Patent Publication Number: US-2020293030-A1

Title: Data management system and data management method

Description:
BACKGROUND 
     The present invention relates to a data management system and a data management method. For example, it relates to a technique suitable for data management for obtaining IoT data on site such as a manufacture line in a factory and providing services using the obtained IoT data. 
     Nowadays, in the social infrastructure field of railway, electric power, gas, and the like and the industrial field including a manufacturing plant, for realization of sophistication of maintenance, optimum transportation, and creation of new services by using data, application of Internet of Things (IoT) and big data analysis to services is expected. On the other hand, data formats from various devices and sensors used on site are various and even the same kind of data is often managed under different items or names in business systems. To analyze them together, preparation such as standardization of formats and data integration is necessary. Generally, it is said that such preparation work is a major part in an entire data analysis work and is an obstacle when data analysis is applied to business. 
     Consequently, it is demanded to streamline the analysis data preparation work which is said a major part in an entire data analysis work such as standardization of data formats and integration of data managed under different items or names. 
     In the manufacturing industry, for data analysis using an IoT platform (PF), a key performance indicator (KPI) group regarding manufacture is hierarchically managed as overall equipment effectiveness (OEE). For example, in the case of a manufacture line, it has to be properly presented to the managers of the manufacture line and layers of programmable logic controllers (PLCs) or the like constructing the manufacture line. 
     However, in reuse of an analysis application, long manhour is required for verification of applicability of the analysis application for reasons such that an application is not set as a part and IoT data to be applied cannot be retrieved. It is said that the manhour occupies about 50 percent of new development of an analysis application. 
     For example, Japanese Unexamined Patent Application Publication No. 2018-72958 (patent literature 1) discloses a data providing device of providing on-site data to a service device, which stores description information of on-site data including specifications of on-site data, description information of services including specifications of on-site data required by services and the on-site data, and a conversion rule for converting the specification of on-site data to the specification required by a service using the on-site data, which are preliminarily registered. In response to an on-site data transfer request from a service device, the data providing device converts all of on-site data used by a service provided by the service device to data in the specification required by the service with reference to the description information of the on-site data, the description information of the service, and the conversion rule and transmits the converted data to the service device. 
     SUMMARY 
     In the technique described in the patent literature 1, it is necessary to explicitly designate description information of a service including on-site data required by a service and the specification of the on-site data and a conversion rule to convert the specification of on-site data to a specification required by a service using the on-site data. For the designation, a specification of on-site data, a specification required by a service, and a corresponding relation and a converting method of them have to be grasped and specialized knowledge is necessary. 
     An object of the present invention is to provide a data management system and a data management method realizing reuse of an analysis application having different contexts such as data units and data acquisition times of on-site data (for example, data of PLCs) in short man-hour without requiring specialized knowledge on an object to be analyzed, for example, a manufacture line or PLCs constructing a manufacture line. 
     To achieve the object, an embodiment of a data management system of the present invention is a data management system providing IoT data to a service system, which includes a storage device storing an asset catalog in which information of a manufacture line and devices constructing a manufacture line is written as an asset, an application catalog in which calculation information of a KPI as a requirement specification of the service system is written, and a data catalog in which information for accessing the IoT data is written. A control unit of the data management system retrieves an asset to be analyzed from the asset catalog and, when a KPI does not exist in the searched asset catalog, retrieves KPI calculation information from the application catalog, and calculates a KPI of the asset to be analyzed as the KPI as the requirement specification of the service system by using the retrieved KPI calculation information. 
     According to the present invention, reuse of an analysis application having different contexts such as data units and data acquisition times of on-site data (for example, data of PLCs) can be realized in short man-hour without requiring specialized knowledge on an object to be analyzed, for example, a manufacture line or PLCs constructing a manufacture line. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram illustrating an example of a system configuration diagram of an embodiment. 
         FIG. 2  is a diagram illustrating an example of a hardware configuration diagram of the system of the embodiment. 
         FIG. 3  is a diagram illustrating an asset catalog of the embodiment. 
         FIG. 4  is a diagram illustrating an example of a data catalog of the embodiment. 
         FIG. 5  is a diagram illustrating an application catalog of the embodiment. 
         FIG. 6  is a diagram illustrating an example of a display screen of a data management system of the embodiment. 
         FIG. 7  is a diagram illustrating an example of the display screen of the data management system of the embodiment. 
