here, with respect to a certain process, the direction from the input data to the output data is the forward direction, and the direction from the output data to the input data is the opposite direction.

The input data extraction unit 131 extracts the input data of the starting point used for obtaining the output data based on the history of the data related to the corresponding user extracted from the history information 111, and generates the input data list 113. The input data list 113 is stored in the storage unit 110. It can be said that the input data list 113 is a list of input data of the starting point specified by the input data extraction unit 131.

For example, the input data extraction unit 131 specifies the input data A1 of the starting point used to obtain the utilization data A3 by tracing the history from the utilization data A3 in the opposite direction. The data that ends when traced in the reverse direction, that is, the input corresponding to the data does not exist in the history information 111, and the data that cannot be traced in the reverse direction further corresponds to the input data of the start point. Further, the input data extraction unit 131 specifies the input data By of the starting point used for obtaining the utilization data Bz by tracing the history from the utilization data Bz in the reverse direction. Since the input data By of the start point is stored in the data storage unit 53, it can also be called the stored data By. The input data extraction unit 131 generates an input data list 113 including the input data A1 and By of the specified start point. The input data list 113 includes the data name and the item of the acquisition source, similarly to the user-owned input data list 112.

The evaluation unit 140 generates a discrepancy list 114 by comparing the input data list 112 possessed by the user and the input data list 113 extracted from the history information 111. The mismatch list 114 is stored in the storage unit 110. The discrepancy list 114 includes list, history and source items. In the list item, among the records of the user-owned input data list 112, the data names of the records that do not exist in the input data list 113 are registered. In the history item, among the records of the input data list 113, the data names of the records that do not exist in the user-owned input data list 112 are registered. The acquisition source of the corresponding data is registered in the acquisition source item. When the data name is registered in the item of the list, the item of the history of the same record is not set. When the data name is registered in the history item, the item in the list of the same record is not set. In the figure, no setting is indicated by a hyphen "-".

A record including the data name "Bx" and the acquisition source "DB_Bx" of the user-owned input data list 112 is registered in the mismatch list 114 with respect to the user-owned input data list 112 and the input data list 113. Further, a record including the data name "By" and the acquisition source "DB_By" of the input data list 113 is registered in the mismatch list 114.

The evaluation unit 140 generates a history evaluation result 115 based on the disagreement list 114. The provenance evaluation result 115 is stored in the storage unit 110. Provenance evaluation result 115 includes items of classification and evaluation value. In the classification item, information representing a part of the data processing section belonging to a series of data processing is registered. In the evaluation value item, the evaluation value of the quality of the data for each classification is registered.

Here, for example, when the data changes such as the input data, the accumulated data, and the utilization data of the starting point, the data from the input data to the accumulated data is classified as the first section, and the accumulated data to the utilization data is classified as the second section. To. Alternatively, it is conceivable that the data may change, such as the input data of the starting point, the first storage data, the second storage data, and the utilization data. In this case, even if the input data to the first accumulated data is classified as the first section, the first accumulated data to the second accumulated data is classified as the second section, and the second accumulated data to the utilized data is classified as the third section. good.

The evaluation unit 140 identifies the data corresponding to the history of the discrepancy list 114 and the information of the acquisition source as the input data of the start point among the history of the data related to the corresponding user in the history information 111, and the input data of the start point. The evaluation value is set to "0" for the classification following. On the other hand, the evaluation unit 140 specifies the data history of the corresponding user in the history information 111, in which the data corresponding to the data name and the acquisition source information of the user possessed input data list 112 is used as the input data of the starting point. .. The evaluation unit 140 sets the evaluation value to "1" for the classification following the specified input data of the start point.

For example, in the history evaluation result 115, a record with an evaluation value of "1" is registered for the classification "between A1 and A2". This indicates that the evaluation value of the quality of the accumulated data A2 generated based on the input data A1 by the history evaluation is "1".

Further, in the history evaluation result 115, a record having an evaluation value of "1" is registered for the classification "A2-A3". This indicates that the evaluation value of the quality of the utilization data A3 generated based on the accumulated data A2 by the history evaluation is "1".

Further, in the history evaluation result 115, a record having an evaluation value of "0" is registered for the classification "between By and Bz". This indicates that the evaluation value of the quality of the utilization data Bz generated based on the accumulated data By is "0" by the history evaluation.

In addition, there may be multiple data of the actual starting point corresponding to the utilization data. In that case, the evaluation unit 140 can control the quality of the utilization data and the intermediate data to be evaluated higher as the number of the data of the actual start point included in the user-owned input data list 112 is larger.

Next, the security evaluation will be described.
FIG. 8 is a diagram showing an example of security evaluation.
For example, the history information 111 reaches the utilization data Az and AB1 stored in the utilization data storage unit 80 via the storage data Ay stored in the data storage unit 53 from the input data Ax stored in the input data storage unit 70. Includes history information.

The history information 111 indicates that the accumulated data Ay was generated by the data acquisition of the data acquisition software 51 for the input data Ax and the data processing process s1 of the data processing software 52. Further, the history information 111 indicates that the utilization data Az is generated by the data shaping process s3 of the data shaping software 54 for the accumulated data Ay. Further, the history information 111 indicates that the utilization data AB1 is generated by the data shaping process s4 of the data shaping software 54 for the accumulated data Ay.

First, the access authority prediction unit 132 acquires the input data access authority information 111a indicating the access authority to the input data of the starting point specified at the time of the provenance evaluation. The input data access authority information 111a may be provided by the user or may be acquired from the information processing system 50. Alternatively, when the history information 111 includes data access authority information, the input data access authority information 111a may be acquired from the history information 111. The input data access authority information 111a is stored in the storage unit 110.

For example, the access authority indicates the usage restrictions of the relevant data, and indicates the personnel who can access the relevant data. The access authority prediction unit 132 may specify the personnel who can access the data according to the information of the purpose of using the data (for example, the purpose of disclosure or secret management within the organization).

Further, the access authority prediction unit 132 acquires the processing shaping processing information 111b based on the history information 111. The processing shaping processing information 111b indicates the processing content used to obtain the output data from the input data in the corresponding processing. For example, the access authority prediction unit 132 derives the processing content by analyzing the query for the software specified by the history information 111. The processing and shaping processing information 111b is stored in the storage unit 110.

