JP2018063572A - Information processing apparatus and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce inefficiency related to access authority to data.SOLUTION: An information processing apparatus comprises: an object data storage part 1 that stores data to be candidates for an analysis object; a data universality information storage part 3 that stores data universality information indicating the degree of universality of data; a classification information storage part 4 that stores classification information for classifying the data into a plurality of groups; an information source management and input part 5 that receives an input of information source involvement range information indicating the authority of an operator to information sources; an analysis type input part 6 that receives an input of analysis universality information indicating the degree of universality of data analysis; an access authority processing part 7 that determines whether or not access to the data analysis to be executed by the operator is permitted for every type of the data; and an authority output part 8 that performs setting, to the access processing part 2, of information on whether or not access to the data in the object data storage part 1 is permitted on the basis of a result of determination performed by the access authority processing part 7.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a technique for analyzing big data, and more particularly to an information processing apparatus and method capable of reducing inefficiency related to access authority to data when performing analysis for big data. .

  With the speeding up, downsizing, and cost reduction of computers and related technologies, advanced control technology can be realized even at the small device level. On the other hand, as represented by the keyword IoT (Internet of Things), network technology has evolved and has penetrated the market. In particular, a solution service business that collects a large amount of data (so-called big data) on a cloud server and links it to new value creation has been activated.

  Multivariate analysis methods for big data (including AI (Artificial Intelligence), SVM (Support Vector Machine), etc.) handle data with a wide variety of properties and analyze data that falls under trade secrets There may be a need to be targeted. Therefore, it is necessary to consider information security issues. In the conventional technology, when a plurality of operators share (share) data, the access authority to the data can be arbitrarily set for each operator, and the data manager or the like sets the access authority appropriately. The method is adopted.

  Also, as a technique for handling access authority, an equipment control system that reduces the setting error due to the troublesomeness of the implanter and the misunderstanding of the administrator in equipment management is disclosed (see Patent Document 1). The equipment control system disclosed in Patent Document 1 is a non-main setting machine limited mode that does not limit the setting change operation of the equipment to the main setting machine → limited to the main setting machine that limits the setting change operation of the equipment to the main setting machine. When the mode is switched from mode to non-main setting machine limited mode, it automatically determines how to return the setting state of the equipment according to the elapsed time from the final setting operation in the main setting machine only mode. . This technique essentially corresponds to a technique for handling access authority focused on operators (administrators and residents).

JP 2014-0774520 A

  In the case where the data manager or the like sets the access authority as appropriate, the responsibility for managing the data source is generally considered. For this reason, for example, when the person in charge of management of an information source tries to analyze data collected from other information sources with similarities or commonality, general data having such commonality is used. There may be situations where you cannot access the.

  That is, since the access authority to data is not usually an access authority specialized for analysis of big data, inefficiency may occur when data is used. Therefore, there is a need for improved security management technology based on the assumption that analysis is performed on big data.

  The present invention has been made to solve the above-described problems, and provides an information processing apparatus and method capable of reducing inefficiency related to access authority to data when performing analysis on big data. The purpose is to do.

  An information processing apparatus according to the present invention includes a target data storage unit that stores one or more types of data that are candidates for analysis collected from one or more information sources, and an access to the data stored in the target data storage unit Access processing means for executing processing; data universality information storage means for preliminarily storing data universality information indicating a degree of universality of data for each type of data stored in the target data storage means; and the data Based on universality information, classification information storage means for previously storing classification information for classifying the candidate data to be analyzed into a plurality of groups, and an operator's information source for the data to be the candidate for analysis Information source management input means for inputting information source involvement range information indicating authority, and analysis indicating the degree of universality of data analysis to be performed by the operator Analysis type input means for inputting universality information, access for data analysis to be performed by an operator based on the data universality information, the classification information, the analytical universality information, and the information source involvement range information An access authority processing unit that determines permission / denial for each type of data that is a candidate for analysis, and a target data storage unit for the access processing unit based on a determination result of the access authority processing unit Authority access means for setting the data access permission / denial information for each type of data stored in the target data storage means, and the access authority processing means is a universal information indicated by the analysis universality information. The degree of sex and the degree of universality of the data are determined to be compatible, and the operator is given access authority to the data. Whether or not based on the information source involvement range information, and access the data that resulted in both the determination result that the degree of universality does not match and the determination result that the access authority is not granted to the operator. Is selected as data that does not permit access, and data that results in at least one of the determination result that the degree of universality matches and the determination result that the access authority is granted to the operator is used as data that permits access It is characterized by selection.

Further, in one configuration example of the information processing apparatus of the present invention, the access processing means includes data access permission / output from the authority output means among the data to be analyzed that are stored in the target data storage means. Only the type of data that is permitted to be accessed by the non-permission information is read, and the read data is transferred to a data analysis processing unit that performs analysis processing.
Further, in one configuration example of the information processing apparatus of the present invention, the access authority processing unit converts the data universality information corresponding to the candidate data to be analyzed stored in the target data storage unit to the data universality information. The classification information corresponding to the data universality information obtained from the storage means is obtained from the classification information storage means, a group to which the candidate data to be analyzed belongs is determined, and the universality indicated by the analysis universality information It is characterized in that it is determined whether or not the degree of sex and the degree of universality of the group to which the data that is the candidate for analysis belongs match.

In one configuration example of the information processing apparatus of the present invention, the analysis type input unit inputs the analysis universality information corresponding to the analysis type name or analysis type number selected or input by the operator to the access authority processing unit. It is characterized by doing.
In addition, one configuration example of the information processing apparatus according to the present invention further includes time-series data of the set value SP of the PID control loop and the control amount PV among the data as analysis target candidates stored in the target data storage unit. The data universality information setting means for automatically registering the data universality information indicating that the degree of universality is lower than the central value of the degree of universality in the data universality information storage means It is what.
Further, one configuration example of the information processing apparatus according to the present invention further includes universality for time series data of the manipulated variable MV of the PID control loop among the data to be analyzed candidates stored in the target data storage unit. The data universality information setting means for automatically registering the data universality information indicating that the degree of universality is higher than the central value of the degree of data in the data universality information storage means, is there.