         FIG. 8  is a diagram illustrating an example of the display screen of the data management system of the embodiment. 
         FIG. 9  is a diagram illustrating an example of a process flow of the data management system of the embodiment. 
         FIG. 10  is a diagram illustrating an example of the process flow of the data management system of the embodiment. 
         FIG. 11  is a diagram illustrating an example of the process flow of the data management system of the embodiment. 
         FIG. 12  is a diagram explaining a method of calculating a throughput of a PLC from a timestamp and a counter value of the asset catalog of the embodiment. 
         FIG. 13  is a diagram explaining a method of calculating a KPI of a line from KPIs of devices constructing the line. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments will be described with reference to the drawings. However, the embodiment which will be described hereinafter does not limit the invention according to the scope of the claims of the invention, and all of elements and combinations of the elements described in the embodiment are not always necessary for the solving means of the invention. 
     In the following description, information will be described by expression of “AAA table”. However, information may be expressed by any data structure. Since information does not depend on a data structure, “AAA table” can be described as “AAA information”. 
     In the following description, “CPU” is a central processing unit including one or more processors. A processor may include a hardware circuit performing a part or all of a process. 
     In the following description, there is a case that a process is described using “program” as the main of operation. However, since a program is executed by a CPU to perform a predetermined process while properly using a storage resource (for example, memory) or the like, the main of the actual process is the CPU. Therefore, the process described using the program as the main of the operation may be also described that the processor is the main of the process. A part or all of processes performed by a processor may be performed by hardware circuits such as an application specific integrated circuit (ASIC) or a field-programmable gate array (FPGA). 
     A computer program may be installed from a program source to a device. A program source may be, for example, a program distribution server or a storage medium which can be read by a computer. 
     Outline 
     The outline of a system of the embodiment will be described with reference to  FIG. 1 . The system of the embodiment has an on-site system  40  generating on-site IoT data, a data lake system  50  storing converted IoT data obtained by converting the on-site IoT data to a context of an analysis application, a data management system  10  obtaining the on-site IoT data and the converted IoT data and automatically generating a key performance indicator (KPI) related to production, a service system  20  analyzing the on-site IoT data by the KPI generated by the data management system, and a client terminal  30  providing an analysis result of analysis of the on-site IoT data by the service system to the user. 
     The data management system  10  has an asset catalog management unit  102  managing an asset catalog in which information of a manufacture line and devices constructing a manufacture line is written, an application catalog management unit  104  managing an application catalog in which calculation information of a KPI is written, a data catalog management unit  106  managing a data catalog in which the locations of on-site IoT data and converted IoT data are written, and a KPI management unit  110 . 
     The KPI management unit  110  obtains an asset catalog, retrieves a KPI as a measurement reference and, when the obtained asset catalog does not include a KPI, repeats the retrieval of a KPI with reference to an application catalog, thereby automatically generating a desired KPI. 
     &lt;Description of Terms&gt; 
     
         
         On-site IoT data: On-site data generated by the on-site system. For example, time information such as a timestamp, a counter value indicating the number of processes, and the like generated by a device as a component of a manufacture line. 
         Converted IoT data: IoT data obtained by converting on-site IoT data to a context of an analysis application. 
         IoT data: On-site IoT data and converted IoT data. 
         Asset catalog: Information of a manufacture line and devices constructing a manufacture line. For example, in the case of setting devices constructing a manufacture line as assets, names of the devices, information of parts constructing the devices, and identifiers (IDs) of data catalogs indicating storage locations of operation data and the like of the devices are included. 
         Application catalog: Data in which calculation information of a KPI as a requirement specification of the service system is written. For example, it is data which describes, to obtain a throughput of a manufacture line, that it is sufficient to calculate devices constructing the manufacture line and the throughput of the devices. 
         Requirement specification of service system: Specification of a KPI which becomes necessary when the user performs analysis. For example, in the case of obtaining a throughput of a manufacture line, it corresponds to a combination of a line as an asset and a throughput as a KPI. Also in designation of a plurality of devices like “lines”, a line itself may be designated like a “line” asset. 
         Throughput: Amount of process which can be performed in unit time. For example, it expresses the number of processes which can be performed in unit time by an on-site device such as a work robot. A PLC measures the amount of process performed by an on-site device and transmits it to the data management system. 