The access authority prediction unit 132 predicts the access authority based on the input data access authority information 111a and the processing and shaping processing information 111b, and generates the access authority prediction result 116. Details of access authority prediction will be described later. The access authority prediction result 116 is stored in the storage unit 110.

The access authority prediction result 116 includes the data name and access authority items. The name of the data is registered in the item of the data name. In the access authority item, the access authority predicted from the preceding data is registered for the corresponding data.

For example, in the access authority prediction result 116, a record indicating that the predicted access authority is "only the person in charge" is registered for the data name "Ay". Further, in the access authority prediction result 116, a record indicating that the predicted access authority is "only the data administrator" is registered for the data name "Az". Further, in the access authority prediction result 116, a record indicating that the predicted access authority is "anyone" is registered for the data name "AB1".

On the other hand, the access authority prediction unit 132 acquires the access authority information 117 indicating the actual access authority of each data, in addition to the access authority prediction result 116. The access authority information 117 is acquired from the information processing system 50 and stored in the storage unit 110. For example, the access authority information 117 includes a record indicating that the actual access authority is "anyone" for the data name "Ay". Further, the access authority information 117 includes a record indicating that the actual access authority is "anyone" for the data name "Az". Further, the access authority information 117 includes a record indicating that the predicted access authority is "anyone" for the data name "AB1".

The evaluation unit 140 generates the security evaluation result 118 by comparing the access authority prediction result 116 with the access authority information 117. The security evaluation result 118 is stored in the storage unit 110. Security evaluation result 118 includes classification and evaluation value items. The meanings of the items of classification and evaluation value are the same as the meanings of the items of the same name in the history evaluation result 115.

The evaluation unit 140 compares the access authority prediction result 116 and the access authority information 117, and determines whether or not the predicted access authority and the actual access authority match with respect to the data having the same data name. When the predicted access authority and the actual access authority match, the evaluation unit 140 sets the evaluation value to "1" for the classification for which the corresponding data is output. On the other hand, when the predicted access authority and the actual access authority do not match, the evaluation unit 140 sets the evaluation value to "0" for the classification for which the corresponding data is output.

For example, in the security evaluation result 118, a record with an evaluation value of "0" is registered for the classification "between Ax and Ay". This indicates that the evaluation value of the quality of the accumulated data Ay generated based on the input data Ax by the security evaluation is "0".

Further, in the security evaluation result 118, a record having an evaluation value of "0" is registered for the classification "between Ay and Az". This indicates that the evaluation value of the quality of the utilization data Az generated based on the accumulated data Ay by the security evaluation is "0".

Further, in the security evaluation result 118, a record with an evaluation value of "1" is registered for the classification "between Ay and AB1". This indicates that the evaluation value of the quality of the utilization data AB1 generated based on the accumulated data Ay is "1" by the security evaluation.

Here, an example of access authority prediction will be described.
FIG. 9 is a diagram showing an example of access authority prediction.
The access authority prediction unit 132 can predict the access authority of other data generated based on the input data of the start point based on the input data access authority information 111a regarding the input data of the start point. For example, the access authority prediction unit 132 may acquire the input data access authority information 111a from the information of the data catalog in the information processing system 50, or may acquire the input data access authority information 111a input by the user. ..

Input data access authority information 111a includes data name, column, secret classification, and access authority items. The name of the data is registered in the item of the data name. The column name (column name) included in the corresponding data is registered in the column item. A column is a data item contained in the corresponding data. In the item of secret classification, a secret classification indicating the classification of secret management for the corresponding column of the corresponding data is registered. In the access authority item, the access authority for the corresponding column of the corresponding data is registered.

For example, in the input data access authority information 111a, a record having a data name "Ax", a column "collect_a", a secret category "confidential", and an access authority "anyone in the company" is registered. This record indicates that the secret classification of the information in the column "column_a" of the input data Ax is "confidential" and the access authority is "anyone in the company". Here, "in-house" represents all users belonging to the company to which the corresponding user belongs.

In the input data access authority information 111a, even for other columns such as "collect_b" of the data name "Ax", secret classifications such as "confidential person concerned" and "public information", "only person in charge" and Access rights such as "Anyone in the company" are registered. Further, the input data access authority information 111a may include secret classification and access authority information regarding the input data of another starting point.

The access authority prediction unit 132 acquires the processing shaping processing information 111b. As described above, the access authority prediction unit 132 generates processing shaping processing information 111b by performing query analysis of each processing included in a series of data processing. For example, the access authority prediction unit 132 can also generate the processing shaping processing information 111b from the relationship between the input data and the output data for a certain process included in the history information 111. Processing The processing information 111b includes items of processing, input data, output data, input columns, and output columns. Identification information of the processing content in each software is registered in the processing item. Input data for the processing content is registered in the input data item. Output data for the processing content is registered in the output data item. The name of the column (input column) in the input data is registered in the item of the input column. The name of the column (output column) in the output data is registered in the item of the output column.

For example, the processing shaping processing information 111b includes a record of processing "processing s1", input data "Ax", output data "Ay", input column "collect_a", and output column "collect_a1". This record indicates that in the data processing process s1, the column volume_a1 of the accumulated data Ay is generated based on the column volume_a of the input data Ax.

Further, for example, the processing shaping processing information 111b includes a record of processing "processing s1", input data "Ax", output data "Ay", input columns "collect_b, volume_c", and output column "collect_bc". This record indicates that in the data processing process s1, the column volume_bc of the accumulated data Ay is generated based on the columns volume_b and volume_c of the input data Ax.

Records related to other processes such as data shaping process s3 are also registered in the processing shaping process information 111b.
The access authority prediction unit 132 generates an access authority prediction result 116a for each output column based on the input data access authority information 111a and the processing shaping processing information 111b. The access authority of the output column is predicted based on the access authority of the input column. For example, when there is one input column corresponding to a certain output column, the access authority of the input column is the expected access authority to the output column. Further, when there are a plurality of input columns for a certain output column, the most restrictive access authority among the access authority of the plurality of input columns is the expected access authority for the output column.