  The information processing method according to the present invention includes an information source management input step for inputting information source involvement range information indicating the authority of an operator with respect to an information source of data that is a candidate for analysis, and a data analysis that the operator intends to perform. An analysis type input step for inputting analysis universality information indicating the degree of universality, target data storage means for storing one or more types of data that are candidates for analysis collected from one or more information sources, and data Data universality information storage means for preliminarily storing data universality information indicating the degree of universality of data for each type, and classification information for classifying the candidate data to be analyzed into a plurality of groups in advance Classification information storage means, and based on the data universality information, the classification information, the analysis universality information, and the information source involvement range information, Based on the access authority processing step for determining the access permission / non-permission for data analysis to be performed by the data for each type of data to be the analysis target, and the determination result of this access authority processing step, An authority output step for setting, for each type of data stored in the target data storage means, setting of data access permission / non-permission information to the target data storage means for the access processing means, The step determines whether or not the degree of universality indicated by the analysis universality information and the degree of universality of the data are compatible, and further determines whether or not the operator is given access authority to the data. Judgment based on the source involvement range information, the judgment result that the degree of universality does not fit, and the access authority is granted to the operator The data that resulted in both of the determination results of not being selected is selected as data that does not permit access, and among the determination results that the degree of universality is suitable and the determination result that the operator has access authority Data in which at least one result is generated is selected as data that permits access.

  According to the present invention, target data storage means, access processing means, data universality information storage means, classification information storage means, information source management input means, analysis type input means, access authority processing means, By providing an authority output means, it is possible to realize security management based on the premise that analysis is performed on big data. When performing analysis on big data, it is related to data access authority. Inefficiency can be reduced.

  Also, in the present invention, only the types of data whose access is permitted by the data access permission / non-permission information from the authority output means are read out from among the analysis target candidates stored in the target data storage means. By providing the access processing means for passing the read data to the data analysis processing means, the access processing means can control the data access for the data analysis that the operator intends to perform, and the access authority to the data At the same time as reducing inefficiency, the possibility of problems such as data leakage can be reduced.

  In the present invention, the data universality information indicating that the degree of universality is lower than the central value of the degree of universality for the time series data of the set value SP of the PID control loop and the control amount PV is the data universality information. By providing the data universality information setting means that automatically registers in the storage means, it is possible to reduce the work burden on the person who sets the data universality information.

  In the present invention, the data universality information indicating that the degree of universality is higher than the central value of the degree of universality is automatically stored in the data universality information storage means for the time series data of the manipulated variable MV of the PID control loop. By providing data universality information setting means for registering data universally, it is possible to reduce the work burden on the person who sets the data universality information.

It is a figure explaining the principle of this invention. It is a block diagram which shows the structure of the information processing apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart explaining operation | movement of the information processing apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart explaining operation | movement of the access authority process part of the information processing apparatus which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the structure of the information processing apparatus which concerns on the 2nd Embodiment of this invention. It is a figure which shows the example of the time series data of the setting value of PID control loop, control amount, and operation amount.

[Principle of Invention 1]
As a case where big data occurs, the inventor becomes big data when the number of information sources is large, or becomes big data when the number of information from one information source is large. Focused on being there. FIG. 1 is a diagram for explaining the principle of the present invention, and is a diagram in which big data generation modes are classified. In FIG. 1, in order to schematically explain the generation of big data, the number of big data is reduced to 100.

  As shown in FIG. 1, the generation form of big data can be expressed in such a manner as 1 × 100 type, 10 × 10 type, 100 × 1 type, for example. The 1 × 100 type is a form in which one data is generated from one information source S. In this case, there are a large number of information sources S corresponding to the number of big data. As a typical information source S of 1 × 100 type, an individual consumer of a mass-produced product of BtoC (Business-to-Consumer) can be considered.

  The 10 × 10 type is a form in which an appropriate amount of data is generated from each appropriate amount of information source S. As this typical information source S of 10 × 10 type, BtoC or BtoB (Business to Business) general equipment (for example, equipment such as air conditioning equipment) can be considered.

  The 100 × 1 type is a form in which a large amount of data is generated from one information source S. As a typical information source S of the 100 × 1 type, a dedicated BtoB manufacturing apparatus (for example, a semiconductor manufacturing apparatus or a chemical manufacturing plant) can be considered.

  In addition, although the example of FIG. 1 is an example expressing both extreme forms (1 × 100 type, 100 × 1 type) and an intermediate form (10 × 10 type), the intermediate form is 10 × 10. The number of information sources S and the number of types of data per information source are not only the same number as in the type, but for example, 2 × 50 type, 4 × 25 type, 25 × 4 type, 20 × 5 type, etc. In addition, it should be considered that further intermediate forms exist continuously.

  Here, the big data in the case corresponding to the 1 × 100 type to the 10 × 10 type (upper form in FIG. 1) is data having the property that the common characteristic between a plurality of information sources is the object of analysis. is there. Although it is clear when considered in the form of a 1 × 100 type in particular, the data obtained from each information source S cannot be sufficient to analyze the characteristics limited to the individual information sources S.

  On the other hand, the big data in the case corresponding to approximately 10 × 10 type to 100 × 1 type (the lower form in FIG. 1) is easily reflected in the data with characteristics peculiar to individual information sources S. It is data of the property that common characteristics between sources are excluded from analysis. Although it is clear when considered in the form of a 100 × 1 type in particular, the data obtained from the information source S cannot be data sufficient to analyze the common characteristics between a plurality of information sources.