         Context: Information describing IoT data such as unit and acquisition date and time. For example, it is a counter value indicating the number of processes performed by an on-site device and Japan standard time (JST). 
         Data catalog: Information indicating the storage location of IoT data. For example, as storage locations, an IP address as information necessary for the data management system to access IoT data, a database name, and a table of a database are included. 
         KPI: A key performance indicator of a manufacturing site. In the embodiment, it is an analysis result desired by the user, for example, a throughput of a manufacture line made by a plurality of PLCs. In the embodiment, a problem that KPIs to be obtained are different among layers of a process manager and a line manager, and manhour to provide desired KPIs to the managers in the layers is required, is solved. 
         KPI management unit: It performs a recursion execution process of various catalog association. It performs a process of obtaining a KPI required by an analysis application of a service system by making information of various catalogs associated. 
         Desired KPI: A KPI required by an analysis application of a service system. 
       
    
     Embodiment 
     System Configuration 
     First, a system according to an embodiment of the present invention will be described. 
       FIG. 1  is a diagram illustrating an example of a system configuration diagram of the embodiment. 
     A system  1  has: the on-site system  40  generating data such as various sensor data as on-site IoT data; the data lake system  50  storing data (converted IoT data) obtained by converting the on-site IoT data to a context of an analysis application; the data management system  10  obtaining IoT data made by the on-site IoT data and the converted IoT data and automatically generating a KPI; the service system  20  analyzing the on-site IoT data by the KPI generated by the data management system; and the client terminal  30  providing a result of analysis of the on-site IoT data by the service system  20  to the user. In the specification, the on-site IoT data and the converted IoT data will be called IoT data as an inclusive term. 
     In  FIG. 1 , the data lake system  50 , the data management system  10 , the service system  20 , and the client terminal  30  are illustrated as different hardware. However, a part or all of the systems and the terminal may be provided for a single computer or may be configured by using cloud computing. 
     The data management system  10  has: a communication I/F  120  which is connected to the on-site system  40 , the data lake system  50 , the service system  20 , and the like and enables exchange of communications and control of data; a catalog I/F unit  101  connected to the various catalog management units  102 ,  104 , and  106  and the client terminal  30 ; a control unit made by the various catalog management units which are the asset catalog management unit  102 , the application catalog management unit  104 , and the data catalog management unit  106  and the KPI management unit  110 ; and storage units  103 ,  105 , and  107  storing various catalogs. 
     The storage units include the asset catalog storage unit  103  in which information of a manufacture line and devices constructing a manufacture line is written, the application catalog storage unit  105  storing an application catalog in which calculation information of a KPI as a requirement specification of the service system is written, and the data catalog storage unit  107  in which a storage location as information necessary for the data management system to access IoT data is written. 
     The control unit of the data management system  10  has: the catalog management units made by the asset catalog management unit  102  performing registration, deletion, and retrieval of an asset catalog for the asset catalog storage unit  103 , the application catalog management unit  104  performing registration, deletion, and retrieval of an application catalog for the application catalog storage unit  105 , and the data catalog management unit  106  performing registration, deletion, and retrieval of a data catalog for the data catalog storage unit  107 ; and the KPI management unit  110  executing a recursive process for obtaining a KPI requested by the analysis application of the service system  20  by making the information of the catalogs of the various catalog management units associated. 
     To explain the functions of the data management system  10  in  FIG. 1  so as to be easily understood, the catalog management units  102 ,  104 , and  106 , the KPI management unit  110 , the asset catalog storage unit  103 , the application catalog storage unit  105 , and the data catalog storage unit  107  are illustrated in different function blocks. However, it is not required that those units are different as hardware. The operations of the management units may be performed as a single control unit, and the storage units may be realized by a single storage device such as a hard disk drive. 
       FIG. 2  is a diagram illustrating an example of a hardware configuration diagram of the system of the embodiment.  FIG. 2  illustrates the hardware configuration of the on-site system  40 , the data lake system  50 , the data management system  10 , and the service system  20 . 
     The service system  20 , the data management system  10 , and the data lake system  50  are constructed by, like the configuration of a common PC or server, NICs  21 ,  11 ,  51  as communication I/Fs (interfaces), CPUs  22 ,  12 ,  52  constructing a control unit, storage devices  24 ,  14 , and  54 , and buses connecting those elements, respectively. The on-site system  40  has an NIC  41  as a communication I/F (interface), a storage device  44 , various sensors  48 , and a controller  47 . 