For example, according to the processing shaping processing information 111b, the column volume_a1 is generated based on the column volume_a. According to the input data access authority information 111a, the access authority of the column volume_a is "anyone in the company". Therefore, the access authority prediction unit 132 predicts that the access authority of the column volume_a1 of the accumulated data Ay is "anyone in the company". The access authority prediction unit 132 adds the predicted access authority "anyone in the company" to the prediction result 116a in association with the identification information of the column volume_a1.

Further, according to the processing shaping processing information 111b, the column "column_bc" is generated based on the columns "column_b" and "column_c". According to the input data access authority information 111a, the access authority of the column "collect_b" is "only the person in charge", and the access authority of the column "collect_c" is "anyone in the company". Therefore, the access authority prediction unit 132 predicts that the access authority of the column "collect_bc" of the accumulated data Ay is "only the person in charge" and "anyone in the company", which is the most restrictive "only the person in charge". .. The access authority prediction unit 132 adds the predicted access authority “only the person in charge” to the prediction result 116a in association with the identification information of the column volume_bc.

The access authority prediction unit 132 predicts the access authority of the accumulated data Ay based on the access authority predicted for each of the columns volume_a1 and volume_bc included in the accumulated data Ay, and generates the access authority prediction result 116. For example, the access authority prediction unit 132 may predict the most restrictive access authority among the predicted access authority for all columns of the corresponding data as the access authority of the corresponding data. In the example of the accumulated data Ay, among the predicted access privileges "anyone in the company" and "only the person in charge" for each of the columns volume_a1 and volume_bc, the most restrictive access authority is "only the person in charge". Therefore, the access authority prediction unit 132 predicts that the access authority of the accumulated data Ay is "only the person in charge". The access authority prediction unit 132 adds the access authority “only the person in charge” predicted for the stored data Ay to the access authority prediction result 116.

The evaluation unit 140 may generate the security evaluation result 118 by comparing the prediction result 116a predicted for each column of data with the actual access authority for each column of the data. In that case, for example, the evaluation unit 140 evaluates that the more columns with the same access authority, the higher the evaluation value of the corresponding data, that is, the more columns with the same access authority, the higher the quality. It can also be controlled.

Next, the latestness evaluation will be described.
FIG. 10 is a diagram showing an example of up-to-dateness evaluation.
Provenance information 111 includes information indicating the provenance of the data exemplified in FIG. First, the delay time calculation unit 133 acquires the delay requirement information 119. In the delay requirement information 119, a time allowed by the user is registered as a delay time from the generation of the input data of the start point to the update of the utilization data. The delay requirement information 119 is input to the information processing apparatus 100 by the user and stored in the storage unit 110.

Delay requirement information 119 includes data names and delay requirement items. The data name of the utilization data is registered in the data name item. In the item of delay requirement, the allowable delay time from the generation of the input data of the starting point to the update of the utilization data is registered. In the item of delay requirement, the upper limit of the delay time allowed from the generation of the input data of the starting point to the update of the utilization data may be registered.

For example, the delay requirement information 119 includes a record indicating that the delay requirement of the utilization data A3 is "within 2 hours". Further, the delay requirement information 119 includes a record indicating that the delay requirement of the utilization data AB is "within 5 minutes". Further, the delay requirement information 119 includes a record indicating that the delay requirement of the utilization data B3 is "within 1 minute". The delay requirement information 119 may include a record of delay requirements for utilization data generated by other data processing.

The delay time calculation unit 133 generates the actual delay time information 120 based on the history information 111. The actual delay time information 120 is stored in the storage unit 110. For example, the delay time calculation unit 133 acquires the data update log recorded by the information processing system 50 from the information processing system 50 and stores it in the storage unit 110. The data update log contains information indicating the data name and the time when the data of the data name was updated. The delay time calculation unit 133 generates the actual delay time information 120 based on the history information 111 and the data update log.

The actual delay time information 120 includes items of data name, update time, and delay time. The data name is registered in the data name item. In the update time item, the update time of the data with the corresponding data name is registered. In the example of FIG. 10, for the sake of simplicity, an example in which the update time is the same day is shown, but the update time may include a date. In the item of delay time, the time elapsed from the time when the input data of the start point is updated, that is, the delay time is registered. For the input data of the start point, the delay time is "-" (no setting).

The delay time calculation unit 133 can acquire the data name and update time information from the above-mentioned data update log. Further, the delay time calculation unit 133 identifies the input data of the start point and the subsequent data generated based on the input data of the start point by tracing the history of the data based on the history information 111, and identifies the subsequent data generated based on the input data of the start point. The delay time for the data can be calculated.

For example, the actual delay time information 120 includes a record with an update time "02:30" and a delay time "-" with respect to the input data A1. Since the input data A1 is the "input data of the starting point" specified by the input data extraction unit 131, the delay time is "-".

Further, the actual delay time information 120 includes a record of the update time "13:30" and the delay time "-" with respect to the input data B1. Since the input data B1 is the "input data of the starting point" specified by the input data extraction unit 131, the delay time is "-".

Further, the actual delay time information 120 includes a record of the update time "02:32" and the delay time "2 minutes" with respect to the accumulated data A2. According to the history information 111, the stored data A2 is stored in the data storage unit 53 after data acquisition and data processing for the input data A1. Therefore, the delay time of the accumulated data A2 is the difference "2 minutes" between the update time "02:30" of the input data A1 and the update time "02:32" of the accumulated data A2.

The actual delay time information 120 includes a record of the update time "13:33" and the delay time "3 minutes" with respect to the accumulated data B2. The actual delay time information 120 includes a record of the update time "04:00" and the delay time "1 hour 30 minutes" with respect to the utilization data A3. The actual delay time information 120 includes a record of the update time “13:33” and the delay time “3 minutes” with respect to the utilization data AB. The actual delay time information 120 includes a record of the update time “13:33” and the delay time “3 minutes” with respect to the utilization data B3.

The evaluation unit 140 evaluates the up-to-dateness of the data by determining whether or not the delay time calculated for the utilization data satisfies the delay requirement of the delay requirement information 119 based on the actual delay time information 120. Then, the latestness evaluation result 121 is generated. The up-to-dateness evaluation result 121 is stored in the storage unit 110. The up-to-dateness evaluation result 121 includes items of classification and evaluation value. The meaning of the classification and the evaluation value is the same as the meaning of the item of the same name in the provenance evaluation result 115.