  Based on the characteristics of the data as described above, the possibility of the existence of common characteristics between information sources is estimated. The data is subject to monitoring according to laws and regulations or industry and corporate standard provisions. In the case of data on a small amount of non-business information (for example, information from standard functions in equipment), it is considered that common characteristics between information sources are likely to exist. On the other hand, common data characteristics between information sources cannot be expected for data that has a large room for “arbitrary” depending on site conditions and operator's feelings. And the more data that this common characteristic cannot be expected, the more it should not be accessed in the case of an open tendency that analyzes the common characteristic.

  Therefore, information indicating the degree of universality of data, such as “legal regulations” and “business”, is registered in advance, and the operator wants to perform an analysis with a high degree of universality, such as power demand prediction. The access authority is adjusted so that data that is suitable only for analysis with a low degree of universality is not accessed. Conversely, when an operator is trying to perform an analysis with a high degree of private (private enterprise) and low degree of universality, such as product quality control analysis, only analysis with a high degree of universality is required. The access authority is adjusted so that suitable data is not accessed. By doing in this way, it came to the idea that inefficiency related to access authority can be reduced when performing analysis for big data.

[Principle of Invention 2]
The time-series data of the set value SP and control amount PV of the PID control loop is so-called recipe information in most cases if it is a manufacturing device in a factory. Therefore, unless there is a specific operation, the degree of universality is automatically low. It is preferable that the information indicating is registered.
On the other hand, the manipulated variable MV is used as energy management information and is related to the Energy Saving Law, etc., so that information indicating a high degree of universality is automatically registered unless there is a specific operation. It is preferable to do so.

  When analyzing the dynamic characteristics unique to the manufacturing apparatus, it is conceivable that a mathematical model of the dynamic characteristics of the manufacturing apparatus is constructed and analyzed using the control amount PV and the manipulated variable MV. Analysis of dynamic characteristics unique to manufacturing equipment is regarded as an analysis with low universality. Even if information indicating that the degree of universality is high is added to the manipulated variable MV as described above, information indicating that the degree of universality is low is set in the control amount PV. Since the access authority for analyzing is substantially low in the level of universality, no problem arises.

[First Embodiment]
Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 2 is a block diagram showing the configuration of the information processing apparatus according to the first embodiment of the present invention. The present embodiment is an example corresponding to Principle 1 of the invention described above.

  The information processing apparatus performs a target data storage unit 1 that stores one or more types of data that are candidates for analysis collected from one or more information sources, and an access process for data stored in the target data storage unit 1. An access processing unit 2 to be executed, a data universality information storage unit 3 for storing data universality information indicating the degree of universality of data for each type of data stored in the target data storage unit 1, and a data universal Based on the data universality information stored in the sex information storage unit 3, a classification information storage unit 4 that stores classification information for classifying data that is candidates for analysis into a plurality of groups, and candidates for analysis An information source management input unit 5 for inputting information source involvement range information indicating the authority of the operator with respect to an information source of the data, and a degree of universality of data analysis to be performed by the operator Based on the analysis type input unit 6 for inputting the analysis universality information, the data universality information, the classification information, the analysis universality information, and the information source involvement range information, access permission / Based on the determination result of the access authority processing unit 7 and the access authority processing unit 7 that determines the disapproval for each type of data to be analyzed, the data to the target data storage unit 1 for the access processing unit 2 An authority output unit 8 for setting access permission / denial information for each type of data stored in the target data storage unit 1, an input device 9 for an operator to give an instruction to the information processing device, And a data analysis processing unit 10 for performing the analysis processing.

  Hereinafter, the operation of the information processing apparatus according to the present embodiment will be described with reference to FIG. First, the target data storage unit 1 stores data as analysis target candidates collected from one or more information sources (not shown) (step S100 in FIG. 3).

  For example, air conditioning power time series data A-1, air conditioning set temperature time series data A-2, air conditioning supply air temperature time series data A-3, air conditioning supply air flow rate from an information source called air conditioner A in a factory production line It is assumed that four types of data, series data A-4, are collected and stored in the target data storage unit 1.

  In addition, from the information source of the air conditioner B of the factory production line, the air conditioning power time series data B-1, the air conditioning set temperature time series data B-2, the air conditioning supply temperature time series data B-3, and the air conditioning supply air volume It is assumed that four types of data called series data B-4 are collected and stored in the target data storage unit 1.

  In addition, from the information source of the air conditioner C of the factory production line, the air conditioning power time series data C-1, the air conditioning set temperature time series data C-2, the air conditioning supply temperature time series data C-3, the air conditioning supply air volume time It is assumed that four types of data called series data C-4 are collected and stored in the target data storage unit 1.

  Also, from the information source of the heat treatment device D of the factory production line, the device power time series data D-1, the heating zone X temperature time series data D-2, the heating zone X heater output time series data D-3, the heating zone It is assumed that five types of data, Y temperature time series data D-4 and heating zone Y heater output time series data D-5, are collected and stored in the target data storage unit 1. Here, the heat treatment apparatus D has two temperature control zones called heating zones X and Y, and the temperature (° C.) and heater output (%) data are acquired for each zone as an example. .

  Furthermore, from the information source of the cooling processing device E of the factory production line, the device power time series data E-1, the cooling zone Z temperature time series data E-2, the cooling zone Z refrigerator output time series data E-3, the cooling It is assumed that five types of data, zone W temperature time series data E-4 and cooling zone W refrigerator output time series data E-5, are collected and stored in the target data storage unit 1. Here, the cooling processing apparatus E has two temperature control zones called cooling zones Z and W, and the temperature (° C.) and refrigerator output (%) data are acquired for each zone as an example. Yes.

  In the above example, the data stored in the target data storage unit 1 is time series data, but it may be single-shot data. It goes without saying that identification information for identifying the type of data is added to each data.

  In addition, the information processing apparatus according to the present embodiment only needs to store data collected by data collection means (not shown), and data collection means need only be completed before analysis is started. It can be applied regardless of the type.