     The NIC is hardware performing protocol control at the time of communication with another system. For example, in the case of transmitting/receiving data to/from another system via wireless communication, the NIC is constructed by a transmission unit mutually converting a digital signal and a wireless signal, converting generated digital data to a wireless signal, and transmitting the wireless signal, and a reception unit extracting the digital data from the received wireless signal. The NIC is not limited to the wireless communication but may be wired communication. 
     The service system  20 , the data management system  10 , the data lake system  50 , and the on-site system  40  are connected to one another via a network so as to be able to mutually exchange information. When a part or all of the systems and the terminal are provided for a single computer, they do not have to be connected via a network. 
     In the data management system  10 , the storage device  14  corresponds to the asset catalog storage unit  103 , the application catalog storage unit  105 , and the data catalog storage unit  107  illustrated in  FIG. 1 , and is constructed by various drives such as an NVMe drive  119   a,  an SAS drive  119   b,  an SATA drive  119   c,  and the like storing various catalog data, and storing a computer program realizing various processes, obtained on-site IoT data, and the like. 
     The memory  13  is constructed by a volatile memory such as an SRAM and a DRAM. When the CPU  12  executes a program stored in the memory  13 , various functions are realized as the control unit. The memory  13  has a cache region as a cache memory temporarily storing data. The operation unit is constructed by, for example, a keyboard  15 , a mouse  17 , and the like and used by the user to input various operations and instructions. The display unit  16  is constructed by, for example, a liquid crystal display monitor or the like and displays a necessary screen and process results of various processes. 
     The sensors  48  in the on-site system  40  are various according to kinds of on-site IoT data to be obtained and are a temperature sensor, an acoustic sensor, and the like. The controller  47  measures a timestamp indicating time information of the on-site system, a counter value indicating the number of processes, and the like. The on-site system  40  provides the information of the sensor  48  and the controller  47  as on-site IoT data to the data management system  10 . 
     Various Catalogs 
       FIG. 3  is a diagram illustrating an example of an asset catalog of the embodiment and illustrates an asset catalog of a manufacture line A to be analyzed. In the asset catalog, a line asset  301  is information related to a manufacture line. In the case of setting devices constructing the manufacture line in the asset catalog as assets, as assets of the devices, the names of the devices and information of the parts constructing the devices, and information indicating the storage locations of operation data of the devices and the like are included. As the information indicating the storage location, the ID (pointer) to a data catalog is written in the asset catalog. The data catalog includes the IP address as information necessary for the data management system to access IoT data, a database name, a table of the database, and the like. 
     In the line asset  301 , “asset010” as the ID for identifying an asset, “Line A” as “name” indicating the name of the asset, “Line” as “type” indicating the type of the asset and, in addition, information of the devices “asset011”, “asset012”, and “asset013” and the like constructing the manufacture line A as subAssets are stored. 
     A PLC asset  302  is an asset catalog related to a PLC registered as the sub asset of the line asset  301 . The PLC asset  302  is information of each of PLCs constructing the line.  FIG. 3  illustrates that three PLCs exist in the line asset  301 . A PLC asset  302   a  illustrates information of asset id “asset011” specified by the sub-asset in the line asset  301 , and “PLC1” as “name” of the asset name, “PLC” as the type, and “throughput” and “counter” as KPIs are stored. The KPIs of the PLC asset  302  are sub KPIs of the line asset  301 . It is illustrated that in the information of “throughput”, pointer data to a data catalog “data001” is stored in “dataCatalog” as data indicating the storage location of the throughput information of the PLC. Time of last updating is written as “lastUpdate”. 
     Further, “counter” indicating the counter value is similar. In the embodiment, the throughput is an amount of process which can be performed per unit time. For example, it expresses the number of processes which can be performed by an on-site device (industrial robot) per unit time, and the counter value indicates, for example, the number of processes performed by the on-site device. The PLC measures the throughput of the on-site device and transmits it to the data management system  10 . 
     PLC assets  302   b  and  302   c  are PLC assets corresponding to the sub assets “asset012” and “asset013” in the line asset  301 . 
     In the case where a line asset and a PLC asset as objects to be analyzed do not exist in an asset catalog, they can be generated by the asset catalog management unit  102 . A line asset, a PLC asset, and the like which become unnecessary can be deleted by the asset catalog management unit  102 . 