When the delay time calculated for the utilization data meets the delay requirement, the evaluation unit 140 sets the evaluation value of each classification up to the corresponding utilization data to "1". When the delay time calculated for the utilization data does not satisfy the delay requirement, the evaluation unit 140 sets the evaluation value of each classification leading to the utilization data to "0". When both the evaluation values "1" and "0" can be given to a certain classification, the evaluation value of the classification is set to "0".

In the example of the actual delay time information, since the utilization data A3 and AB satisfy the delay requirement, the evaluation value of each classification up to the utilization data A3 and AB is "1". On the other hand, since the utilization data B3 does not satisfy the delay requirement, the evaluation value of each classification leading to the utilization data “B3” is “0”. In particular, the classification "between B1 and B2" is a classification linked to the utilization data AB and B3, but the evaluation value is "0" because the delay requirement is not satisfied for the utilization data B3.

Note that the history information 111 may include information corresponding to the data update log. In that case, the delay time calculation unit 133 can generate the actual delay time information 120 from the history information 111 without separately acquiring the data update log from the information processing system 50.

In this way, the evaluation unit 140 evaluates the data quality by the history evaluation, the security evaluation, and the up-to-dateness evaluation based on the analysis result by the history information analysis unit 130. Further, the evaluation unit 140 performs a comprehensive evaluation of data quality based on the evaluation results of the history evaluation, the security evaluation, and the up-to-dateness evaluation. Next, the comprehensive evaluation will be described.

FIG. 11 is a diagram showing an example of a comprehensive evaluation result table.
The comprehensive evaluation result table 122 is generated by the evaluation unit 140 and stored in the storage unit 110 based on the probability evaluation result 115, the security evaluation result 118, and the up-to-dateness evaluation result 121. The comprehensive evaluation result table 122 includes items of classification, history evaluation value, security evaluation value, up-to-dateness evaluation value, and comprehensive evaluation value.

Classification is registered in the classification item. The meaning of the classification is the same as the meaning of the classification in the history evaluation result 115. In the item of the provenance evaluation value, the evaluation value in the provenance evaluation result 115 for the corresponding classification, that is, the provenance evaluation value is registered. In the item of security evaluation value, the evaluation value in the security evaluation result 118 for the corresponding classification, that is, the security evaluation value is registered. In the item of up-to-dateness evaluation value, the evaluation value in the up-to-dateness evaluation result 121 for the corresponding classification, that is, the up-to-dateness evaluation value is registered. In the item of the comprehensive evaluation value, the comprehensive evaluation value calculated based on the history evaluation value, the security evaluation value and the up-to-dateness evaluation value is registered. For example, the comprehensive evaluation value is the sum of the history evaluation value, the security evaluation value, and the up-to-dateness evaluation value.

For example, the comprehensive evaluation result table 122 is a record of a history evaluation value "1", a security evaluation value "1", an up-to-date evaluation value "1", and a comprehensive evaluation value "3" for the classification "A1-A2". including. Further, for example, in the comprehensive evaluation result table 122, the history evaluation value "0", the security evaluation value "0", the up-to-dateness evaluation value "0", and the comprehensive evaluation value "0" are shown for the classification "B1-B2". Includes records for. Records for other classifications are also registered in the comprehensive evaluation result table 122.

In the above example, the evaluation unit 140 has shown that the sum (V1 + V2 + V3) of the history evaluation value (V1), the security evaluation value (V2), and the up-to-dateness evaluation value (V3) is used as the comprehensive evaluation value. Here, V1, V2, and V3 are positive real numbers. On the other hand, other examples can be considered for the calculation method of the comprehensive evaluation value. For example, the evaluation unit 140 may use a weighted sum (w1 * V1 + w2 * V2 + w3 * V3) weighted for each of the provenance evaluation value, the security evaluation value, and the up-to-dateness evaluation value as the comprehensive evaluation value. Here, w1, w2, and w3 are positive real numbers.

The display control unit 150 causes the display 61 to display an evaluation result screen showing the evaluation result based on the comprehensive evaluation result table 122. Next, an example of the evaluation result screen will be described.
FIG. 12 is a diagram showing a first example of the evaluation result screen.

The evaluation result screen 400 includes images of the data flow diagram 401 and the legend 402. The data flow diagram 401 is a diagram showing a data flow in the information processing system 50. The display control unit 150 accepts the input of the user's identification information, and displays the flow of data related to the user's identification information as the data flow diagram 401 based on the history information 111.

Data flow In FIG. 401, the data flow is represented by an arrow. One arrow corresponds to the classification in the comprehensive evaluation result table 122. The display control unit 150 presents the evaluation value for each classification, that is, the evaluation result of the quality, to the user by coloring the arrow. Legend 402 indicates the high quality corresponding to the color of the arrow.

The example of FIG. 12 shows a case where quality is distinguished by three colors. The first color represents quality "high". The second color represents quality "medium". The third color represents quality "low". The first color is, for example, green. The second color is, for example, yellow. The third color is, for example, red.

For example, the display control unit 150 uses the arrow of the classification corresponding to the total evaluation value of "3" as the first color in the comprehensive evaluation result table 122. Further, the display control unit 150 uses the arrow of the classification corresponding to the comprehensive evaluation value "0" in the comprehensive evaluation result table 122 as the third color. Further, the display control unit 150 sets the arrow of the classification in which the comprehensive evaluation value is larger than 0 and smaller than 3 in the comprehensive evaluation result table 122 as the second color. The color coding of the arrows according to the comprehensive evaluation value may be performed by using two colors or four or more colors.

The display control unit 150 displays, for example, a cross mark "X" superimposed on the utilization data obtained via an arrow having a low overall evaluation value (for example, an overall evaluation value of less than 3). Show the user that it is a part that needs to be reviewed.

The user can select an icon representing data or processing in the data flow diagram 401 by operating the pointer P1 displayed on the evaluation result screen 400 by the input device 62.