  Next, in the data universality information storage unit 3, data universality information is registered in advance for each known type of data stored in the target data storage unit 1. Here, it is defined by public standards and guidelines such as laws (Energy Conservation Law), GMP (Good Manufacturing Practice), JIS (Japanese Industrial Standards) and HACCP (Hazard Analysis and Critical Control Point), industry standards, and common sense. Data has a high degree of universality.

  In addition, since at least a part of the data obtained from the information sources such as the air conditioners A to C is often subjected to some regulation such as a law, an official standard, a guideline, an industry standard, and an in-house standard, the degree of universality Becomes higher. In addition, since at least a part of the data obtained from the manufacturing apparatus such as the heat processing apparatus D and the cooling processing apparatus E is often special data specialized for product production, the degree of universality is low. Become.

  For example, the data universality information storage unit 3 indicates that these data are regulated by law as data universality information of the air conditioning power time series data A-1 and the air conditioning set temperature time series data A-2. Information “regulatory management target” is stored. Further, in the data universality information storage unit 3, these data are not regulated by law as data universality information of the air conditioning supply air temperature time series data A-3 and the air conditioning supply air flow time series data A-4. However, information “standard regulation management target” indicating that it is subject to regulations such as public standards, guidelines, industry standards, and in-house standards is stored.

  The data universality information storage unit 3 also includes air conditioning power time series data B-1, air conditioning set temperature time series data B-2, air conditioning power time series data C-1, and air conditioning set temperature time series data C-2. As data universality information, information “regulatory control target” is stored, and air-conditioning supply air temperature time-series data B-3, air-conditioning supply air volume time-series data B-4, air-conditioning supply temperature time-series data C- 3 and information “standard regulation management object” is stored as data universality information of the air-conditioning supply air volume time series data C-4.

  The data universality information storage unit 3 stores information “regulatory management target” as data universality information of the apparatus power time-series data D-1 and the apparatus power time-series data E-1. X temperature time series data D-2, heating zone X heater output time series data D-3, heating zone Y temperature time series data D-4, heating zone Y heater output time series data D-5, cooling zone Z temperature time series As data universality information of data E-2, cooling zone Z refrigerator output time series data E-3, cooling zone W temperature time series data E-4, and cooling zone W refrigerator output time series data E-5, these Is stored as information “object characteristic monitoring work target” indicating that the data is special data specialized in product production. Table 1 summarizes the above data universality information.

  In this embodiment, in order from the highest degree of universality, data regulated by law → data regulated by public standards and guidelines → data regulated by industry standards → regulated by company standards Data properties are defined in the order of data → special data regulated by product quality. However, in the present embodiment, the degree of universality indicated by the data universality information is divided into three stages in order to simplify the description. Needless to say, the degree of universality may be divided into four or more levels.

  On the other hand, classification information for classifying data that is candidates for analysis into a plurality of groups having different degrees of universality is registered in the classification information storage unit 4 in advance. The classification information is, for example, data universal information and group identification information associated with each other. For example, data universality information “regulatory control target” is associated with identification information of the first group g1 (corresponding to 1 × 100 type to 4 × 25 type in FIG. 1) having a high degree of universality. The data universality information “standard regulation management object” is associated with the identification information of the second group g2 (corresponding to the 10 × 10 type in FIG. 1) with a medium degree of universality, Data universality information “target” is associated with identification information of the third group g3 (corresponding to 25 × 4 type to 100 × 1 type in FIG. 1) having a low degree of universality. Table 2 summarizes the above classification information.

  In the example of the present embodiment, the number of steps of the degree of universality indicated by the data universality information, and the number of steps of the degree of universality (number of groups) set for each group defined by the classification information However, it is not an essential component of the present invention to match these numbers. The design item of how many degrees of universality is set in the data universality information and the design item of how many groups the data is classified are different, and may be set individually. Further, data universality information such as “regulatory management object”, “standard regulation management object”, and “apparatus characteristic monitoring work object” is information representing the nature of the data, and registration contents of the data universality information storage unit 3 are generally While the information processing device manufacturer's person in charge and the information processing device operator set it according to the law and the convenience of the information source side, the registered contents of the classification information storage unit 4 are generally on the information processing device designer side. Information to be set. In this way, by using the data universality information and the classification information, an information processing apparatus that is easy to use for the operator can be realized.

Next, when the operator wants to start data analysis, he / she operates the input device 9 to instruct the information processing apparatus to start analysis (YES in step S101 in FIG. 3).
The information source management input unit 5 inputs information source involvement range information indicating the authority of the operator with respect to the information source of the data stored in the target data storage unit 1 at the start of data analysis (step S102 in FIG. 3). In general, the information processing apparatus identifies the operator's identity when the operator logs on to the information processing apparatus. In the information source management input unit 5, information source participation range information is registered in advance for each operator, and information source participation range information corresponding to the operator who has logged on to the information processing apparatus is input to the access authority processing unit 7.

  Note that the information source management input unit 5 provides information source involvement range information (for example, access to all data originating from each information source) indicating the specified minimum level authority when the information source involvement range information of the operator is not registered. May be input to the access authority processing unit 7.

  The analysis type input unit 6 inputs analysis universality information indicating the degree of universality of data analysis to be performed by the operator (step S103 in FIG. 3). Analysis universality information is registered in advance in the analysis type input unit 6 for each type of data analysis, and the analysis universality information corresponding to the data analysis type name input by the operator is input to the access authority processing unit 7. .

  For example, it shows that the degree of universality is high for the type names of “energy management analysis”, “labor management analysis”, and “equipment maintenance analysis” (corresponding to 1 × 100 type to 4 × 25 type in FIG. 1). Analysis universality information is set, and analysis universality information indicating that the degree of universality is moderate (corresponding to 10 × 10 type in FIG. 1) is set for the type name “hygiene management analysis”. , Analysis universality information indicating that the degree of universality is low (corresponding to 25 × 4 type to 100 × 1 type in FIG. 1) for the type names “quality control analysis” and “apparatus characteristic analysis” Has been.