       FIG. 4  is a diagram illustrating an example of a data catalog of the embodiment. The data catalog is information indicating the storage location of IoT data. For example, as storage locations, an IP address, a database name, a table of a database, and the like are included. On precondition that IoT data has a timestamp, the IoT data itself is stored in the storage device  54  of the data lake system  50  and the storage device  44  of the on-site system  40 , and the information indicating the storage location is managed as a data catalog. 
     In the example illustrated in  FIG. 4 , in a data catalog  401 , “data001” as the identifier “id” specifying the data catalog, the data catalog name “PLC 1 Data” as “name”, “Data” as “type”, the ip address “192.168.1.1” as the storage location of data, port “5823”, and the like are stored. The id “data001” of the data catalog is the id stored as information indicating the throughput of the KPI of the PLC asset  302   a  illustrated in  FIG. 3 . 
     In the case where a data catalog as an object to be analyzed does not exist, it can be generated by the data catalog management unit  106 . A data catalog which becomes unnecessary can be deleted by the data catalog management unit  106 . 
       FIG. 5  is a diagram illustrating an example of an application catalog of the embodiment. The application catalog is data in which calculation information of a KPI as a requirement specification of the service system  20  is written. For example, as a KPI, when it is desired to obtain the throughput of a manufacture line, the application catalog is data describing that it is sufficient to calculate a device as a component of the line and the throughput of the device as a sub KPI. 
     In the application catalog, for example, a throughput and a counter value as KPIs the user desires to obtain as an analysis result are stored as an application  501 , and a line and a PLC are stored as objects to be analyzed as a target type  502 . In the case where there is another KPI (sub KPI) necessary to obtain the application  501  (the KPI the user desires to obtain as an analysis result) as a required KPI  503 , the another KPI is stored. For example, in the case where the throughput of the PLC is the KPI the user desires to obtain as an analysis result, the counter value “counter” of the PLC or the like is stored. 
     Like the required KPI  503 , a required sub-assets type  504  is also stored when there is a sub-asset type necessary to obtain the application  501 . For example, when the throughput of the line is a KPI, a PLC as a component of the line or the like is stored. In the case where there is information such as a required sub KPI  505 , execution frequency  506 , and the like, the information is stored. For example, when the throughput of the line is set as the KPI, in the case where a PLC as a component of the line is registered as a required sub-assets type  504 , the required sub KPI  505  and the execution frequency  506  related to the PLC are stored as “throughput” and “1 day”. 
     In the service system  20 , in the case where the user wants to know the throughput of the line, “Line” of the target type  502  and “throughput” of the application  501  are specified. When the target type  502  and the application  501  are specified, the required sub-assets type  504 , the required sub KPI  505 , and the execution frequency  506  are grasped as “PLC”, “throughput”, and “1 day”, respectively. That is, as data (calculation information) necessary for calculating a KPI as a requirement specification of the service system, the required KPI  503 , the required sub-assets type  504 , the required sub KPI  505 , the execution frequency  506 , and the like are grasped. 
     When the application  501 , the target type  502 , the required KPI  503 , the required sub-assets type  504 , the required sub KPI  505 , the execution frequency  506 , and the like do not exit in the application catalog, they can be generated by the application catalog management unit  104 . The application catalog which becomes unnecessary can be deleted by the application catalog management unit  104 . 
     An example of operation that the data management system  10  provides a desired KPI to the service system  20  will be described. In the operation of providing a desired KPI, different processes are executed in rows (for example, a combination of throughput and line) described in  FIG. 5 . In the embodiment, a case that the user desires to know the throughput of line A constructed by a plurality of devices as a KPI will be described as an example.
     (1) The service system, the user, or the KPI management unit  110  (in the case of recursion execution) in the data management system inquires the data management system  10  for the throughput of the line A (id: asset010).   (2) The KPI management unit  110  determines whether the throughput exists as a KPI or not with reference to the asset catalog of asset010. Since it does not exist in the example illustrated in  FIG. 3 , an application catalog is retrieved and the calculation information of the throughput of the line is specified. At this time point, it is understood that the throughput of the PLC as a component of the line asset is necessary for calculation of the throughput of the line asset.   (3) The KPI management unit  110  obtains a PLC list included in Line A with reference to the asset catalog of the line asset.   (4) The KPI management unit  110  determines whether throughput is calculated or not with reference to the asset catalog of the PLC asset.   (5) The KPI management unit  110  determines that the required sub KPI is the throughput value of the PLC as a component of Line A, and reads the throughput value of the PLC as a component of the line from the data lake.   (6) The throughput of the line is obtained from the throughput of the PLC as a component of the line. An example of this process will be described with reference to  FIG. 13 .   