FIG. 13 is a diagram showing a second example of the evaluation result screen.
When the display control unit 150 detects that the icon of the utilization data AB on the evaluation result screen 400 is selected by the pointer P1, the display control unit 150 updates the evaluation result screen 400 to the evaluation result screen 500. The evaluation result screen 500 includes images of the data flow diagram 501 and the legend 502. The legend 502 is the same as the legend 402.

In the data flow diagram 501, an arrow in the reverse direction, which goes back from the selected utilization data AB to the accumulated data B2 via the data shaping process s4, is highlighted. Further, in the data flow diagram 501, a forward arrow indicating that the input data B1 reaches the accumulated data B2 via the data acquisition process and the data processing process s2 is highlighted. Other arrows are displayed in an inconspicuous manner.

Further, when tracing back the data input source for the data shaping process s4, there are two input sources, the accumulated data A2 and B2, and they are branched. In this case, it is conceivable that the display control unit 150 preferentially selects the one having the lower overall evaluation value and displays the arrow in the opposite direction. More specifically, on the evaluation result screen 500, when the data shaping process s4 traced back from the utilization data AB is traced in the reverse direction, the data is branched into the accumulated data A2 and B2. Therefore, the display control unit 150 highlights the arrow connected to the classification "B1-B2", which is the lower of the classifications "A1-A2" and "B1-B2", which has the lower overall evaluation value. This makes it easier for the user to find a part that causes deterioration of data quality.

In the examples of FIGS. 12 and 13, the evaluation result screens 400 and 500 for the comprehensive evaluation value are illustrated, but the display control unit 150 uses the comprehensive evaluation result table 122 as a basis for the provenance evaluation value, the security evaluation value, and the latest. The evaluation result screen for each of the sex evaluation values may be displayed.

Next, the processing procedure of the information processing apparatus 100 will be described.
FIG. 14 is a flowchart showing a processing example of the information processing apparatus.
The information processing apparatus 100 starts the following procedure when, for example, the user receives an input for starting a data quality evaluation.

(S10) The provenance information analysis unit 130 generates an input data list 113 corresponding to the identification information of the corresponding user based on the provenance information 111. The evaluation unit 140 evaluates the history of data based on the user-owned input data list 112 and the input data list 113, and generates the history evaluation result 115. The evaluation unit 140 stores the generated probability evaluation result 115 in the storage unit 110. The procedure for provenance evaluation will be described later.

(S11) The provenance information analysis unit 130 generates the access authority prediction result 116 based on the provenance information 111. The evaluation unit 140 performs security evaluation of data based on the access authority prediction result 116 and the actual access authority information 117, and generates the security evaluation result 118. The evaluation unit 140 stores the generated security evaluation result 118 in the storage unit 110. The security evaluation procedure will be described later.

(S12) The provenance information analysis unit 130 generates the actual delay time information 120 based on the provenance information 111. The evaluation unit 140 evaluates the latestness of the data based on the delay requirement information 119 and the actual delay time information 120, and generates the latestness evaluation result 121. The evaluation unit 140 stores the generated up-to-dateness evaluation result 121 in the storage unit 110. The procedure for up-to-date evaluation will be described later.

(S13) The evaluation unit 140 generates a comprehensive evaluation result table 122 based on the provenance evaluation result 115, the security evaluation result 118, and the up-to-dateness evaluation result 121. The evaluation unit 140 stores the generated comprehensive evaluation result table 122 in the storage unit 110. The evaluation unit 140 registers the history evaluation value, the security evaluation value, and the latestness evaluation value of each category in the history evaluation result 115, the security evaluation result 118, and the up-to-dateness evaluation result 121 in the comprehensive evaluation result table 122. Then, the evaluation unit 140 calculates the sum of the history evaluation value, the security evaluation value, and the up-to-dateness evaluation value as the comprehensive evaluation value for each classification, and registers the sum in the comprehensive evaluation result table 122. The comprehensive evaluation value may be calculated by another calculation method such as a weighted sum of the history evaluation value, the security evaluation value, and the up-to-dateness evaluation value.

(S14) The display control unit 150 executes the evaluation result display control based on the comprehensive evaluation result table 122. The procedure for controlling the evaluation result display will be described later. When the display control unit 150 receives the input of the end of the evaluation result display by the user, the display control unit 150 ends the evaluation result display control and ends the display of the evaluation result screen. Then, the processing of the information processing apparatus 100 is completed.

FIG. 15 is a flowchart showing a history evaluation example.
Provenance evaluation corresponds to step S10.
(S20) The input data extraction unit 131 acquires the user-owned input data list 112 and stores it in the storage unit 110. For example, the user-owned input data list 112 is input to the information processing apparatus 100 by the user.

(S21) The input data extraction unit 131 generates a list of input data of the actual start point, that is, an input data list 113, based on the history information 111 stored in the storage unit 110, and stores the input data list 113 in the storage unit 110. At this time, the input data extraction unit 131 identifies the history of the data used in the process corresponding to the identification information of the corresponding user based on, for example, the history information 111, and generates the input data list 113 from the specified history.

(S22) The evaluation unit 140 specifies the utilization data to be evaluated. In the history evaluation process, it is assumed that the initial value of the history evaluation value of each data at the time when step S22 is first executed is 0.

(S23) The evaluation unit 140 determines whether or not the input data of the actual starting point corresponding to the corresponding utilization data matches the user-owned input data based on the user-owned input data list 112 and the input data list 113. .. If they match, the evaluation unit 140 proceeds to step S24. If they do not match, the evaluation unit 140 proceeds to step S25.

(S24) The evaluation unit 140 adds points to the evaluation value of the history evaluation of the corresponding utilization data, that is, the history evaluation value. In addition, the evaluation unit 140 also adds points to the history evaluation value of the intermediate data (accumulated data) leading to the corresponding utilization data. In adding points, for example, the revenue evaluation value "1" (unit points) is added. However, the history evaluation value to be added may be other than "1", and as described above, the history evaluation value for the corresponding data may be given so as not to exceed a predetermined upper limit value (for example, "1"). Here, the quality evaluation value for a certain data corresponds to the evaluation value of the classification that outputs the data. For example, the evaluation value for the classification "between A1 and A2" in the comprehensive evaluation result table 122 can be said to be the evaluation value for the accumulated data A2.