  An example of actual data analysis corresponding to the type of “energy management analysis” is, for example, power demand prediction. An example of data analysis corresponding to the type of “labor management analysis” is, for example, prediction of working hours. As an example of data analysis corresponding to the type “equipment maintenance analysis”, there is, for example, prediction of filter replacement timing of an air conditioner. As an example of data analysis corresponding to the type of “sanitary management analysis”, there is, for example, food hygiene condition estimation. An example of data analysis corresponding to the type of “quality control analysis” is, for example, product strength factor analysis. An example of data analysis corresponding to the type of “device characteristic analysis” is, for example, readjustment of PID parameters of the control device. Table 3 summarizes the above analysis universality information.

  Note that the analysis universality information is for determining whether or not the universality of the data that is the candidate for analysis is compatible with the degree of universality of the data analysis, as described later. The number of steps of the degree of universality indicated by the analysis universality information needs to match the number of steps of the degree of universality (number of groups) set for each group specified by the classification information. In the present embodiment, the number of stages is three.

Further, the analysis type input unit 6 may display a plurality of analysis type names prepared in advance, and allow the operator to select a desired type name from among them.
The analysis type input unit 6 may input analysis universality information having the lowest degree of universality to the access authority processing unit 7 when the analysis type name input by the operator is not registered.

  Next, the access authority processing unit 7 acquires data universality information corresponding to the determination target data stored in the target data storage unit 1 from the data universality information storage unit 3, and corresponds to the data universality information. The classification information is acquired from the classification information storage unit 4, the group to which the data to be determined belongs is determined, the degree of universality indicated by the analysis universality information input from the analysis type input unit 6 and the data to be determined belong It is determined whether or not the degree of universality of the group is appropriate, and whether or not the operator is authorized to access the data to be determined is determined based on the information source involvement range information. Data that results in both the determination result that the degree does not fit and the determination result that the access authority is not granted to the operator is regarded as data that does not permit access The data having at least one of the determination result that the degree of universality matches and the determination result that the access authority is granted to the operator is selected as data that permits access (FIG. 3). Step S104). FIG. 4 is a flowchart for explaining the operation of the access authority processing unit 7.

  First, the access authority processing unit 7 acquires analysis universality information input from the analysis type input unit 6 (step S200 in FIG. 4). For example, it is assumed that the type of data analysis to be performed by the operator is “energy management analysis”. According to the data analysis type “energy management analysis”, analysis universality information indicating that the degree of universality is high is input from the analysis type input unit 6.

  Subsequently, the access authority processing unit 7 acquires the data universality information corresponding to the determination target data from the data universality information storage unit 3, and the classification information corresponding to the data universality information from the classification information storage unit 4. Obtaining and determining the group to which the data to be determined belongs (step S201 in FIG. 4).

  When the data to be determined is the air-conditioning power time-series data A-1, the access authority processing unit 7 sends the information “legal management target” from the data universality information storage unit 3 as the data universality information corresponding to this data. Based on the acquired data universality information and the classification information stored in the classification information storage unit 4, the air-conditioning power time-series data A-1 is classified into the first group g1 having a high degree of universality.

  In addition, when the determination target data is the heating zone X temperature time-series data D-2, the access authority processing unit 7 sets information “device characteristic monitoring work target” as data universality information corresponding to this data. Based on the data universality information and the classification information stored in the classification information storage unit 4 and obtained from the information storage unit 3, the heating group X temperature time-series data D-2 is a third group g3 having a low degree of universality. Classify into:

  Next, the access authority processing unit 7 determines whether or not the degree of universality indicated by the analysis universality information matches the degree of universality of the group to which the determination target data belongs (step S202 in FIG. 4).

  Since the analysis universality information indicating that the degree of universality is high is input from the analysis type input unit 6 according to the type of data analysis called “energy management analysis”, the access authority processing unit 7 performs the analysis universality. It is determined whether or not the degree of universality indicated by the information and the degree of universality of the first group g1 to which the air-conditioning power time series data A-1 belongs match. In this case, the access authority processing unit 7 determines that the degree of universality is appropriate because both the universality of analysis and the universality of data are high.

  When the determination target data is the heating zone X temperature time series data D-2, the access authority processing unit 7 performs the heating zone X temperature time series for the analysis universality information indicating that the degree of universality is high. Since the data D-2 is classified into the third group g3 having a low degree of universality, it is determined that the degree of universality does not match.

  In other words, in the above example, the data A-1, A-2, B-1, B-2, C-1, C-2, D-1, and E-1 are compatible with the degree of universality. Data A-3, A-4, B-3, B-4, C-3, C-4, D-2, D-3, D-4, D-5, E-2, E- 3, E-4, and E-5 are determined as data that do not match the degree of universality.

  The access authority processing unit 7 assumes that the data whose corresponding data universality information is not registered in the data universality information storage unit 3 belongs to the group with the lowest degree of universality. What is necessary is just to determine whether the degree of is suitable.

  There are two possible methods for determining whether or not the degree of universality is appropriate. In the first method, the universality of the group to which the data to be judged belongs is determined to be suitable if the degree of universality of the group to which the data to be judged belongs is equal to or greater than the degree of universality indicated by the analysis universality information. Is a non-conformity when the degree of is less than the degree of universality indicated by the analysis universality information.

  The second method determines that the degree of universality of the group to which the data to be judged belongs matches only when the degree of universality indicated by the analysis universality information is exactly the same, and the universality of the group to which the data to be judged belongs belongs. This is a method for determining non-conformity when the degree of sex does not match the degree of universality indicated by the analysis universality information. Which one of the first method and the second method is used may be appropriately set as necessary.

  Next, the access authority processing unit 7 acquires information source involvement range information input from the information source management input unit 5 (step S203 in FIG. 4). For example, it is assumed that the operator has been given access authority to all data issued from the heat treatment apparatus D.