     Various Input Screens 
       FIG. 6  is a diagram illustrating an example of a display screen of the data management system of the embodiment. The screen is used for editing an application catalog by the control of the KPI management unit  110 . 
     In a display screen  600  of the data management system, display regions of a service system requirement specification region  610 , an asset catalog region  620 , an application catalog region  630 , and an application catalog edit region  640  and, in addition, an application upload button  650 , a registration button  660 , and a deletion button  670  are displayed. 
     The service system requirement specification region  610  is a region of displaying a specification of a service required by the user using the service system  20  by the KPI management unit  110 . In this case, it illustrates that an object to be analyzed is “Line A”, and the KPI desired to be obtained is “throughput”. 
     The asset catalog region  620  displays, for example, an asset id or the like as an object to be analyzed as the target of a service. In this case, asset id “Asset001”, asset name “Line A”, asset type “Line” and the like are displayed. The KPI management unit  110  in the above-described (2) refers to the asset catalog of the asset010, determines whether throughput exists as a KPI or not and, when the application catalog is searched and no application can be found, performs display of  FIG. 6  to urge the user to register an application. 
     In the application catalog region  630 , an application catalog is displayed by the KPI management unit  110 , and the application catalog is edited by using the application catalog edit region  640 . The usage of  FIG. 6  will be described also with reference to  FIG. 10 . 
       FIG. 7  is a diagram illustrating an example of the display screen of the data management system of the embodiment and corresponds to service system requirement specifications (specification of an object to be analyzed and KPI desired to be obtained). It is a screen for performing asset catalog retrieval and asset catalog edit by the control of the KPI management unit  110 . 
     Like  FIG. 6 , in a service system requirement specification display region  710 , specifications of service required by the user using the service system  20  are displayed by the KPI management unit  110 . 
     In an asset catalog search  720 , name, type, and the like of an asset as an object to be retrieved are designated, and an asset stored in the asset catalog storage unit  103  is retrieved.  FIG. 7  illustrates a state that “PLC” is designated as type, and an asset of asset id “asset011”, name “PLC 1”, and type “PLC” is retrieved. 
     In an asset catalog edit  730 , the content of the asset catalog is edited, and an asset as an object to be edited is registered by a registration button  740  and deleted by a deletion button  750 . 
       FIG. 8  is a diagram illustrating an example of the display screen of the data management system of the embodiment. It is a screen for performing data catalog retrieval and data catalog edit for service system requirement specification (specification of an object to be analyzed and a KPI desired to be obtained) by the control of the KPI management unit  110 . 
     Like  FIGS. 6 and 7 , in a service system requirement specification display region  810 , the specification of a service required by the user using the service system  20  is displayed by the KPI management unit  110 . 
     In a data catalog search  820 , “id” as identifier, “name”, “type”, and the like of data as an object to be retrieved are designated, and an asset stored in the data catalog storage unit  107  is retrieved.  FIG. 8  illustrates a state where an asset of id “data001”, name “PLC 1 Data”, and type “Data” is retrieved. 
     In data catalog edit  830 , the content of a data catalog is edited, and an asset as an object to be edited is registered by a registration button  840  and deleted by a deletion button  850 . 
     Processing Operation of Data Management System 
       FIG. 9  is a diagram illustrating an example of a process flow of the data management system of the embodiment. 
     The process operation of the data management system  10  in the case where the user desires to obtain a KPI with respect to a predetermined asset by the service system  20  will be described. To make the content of the invention easily understood, the process operation of the data management system  10  in the case where the user sets the throughput of Line A which is an object to be analyzed, as a KPI desired to be obtained by the service system  20  will be described. Obviously, an object to be analyzed and a KPI are not limited to Line A and throughput. Various combinations are included and, particularly, the combinations in the rows in  FIG. 5  can be considered. 
     In step S 101 , Line A as an asset and throughput as a KPI are input by the user from the operation unit of the data management system  10  to the control unit (concretely, the asset catalog management unit  102 ). 
     In step S 102 , the asset catalog management unit  102  retrieves an asset catalog corresponding to the asset. That is, the asset catalog of Line A is retrieved. 