(S25) The evaluation unit 140 determines whether or not all the utilization data to be evaluated have been evaluated. If all the utilization data to be evaluated have been evaluated, the evaluation unit 140 ends the history evaluation. If the evaluation target full utilization data has not been evaluated, the evaluation unit 140 proceeds to step S22.

In the processing of steps S23 and S24, there may be a plurality of actual starting point data corresponding to the utilization data. In that case, the evaluation unit 140 adds points to the history evaluation values of the utilization data and the intermediate data as many as the number included in the user-possessed input data list 112 among the actual start point data. For example, when the number of the input data of the actual start point included in the user-owned input data list 112 is 2, the evaluation unit 140 utilizes the evaluation value twice as the unit score a of the evaluation value, or the intermediate data. It is conceivable to add to each history evaluation value of.

FIG. 16 is a flowchart showing an example of security evaluation.
The security evaluation corresponds to step S11.
(S30) The access authority prediction unit 132 identifies the input data of the starting point corresponding to the identification information of the user to be processed based on the input data list 113 generated in step S21. The access authority prediction unit 132 acquires the input data access authority information 111a related to the input data of the specified start point and stores it in the storage unit 110. Further, the access authority prediction unit 132 acquires the processing and shaping processing information 111b related to the processing from the input data of the start point to the utilization data based on the history information 111, and stores it in the storage unit 110.

(S31) The access authority prediction unit 132 predicts the access authority of other data obtained from the input data of the start point based on the history information 111, generates the access authority prediction result 116, and stores it in the storage unit 110. Other data obtained from the input data of the start point includes accumulated data (intermediate data) and utilization data generated based on the input data of the start point. Further, the access authority prediction unit 132 acquires the access authority information 117 indicating the actual data access authority from the data catalog or the like of the information processing system 50 and stores it in the storage unit 110.

(S32) The evaluation unit 140 specifies the data to be evaluated. Candidates for the data to be evaluated are all accumulated data and all utilization data included in the access authority prediction result 116. The evaluation unit 140 specifies one data to be evaluated from the data candidates to be evaluated. In the security evaluation process, the initial value of the security evaluation value of each data at the time when step S32 is first executed is assumed to be 0.

(S33) The evaluation unit 140 determines whether or not the predicted access authority for the data to be evaluated in the access authority prediction result 116 matches the actual access authority in the access authority information 117. If they match, the evaluation unit 140 proceeds to step S34. If they do not match, the evaluation unit 140 proceeds to step S35.

(S34) The evaluation unit 140 adds points to the evaluation value of the security evaluation of the data to be evaluated, that is, the security evaluation value. In addition, for example, a security evaluation value "1" is added. However, the history evaluation value to be added may be other than "1", and as described above, a security evaluation value may be given to the relevant data so as not to exceed a predetermined upper limit value (for example, "1").

(S35) The evaluation unit 140 determines whether or not all the data to be evaluated have been evaluated. If all the data to be evaluated have been evaluated, the evaluation unit 140 ends the security evaluation. If all the data to be evaluated have not been evaluated, the evaluation unit 140 proceeds to step S32.

FIG. 17 is a flowchart showing an example of up-to-date evaluation.
The up-to-dateness evaluation corresponds to step S12.
(S40) The delay time calculation unit 133 acquires the delay requirement information 119 regarding the utilization data. For example, the delay requirement information 119 is input to the information processing apparatus 100 by the user.

(S41) The delay time calculation unit 133 calculates the delay time of the actual data update for the utilization data based on the history information 111. As described above, the delay time calculation unit 133 can use the data update log acquired from the information processing system 50 to calculate the delay time for data update. The delay time calculation unit 133 records the calculated delay time in the actual delay time information 120 stored in the storage unit 110.

(S42) The evaluation unit 140 specifies the utilization data to be evaluated. In the up-to-dateness evaluation process, it is assumed that the initial value of the up-to-dateness evaluation value of each data at the time when step S42 is first executed is 0.

(S43) The evaluation unit 140 determines whether or not the delay time calculated for the corresponding utilization data is within the permissible range based on the delay requirement information 119 based on the delay requirement information 119 and the actual delay time information 120. judge. If it is within the permissible range, the process proceeds to step S44. If it is not within the permissible range, the process proceeds to step S45.

(S44) The evaluation unit 140 adds points to the evaluation value of the latestness evaluation of the corresponding utilization data, that is, the latestness evaluation value. In addition, the evaluation unit 140 also adds points for the up-to-dateness evaluation value of the intermediate data (accumulated data) leading to the corresponding utilization data. In addition, for example, the latestness evaluation value "1" is added. However, the up-to-dateness evaluation value to be added may be other than "1", and as described above, even if the up-to-dateness evaluation value is given to the corresponding data so as not to exceed a predetermined upper limit value (for example, "1"). good.

(S45) The evaluation unit 140 determines whether or not all the utilization data to be evaluated have been evaluated. If all the utilization data to be evaluated have been evaluated, the evaluation unit 140 ends the up-to-date evaluation. If the evaluation target full utilization data has not been evaluated, the evaluation unit 140 proceeds to step S42.

FIG. 18 is a flowchart showing an evaluation result display control example.
The evaluation result display control corresponds to step S14.
(S50) The display control unit 150 accepts the user's selection of the evaluation type to be displayed. Evaluation types include history evaluation, security evaluation, up-to-date evaluation, and comprehensive evaluation. The user may select one of these evaluation types, or may select a combination of two of the history evaluation, the security evaluation, and the up-to-date evaluation. In the following, the case where the comprehensive evaluation is mainly selected is illustrated, but the procedure is the same for other evaluation types.

(S51) The display control unit 150 displays the evaluation result screen 400 showing the history of the data corresponding to the identification information of the corresponding user on the display 61. The display control unit 150 transmits the information of the evaluation result screen 400 to another device such as a client device connected via the network 60, and the evaluation result screen is displayed on the display connected to the other device by the other device. 400 may be displayed. The display control unit 150 displays the data flow diagram 401 in which the arrow indicating “classification” is color-coded using the evaluation value (here, the comprehensive evaluation value) corresponding to the evaluation type selected in step S50 on the evaluation result screen 400. Display inside. The evaluation result screen 400 may include the image of the legend 402. When two evaluation types are selected in step S50, the display control unit 150 may color-code the arrows according to the sum of the evaluation values of the two evaluation types for the corresponding classification.