  The access authority processing unit 7 determines whether an access authority to the determination target data is given to the operator (step S204 in FIG. 4). Since the information source involvement range information indicating that the operator has been given access authority to all data issued from the heat treatment apparatus D is input from the information source management input section 5, the access authority processing section 7 It is determined that the access authority is not given to the operator for all data originating from -C and the cooling processing apparatus E.

  That is, in the above example, the access authority is given to the operator for data D-1 to D-5, and data A-1 to A-4, B-1 to B-4, C-1 to C-. For 4 and E-1 to E-5, the access authority is not given to the operator.

  The access authority processing unit 7 determines that the degree of universality indicated by the analysis universality information does not match the degree of universality of the group to which the data to be determined belongs, and the access authority is not given to the operator. The data to be judged that produced both results of the judgment result is selected as data that does not permit access, and the degree of universality indicated by the analysis universality information and the degree of universality of the group to which the data to be judged belongs are determined. The data to be determined in which at least one of the determination result of conformity and the determination result that the access authority is granted to the operator is selected as data that permits access (step S205 in FIG. 4).

  That is, in the above example, the data A-3, A-4, B-3, B-4, C-3, C-4, and E-2 to E-5 are selected as data that does not permit access. Then, the data A-1, A-2, B-1, B-2, C-1, C-2, D-1 to D-5, and E-1 are selected as data that permits access. The access authority processing unit 7 performs the above processing for each data stored in the target data storage unit 1.

  Based on the selection result of the access authority processing unit 7, the authority output unit 8 stores in the target data storage unit 1 the setting of data access permission / non-permission information to the target data storage unit 1 for the access processing unit 2. This is performed for each type of data being stored (step S105 in FIG. 3). The data access permission / denial information may specify only the type of data that is not permitted to access, or may specify only the type of data that is permitted to access, or permit access. It is also possible to specify both the type of data that is not permitted and the type of data that is permitted to be accessed.

  The access processing unit 2 selects only the types of data whose access is permitted by the data access permission / non-permission information from the authority output unit 8 among the analysis target candidate data stored in the target data storage unit 1. The read data is transferred to the data analysis processing unit 10 as analysis target data (step S106 in FIG. 3). Note that the final access permission / denial determination may be determined using a method other than the present embodiment in combination.

  The data analysis processing unit 10 performs analysis processing on the data to be analyzed passed from the access processing unit 2 in accordance with the type name of the desired data analysis selected or input by the operator when the analysis start instruction is given. (FIG. 3, step S107). Various analysis methods have been proposed as analysis methods for big data, but the method of analysis is not an essential problem of the present invention, and the present invention does not matter the type of analysis method. Therefore, detailed description of the analysis method is omitted.

  As described above, in the present embodiment, it is possible to perform security management on the assumption that analysis is performed on big data. That is, when performing analysis for big data, it is possible to reduce inefficiency related to the authority to access data.

  In this embodiment, the security management method is changed only for data analysis, so that access can be made to data of an information source that is not originally granted access authority to the operator, so that analysis can be performed. It is necessary to pay attention to problems such as data leakage and personal information leakage.

  For example, the access processing unit 2 needs to limit the output destination of data to be analyzed to the data analysis processing unit 10 and control and monitor data access so that the data is not used for purposes other than data analysis. In the present invention, the data analysis processing unit 10 may be provided outside the information processing apparatus. However, in order to prevent the data to be analyzed from leaking outside the information processing apparatus, the installation of the data analysis processing unit 10 is information. You may limit to the inside of a processing apparatus.

  Further, when displaying the data to be analyzed and the analysis result during or after the analysis, the data analysis processing unit 10 may display the information source of the data to be analyzed so that it cannot be specified. Processing such as displaying only the analysis result may be performed so that the target data itself is not known to the operator.

[Second Embodiment]
Next, a second embodiment of the present invention will be described. FIG. 5 is a block diagram showing the configuration of the information processing apparatus according to the second embodiment of the present invention. The same components as those in FIG. This embodiment is an example corresponding to Principle 1 and Principle 2 of the invention.

  The information processing apparatus according to the present embodiment includes a target data storage unit 1, an access processing unit 2, a data universality information storage unit 3, a classification information storage unit 4, an information source management input unit 5, and an analysis type input. Unit 6, access authority processing unit 7, authority output unit 8, input device 9, data analysis processing unit 10, and data universality information setting unit 11.

  As described in the first embodiment, data universality information is information that represents the degree of universality of data and at the same time represents the nature of the data, and is determined by the convenience of the law or the information source side. It is set by the person in charge of the manufacturer or the operator of the information processing apparatus.

  However, the time series data (FIG. 6) of the set value SP (for example, temperature set value) and the control amount PV (for example, temperature measured value) of the PID control loop is so-called recipe information in most cases if it is a manufacturing apparatus in a factory. Unless otherwise specified, data universality information indicating that the degree of universality is lower than a predetermined central value of the degree of universality (“device characteristic monitoring work target” in the example of the first embodiment) Is preferably registered automatically.

  On the other hand, the time-series data (FIG. 6) of the manipulated variable MV (for example, heater output, refrigerator output) is of a property used as energy management information and is related to the Energy Saving Law and so on unless otherwise specified. Data universality information indicating that the degree of universality is higher than a predetermined central value of the degree of universality (“regulatory management target” in the example of the first embodiment) is automatically registered. It is preferable to keep it.

  That is, when the data universality information is registered in the data universality information storage unit 3 by the person in charge of the information processing device manufacturer or the operator of the information processing device, the data universality information setting unit 11 Data universality information for at least some of the data is automatically registered.

  Explaining with the example of data of the first embodiment, the heating zone X temperature time series data D-2 and the heating zone Y temperature time series data D-4 indicate the temperatures of the heating zones X and Y of the heat treatment apparatus D, respectively. This is the control amount PV acquired by the temperature sensor in the PID control loop to be controlled. Therefore, the data universality information setting unit 11 sets the data universality information as “apparatus characteristic monitoring work target” for the heating zone X temperature time series data D-2 and the heating zone Y temperature time series data D-4. Register in the storage unit 3.

  The heating zone X heater output time series data D-3 and the heating zone Y heater output time series data D-5 are the controllers (temperatures) in the PID control loop that controls the temperatures of the heating zones X and Y of the heat treatment apparatus D. The operation amount MV is output from the control. Accordingly, the data universality information setting unit 11 sets the data universality information “regulatory control target” for the heating zone X heater output time series data D-3 and the heating zone Y heater output time series data D-5. Register in the information storage unit 3.

  Note that the controller that controls the temperature of the heating zone X of the heat treatment apparatus D is the heating zone X heater output time series so that the set value SP of the heating zone X matches the heating zone X temperature time series data D-2. Data D-3 is calculated and output to the heater in the heating zone X. Further, the controller that controls the temperature of the heating zone Y sets the heating zone Y heater output time series data D-5 so that the set value SP of the heating zone Y matches the heating zone Y temperature time series data D-4. Calculate and output to the heater in the heating zone Y.

  Similarly, the cooling zone Z temperature time series data E-2 and the cooling zone W temperature time series data E-4 are acquired by a temperature sensor in a PID control loop that controls the temperatures of the cooling zones Z and W of the cooling processing apparatus E. This is the controlled amount PV. Therefore, the data universality information setting unit 11 sets the data universality information as “apparatus characteristic monitoring work target” for the cooling zone Z temperature time series data E-2 and the cooling zone W temperature time series data E-4. Register in the storage unit 3.

  The cooling zone Z refrigerator output time series data E-3 and the cooling zone W refrigerator output time series data E-5 are the controllers in the PID control loop that controls the temperatures of the cooling zones Z and W of the cooling processing apparatus E. This is the operation amount MV output from the (temperature controller). Therefore, the data universality information setting unit 11 sets the data universality information “regulatory control target” for the cooling zone Z refrigerator output time series data E-3 and the cooling zone W refrigerator output time series data E-5. Register in the universality information storage unit 3.

  The controller that controls the temperature of the cooling zone Z of the cooling processing apparatus E is the cooling zone Z refrigerator output time series data so that the set value SP of the cooling zone Z matches the cooling zone Z temperature time series data E-2. E-3 is calculated and output to the refrigerator in the cooling zone Z. The controller that controls the temperature of the cooling zone W also outputs the cooling zone W refrigerator output time series data E-5 so that the set value SP of the cooling zone W matches the cooling zone W temperature time series data E-4. Is output to the refrigerator in the cooling zone W.

  Table 4 shows the data universality information registered in the data universality information storage unit 3 in an organized manner.

The data universality information different from Table 1 is automatically set by the data universality information setting unit 11 as described above.
The operation of the configuration other than the data universality information setting unit 11 is as described in the first embodiment.

Thus, in this embodiment, it is possible to reduce the work burden on the person who sets data universality information.
When analyzing the dynamic characteristics unique to the manufacturing apparatus, it is conceivable that a mathematical model of the dynamic characteristics of the manufacturing apparatus is constructed and analyzed using the control amount PV and the manipulated variable MV. The analysis of the dynamic characteristic unique to the manufacturing apparatus corresponds to “apparatus characteristic analysis” in the example of the first embodiment, and therefore analysis universality information with the lowest degree of universality is input to the access authority processing unit 7. Is done.

  Even if the data universality information setting unit 11 of the present embodiment gives the data universality information “regulatory control target” indicating that the degree of universality is high to the manipulated variable MV, Since the data universality information of “Device characteristics monitoring work object” indicating that the degree is low is set, the access authority for analyzing the dynamic characteristics unique to the manufacturing equipment is substantially “Device characteristics monitoring work object”. It becomes the level of. Therefore, if the first method is adopted as a method for determining whether or not the degree of universality is suitable, both the control amount PV and the operation amount MV can be accessed, and no problem occurs.

  In this embodiment, the degree of universality is divided into three stages. However, as described in the first embodiment, the degree of universality may be divided into four or more stages. In this embodiment, data universality information indicating that the degree of universality is the lowest is set for the set value SP and the control amount PV. However, when the degree of universality is divided into four or more levels, the minimum value is used. A high level of universality may also be set. Similarly, although data universality information indicating that the degree of universality is the highest is set for the operation amount MV, a degree of universality at a level lower than the maximum value may be set.

Needless to say, the data universality information is prioritized by manual setting by the person in charge of the manufacturer of the information processing apparatus or the operator of the information processing apparatus.
For example, if the manufacturer's person or operator selects manual setting when registering data universality information, the data universality information input via the input device 9 is registered in the data universality information storage unit 3. Further, after the data universality information setting unit 11 automatically registers, the person in charge or operator of the manufacturer may manually rewrite the data universality information.

  In the first and second embodiments, the analysis type input unit 6 displays a plurality of analysis type numbers prepared in advance, instead of the analysis type name, and the desired analysis type number is displayed to the operator from among them. And the analysis universality information corresponding to the analysis type number may be input to the access authority processing unit 7. Further, the analysis type number may be input by the operator.

  The information processing apparatus described in the first and second embodiments can be realized by a computer having a CPU (Central Processing Unit), a storage device, and an interface, and a program for controlling these hardware resources. The CPU executes the processing described in the first and second embodiments in accordance with a program stored in the storage device.

  The present invention can be applied to a technique for analyzing big data.

  DESCRIPTION OF SYMBOLS 1 ... Object data storage part, 2 ... Access processing part, 3 ... Data universality information storage part, 4 ... Classification information storage part, 5 ... Information source management input part, 6 ... Analysis classification input part, 7 ... Access authority processing part 8 ... Authority output unit, 9 ... Input device, 10 ... Data analysis processing unit, 11 ... Data universality information setting unit.