(S52) The display control unit 150 determines whether or not any data is selected in the data flow diagram 401. If there is such a selection, the display control unit 150 proceeds to step S53. If there is no such selection, the display control unit 150 proceeds to step S54. For example, the user can operate the input device 62 to select the data displayed in the data flow diagram 401 by the pointer P1. Alternatively, when the evaluation result screen 400 is displayed by the client device used by the user, the user may operate the input device of the client device to input the selection of any data to the information processing device 100. ..

(S53) The display control unit 150 displays a data flow that traces back from the data selected based on the comprehensive evaluation value. For example, when the utilization data AB is selected in the data flow diagram 401, the display control unit 150 displays an evaluation result screen 500 including a data flow that traces back from the utilization data AB to the accumulated data B2 which is the previous data. As described above, when the display control unit 150 has a branch in the retroactive route, the display control unit 150 preferentially selects and selects the classification that includes many classifications having a low comprehensive evaluation value among the classifications leading to the utilization data AB. It is conceivable to highlight the classification of the branch destination. For example, on the evaluation result screen 500, when the data shaping process s4 traced back from the utilization data AB is traced in the reverse direction, the data is branched into the accumulated data A2 and B2. Therefore, the display control unit 150 highlights the arrow connected to the classification "B1-B2", which is the lower of the classifications "A1-A2" and "B1-B2", which has the lower overall evaluation value.

(S54) The display control unit 150 determines whether or not the input for ending the display has been accepted. When the display end input is received, the display control unit 150 ends the evaluation result display control. If the display control unit 150 does not accept the input for ending the display, the display control unit 150 proceeds to step S52.

As described above, according to the information processing apparatus 100, it is possible to realize a service for evaluating the data quality in the information processing infrastructure. In particular, the information processing apparatus 100 evaluates the flow of data across software products by utilizing the history information of the data. Further, the information processing apparatus 100 displays the problematic portion on the data flow diagram based on the evaluation result.

This makes it possible to evaluate data across multiple softwares and support the user's identification of problem areas in the entire information processing infrastructure.
Here, in the information processing system 50, various software is executed. For example, it is conceivable to evaluate the data itself for each software product based on data missing values, duplicate data, data types, and the like. However, in an information processing platform consisting of multiple software products, not only evaluation of each software product but also evaluation of whether data quality is properly managed in a series of flows from data collection to output destination is evaluated. Is possible.

However, no mechanism for evaluating data quality has been considered in a series of flows that span multiple software products. For example, in order to evaluate the data quality in a series of flows, it is conceivable to personally evaluate the data quality of each software product, but the evaluation takes time. In particular, forcing the user to read the data flow in order to identify the cause of the deterioration of data quality is a heavy burden on the user and takes time for evaluation.

Therefore, the information processing apparatus 100 appropriately evaluates the quality of data in the data processing by the plurality of software based on the history information 111.
For example, in a series of data processing by a plurality of software, the quality of the data output by the data processing changes depending on whether or not the data intended by the user is processed. For example, when performing data processing such as analysis, if input data not intended by the user is processed, the input data may contain unnecessary information or incorrect information, resulting in data processing. Is more likely to be wrong, which reduces the reliability of the result.

Therefore, the information processing apparatus 100 specifies the input data of the start point of the data processing by the plurality of software based on the history information 111. By confirming whether the input data of the start point is the input intended by the user, the quality of the utilization data and the accumulated data output by the data processing can be appropriately evaluated. In addition, the evaluation can be performed faster than the user can perform.

Further, the information processing apparatus 100 evaluates the quality of data in a plurality of evaluation types such as security evaluation and up-to-dateness evaluation in addition to the history evaluation, and comprehensively evaluates the quality of the data from the evaluation results in the plurality of evaluation types. Therefore, the quality of the data can be evaluated more appropriately.

For example, the information processing apparatus 100 performs the following processing.
The history information analysis unit 130 extracts information on the first input data, which is a starting point of data processing by the plurality of software, based on the history information 111 showing the history of input data and output data for each of the plurality of software. The evaluation unit 140 evaluates the quality of the first output data output by the data processing according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user. I do.

This makes it possible to appropriately evaluate the quality of the data.
The evaluation unit 140 ranges from the first input data to the first output data according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user. Perform quality evaluation of intermediate data via.

This makes it possible to appropriately evaluate the quality of not only the first output data, which is the final output of the data processing, but also the intermediate data generated in the process of data processing.
Further, the history information analysis unit 130 acquires the information of the first access authority to the first input data, and based on the first access authority and the history information 111, the second access authority to the first output data. Predict. The evaluation unit 140 evaluates the quality of the first output data according to the comparison of whether or not the actual access authority of the first output data matches the predicted second access authority.

In this way, by confirming whether or not the access authority of the first output data predicted from the history information 111 matches the actual access authority, the first output data is generated through an appropriate process. It is possible to evaluate whether or not it is a product. For example, if the access permissions do not match, there is a possibility that inappropriate processing that the user did not anticipate has been performed in the process of generating the first output data. Therefore, if the predicted access authority does not match the actual access authority, the quality of the corresponding data is judged to be low.

In the prediction of the second access authority, the history information analysis unit 130 determines the third access authority for the intermediate data passing from the first input data to the first output data based on the first access authority. Predict. The provenance information analysis unit 130 predicts the second access authority based on the predicted third access authority.

In this way, the second access authority can be appropriately predicted by predicting the access authority of the data in order in the forward direction of the data flow based on the prediction result of the access authority to the intermediate data.

The evaluation unit 140 may evaluate the quality of the intermediate data according to the comparison of whether or not the actual access authority of the intermediate data matches the predicted third access authority.
This makes it possible to appropriately evaluate the quality of not only the first output data, which is the final output of the data processing, but also the intermediate data generated in the process of data processing.