Claims (12)

Target data storage means for storing one or more types of data that are candidates for analysis collected from one or more information sources;
Access processing means for executing access processing for data stored in the target data storage means;
Data universality information storage means for preliminarily storing data universality information indicating the degree of universality of data for each type of data stored in the target data storage means;
Based on the data universality information, classification information storage means for previously storing classification information for classifying the candidate data to be analyzed into a plurality of groups;
Information source management input means for inputting information source involvement range information indicating the authority of the operator with respect to the information source of the candidate data to be analyzed;
An analysis type input means for inputting analysis universality information indicating the degree of universality of data analysis to be performed by the operator;
Based on the data universality information, the classification information, the analysis universality information, and the information source participation range information, access permission / nonpermission for data analysis that an operator intends to perform is determined as the analysis target candidate. Access authority processing means for determining for each type of data,
Based on the determination result of the access authority processing means, the setting of data access permission / non-permission information to the target data storage means for the access processing means is set for each type of data stored in the target data storage means. And authority output means
The access authority processing means determines whether or not the degree of universality indicated by the analysis universality information and the degree of universality of the data are compatible, and whether or not the operator has authority to access the data. Is determined based on the information source involvement range information, and access is made to data in which both the determination result that the degree of universality does not match and the determination result that the access authority is not granted to the operator are generated. Select data that is permitted to be accessed, and select data that results in at least one of the determination result that the degree of universality is appropriate and the determination result that the operator has access authority. An information processing apparatus characterized by: The information processing apparatus according to claim 1,
The access processing means includes only data of a type that is permitted to be accessed by data access permission / non-permission information from the authority output means, among the candidate data to be analyzed stored in the target data storage means. And processing the read data to a data analysis processing means for performing an analysis process. The information processing apparatus according to claim 1 or 2,
The access authority processing unit obtains data universality information corresponding to data to be analyzed candidates stored in the target data storage unit from the data universality information storage unit, and corresponds to the data universality information. The classification information is acquired from the classification information storage means, the group to which the analysis target candidate data belongs is determined, and the degree of universality indicated by the analysis universality information and the analysis target candidate data belong to An information processing apparatus for determining whether or not a degree of universality of a group is suitable. The information processing apparatus according to any one of claims 1 to 3,
The analysis type input unit inputs the analysis universality information corresponding to an analysis type name or an analysis type number selected or input by an operator to the access authority processing unit. The information processing apparatus according to any one of claims 1 to 4,
Further, among the candidate data to be analyzed stored in the target data storage means, the time series data of the setting value SP of the PID control loop and the control amount PV is more universal than the central value of the degree of universality. An information processing apparatus comprising: data universality information setting means for automatically registering the data universality information indicating that the degree is low in the data universality information storage means. The information processing apparatus according to any one of claims 1 to 4,
Further, among the candidate data to be analyzed stored in the target data storage means, the time series data of the manipulated variable MV of the PID control loop has a higher degree of universality than the central value of the degree of universality. An information processing apparatus comprising data universality information setting means for automatically registering the data universality information indicating the data universality information in the data universality information storage means. An information source management input step for inputting information source involvement range information indicating the authority of the operator with respect to the information source of the data to be analyzed
An analysis type input step for inputting analysis universality information indicating the degree of universality of data analysis to be performed by the operator;
Target data storage means for storing one or more types of data that are candidates for analysis collected from one or more information sources, and data universality information indicating the degree of data universality for each data type are stored in advance Data universality information storage means, and classification information storage means for previously storing classification information for classifying the candidate data to be analyzed into a plurality of groups, the data universality information and the classification information And access permission / non-permission for analyzing data to be performed by the operator based on the analysis universality information and the information source participation range information, for each type of data to be analyzed An authorization processing step;
Based on the determination result of this access authority processing step, the setting of the data access permission / non-permission information to the target data storage means for the access processing means is set for each type of data stored in the target data storage means. An authority output step to perform,
In the access authority processing step, it is determined whether or not the degree of universality indicated by the analysis universality information and the degree of universality of the data are compatible, and further whether or not the authority to access the data is given to the operator. Is determined based on the information source involvement range information, and access is made to data in which both the determination result that the degree of universality does not match and the determination result that the access authority is not granted to the operator are generated. Select data that is permitted to be accessed, and select data that results in at least one of the determination result that the degree of universality is appropriate and the determination result that the operator has access authority. An information processing method characterized by: The information processing method according to claim 7,
Furthermore, among the data as analysis target candidates stored in the target data storage unit, the type of access permitted by the data access permission / denial information set in the access processing unit in the authority output step An information processing method comprising: an access processing step of reading out only the data and passing the read data to a data analysis processing means for performing analysis processing. The information processing method according to claim 7 or 8,
The access authority processing step obtains data universality information corresponding to analysis target candidate data stored in the target data storage means from the data universality information storage means, and corresponds to the data universality information. The classification information is acquired from the classification information storage means, the group to which the analysis target candidate data belongs is determined, and the degree of universality indicated by the analysis universality information and the analysis target candidate data belong to An information processing method comprising a step of determining whether or not a degree of universality of a group is compatible. The information processing method according to any one of claims 7 to 9,
The analysis type input step includes a step of inputting the analysis universality information corresponding to an analysis type name or an analysis type number selected or input by an operator for the access authority processing step. . The information processing method according to any one of claims 7 to 10,
Further, among the candidate data to be analyzed stored in the target data storage means, the time series data of the setting value SP of the PID control loop and the control amount PV is more universal than the central value of the degree of universality. An information processing method comprising a data universality information setting step of automatically registering the data universality information indicating a low degree in the data universality information storage means. The information processing method according to any one of claims 7 to 10,
Further, among the candidate data to be analyzed stored in the target data storage means, the time series data of the manipulated variable MV of the PID control loop has a higher degree of universality than the central value of the degree of universality. And a data universality information setting step of automatically registering the data universality information indicating the data universality information in the data universality information storage means.

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