Further, the history information analysis unit 130 acquires information on the first delay time allowed from the generation of the first input data to the update of the first output data. The information of the first delay time is input by the user, for example. The history information analysis unit 130 calculates a second delay time from the generation of the first input data to the update of the first output data based on the data update history information and the history information 111. .. The evaluation unit 140 evaluates the quality of the first output data according to the comparison of whether or not the second delay time is shorter than the first delay time.

In this way, the first output data is generated through an appropriate process depending on whether the delay time from the generation of the first input data to the update of the first output data meets the delay requirement of the user. It is possible to evaluate whether or not it is a thing. For example, if the second delay time is longer than the first delay time, the delay requirement is not satisfied, and an abnormality or performance deterioration occurs in the process from the first input data to the first output data. There may be. Therefore, when the second delay time is longer than the first delay time, it is determined that the quality of the first output data is low. The evaluation unit 140 passes through from the first input data to the first output data in addition to the first output data according to the comparison between the second delay time and the first delay time. Data quality may be evaluated. In this case as well, if the second delay time is longer than the first delay time, the quality of the intermediate data is judged to be low.

The display control unit 150 causes the display device to display the data flow diagram 401 from the first input data to the first output data. The display control unit 150 determines the display mode of the image element, which is included in the data flow diagram 401 and shows the relationship between the first input data and the first output data, based on the result of quality evaluation for the first output data. change.

This can help the user identify the review location. Data flow The arrow indicating the data flow in FIG. 401 is an example of an image element. The display 61 is an example of a display device. The display device may be a display device connected to another information processing device. In that case, the display control unit 150 performs display control by transmitting information on the display content to another information processing device via the network 60.

The display control unit 150 accepts the selection of the image showing the first output data included in the data flow diagram 401 displayed on the display device. Then, the display control unit 150 emphasizes among a plurality of image elements showing the relationship between the data up to the first output data, based on the evaluation value of the data up to the first output data. Select the image element to be displayed and highlight the selected image element.

This can help the user identify the review location. For example, as illustrated in FIG. 13, a series based on the input data of a plurality of starting points of the data flow leading to the first output data (for example, between the classifications “A1-A2” and “B1-B2”) There may be. In that case, it is conceivable that the display control unit 150 selects and highlights an image element belonging to a series containing many classifications having low evaluation values or a series having a low average value of the evaluation values of the classifications. As a result, it is possible to present a part having a high priority for review by the user, and it is possible to support the efficient identification of the part to be reviewed by the user.

The information processing of the first embodiment can be realized by causing the processing unit 12 to execute the program. Further, the information processing of the second embodiment can be realized by causing the CPU 101 to execute the program. The program can be recorded on a computer-readable recording medium 63.

For example, the program can be distributed by distributing the recording medium 63 on which the program is recorded. Alternatively, the program may be stored in another computer and distributed via the network. For example, the computer may store (install) a program recorded on the recording medium 63 or a program received from another computer in a storage device such as RAM 102 or HDD 103, read the program from the storage device, and execute the program. good.

The above merely indicates the principle of the present invention. Further, numerous modifications and modifications are possible to those skilled in the art, and the invention is not limited to the exact configurations and applications described and described above, and all corresponding modifications and equivalents are attached. It is considered to be the scope of the present invention according to the claims and their equivalents.

10 Information processing device 11 Storage unit 12 Processing unit 20 History information 31, 32 Software 41, 42, 43 Data storage unit d1, d2, d3 Data S1, S2 Step

Claims (10)

On the computer
Based on the history information indicating the history of the input data and the output data for each of the plurality of software, the information of the first input data which is the starting point of the data processing by the plurality of software is extracted.
The quality of the first output data output by the data processing is evaluated according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user.
An information processing program that executes processing. Further to the computer
The route from the first input data to the first output data depends on the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user. Perform quality evaluation of intermediate data
The information processing program according to claim 1, wherein the processing is executed. Further to the computer
The information of the first access authority to the first input data is acquired, and the second access authority to the first output data is predicted based on the first access authority and the history information.
The quality of the first output data is evaluated according to the comparison of whether or not the actual access authority of the first output data matches the predicted second access authority.
The information processing program according to claim 1 or 2, wherein the processing is executed. In the prediction of the second access authority, the third access authority to the intermediate data passing from the first input data to the first output data is predicted based on the first access authority. Predicting the second access right based on the predicted third access right,
The information processing program according to claim 3. Further to the computer
The quality of the intermediate data is evaluated according to the comparison of whether or not the actual access authority of the intermediate data matches the third access authority.
The information processing program according to claim 4. Further to the computer
Information on the first delay time allowed from the generation of the first input data to the update of the first output data is acquired.
Based on the data update history information and the history information, the second delay time from the generation of the first input data to the update of the first output data is calculated, and the second delay time is calculated. The quality of the first output data is evaluated according to the comparison of whether or not the delay time is shorter than the first delay time.
The information processing program according to any one of claims 1 to 5, wherein the processing is executed. Further to the computer
A data flow diagram from the first input data to the first output data is displayed on the display device, and the relationship between the first input data and the first output data included in the data flow diagram is determined. The display mode of the image element shown is changed based on the result of the quality evaluation for the first output data.
The information processing program according to any one of claims 1 to 6, wherein the processing is executed. Further to the computer
When an image showing the first output data included in the data flow diagram displayed on the display device is selected, the said is based on the evaluation value of the data passing through to the first output data. Among a plurality of image elements showing the relationship between the data up to the first output data, the image element to be highlighted is selected, and the selected image element is highlighted.
The information processing program according to claim 7, wherein the processing is executed. The computer
Based on the history information indicating the history of the input data and the output data for each of the plurality of software, the information of the first input data which is the starting point of the data processing by the plurality of software is extracted.
The quality of the first output data output by the data processing is evaluated according to the comparison of whether or not the information of the first input data matches the information of the predetermined data input by the user.
Information processing method. A storage unit that stores history information indicating the history of input data and output data for each of a plurality of software, and a storage unit.
Based on the history information stored in the storage unit, the information of the first input data which is the starting point of the data processing by the plurality of software is extracted, and the information of the first input data is input by the user. , A processing unit that evaluates the quality of the first output data output by the data processing according to the comparison of whether or not the information matches the predetermined data.
Information processing device with.

Images