     In step S 103 , the asset catalog management unit  102  determines whether the asset catalog of Line A could be found or not, when it could be found, advances to step S 106  and, when it could not be found, advances to step S 104 . 
     In step S 104 , the asset catalog management unit  102  displays the input screen ( FIG. 7 ) of the asset catalog of Line A on the display unit  16  to the user. The asset catalog of the asset which is input in step S 101  is generated. 
     Subsequently, in step S 105 , the asset catalog management unit  102  registers an asset catalog corresponding to the asset by the user from the asset catalog edit screen illustrated in  FIG. 7 . That is, the asset catalog  301  of Line A illustrated in  FIG. 3  is registered. 
     In step S 106 , the asset catalog management unit  102  obtains a KPI list from the asset catalog. That is, a KPI included in the asset catalog of Line A is obtained. When the asset catalog of Line A could be found in step S 103 , the KPI list included in the asset catalog is obtained. In step S 105 , when the user inputs the KPI of the line asset, the information is obtained. 
     In step S 107 , the control unit (concretely, the KPI management unit  110 ) of the data management system  10  determines whether a desired KPI exists in the obtained KPI list or not. That is, the KPI management unit  110  determines whether or not the throughput as the desired KPI as the requirement specification of the service system exists in the obtained KPI list. In the case where it exists, the unit advances to step S 109 . In the case where it does not exist, the unit advances to step S 108 . The KPI calculating process of step S 108  will be described later with reference to  FIG. 10 . 
     In step S 109 , the asset catalog management unit  102  retrieves a data catalog associated with the KPI. That is, when a data catalog expressing the throughput exists in the asset catalog of Line A, the data catalog is retrieved.  FIG. 3  expresses an example that a data catalog associated with the throughput does not exist in the asset catalog  301  of Line A and a data catalog is associated with a KPI (throughput) in an asset catalog (PLC asset  302 ) of the PLC as the component of Line A. In the case where a data catalog is associated with the KPI of the line asset  301  like the KPI of the PLC asset of  FIG. 3 , the data catalog is retrieved. 
     In step S 110 , the asset catalog management unit  102  reads IoT data from the storage location in the data lake system  50  or the on-site system  40  indicated in the data catalog, and presents it as a desired KPI to the user/service system. 
       FIG. 10  is a diagram illustrating an example of the process flow of the data management system of the embodiment, and illustrates the details of the process content of step S 108  in  FIG. 9 . 
     In step S 108  in  FIG. 9 , in the case where a desired KPI does not exist in the obtained KPI list, that is, in the case where a throughput as a desired KPI does not exist in the asset catalog of Line A, the control unit (concretely, the KPI management unit  110 ) of the data management system  10  starts a process (step S 111 ). 
     In step S 112 , the KPI management unit  110  retrieves KPI calculation information corresponding to a desired KPI of the asset from the application catalog. Concretely, since the user sets a throughput as the desired KPI with respect to Line A, referring to the application catalog illustrated in  FIG. 5 , the required KPI  503 , the required sub-assets type  504 , the required sub KPI  505 , and the like are retrieved. As a result, the required sub-assets type  504  “PLC”, the required sub KPI  505  “throughput”, and the execution frequency  506  “1 day” are found as KPI calculation information. 
     In step S 113 , the KPI management unit  110  determines whether KPI calculation information could be found or not. In the case where KPI calculation information could be found, the unit advances to step S 116 . In the case where KPI calculation information could not be found, the unit advances to step S 114 . 
     In step S 114 , the KPI management unit  110  displays an input screen of the application catalog as illustrated in  FIG. 6  on the display unit  16  to the user. Concretely, the user checks the service system requirement specification  610  and specifies an application to be registered in the application catalog. In the embodiment, throughput calculation for a line asset is specified. The user refers to the asset catalog  620 , refers to an asset (line asset) corresponding to an asset to be analyzed and an asset (PLC or the like) related to the asset, and checks whether a KPI necessary to calculate the throughput is calculated or not. While referring to the application catalog region  630 , the user enters an application and a target type corresponding to the service system requirement specification by operating the keyboard or mouse in the application catalog edit region  640 . That is, catalog information of an application defined by “throughput” as application and “Line” as target type is entered. By clicking an application upload button, KPI calculation information corresponding to the catalog information is registered in the application catalog. An unnecessary application may be deleted by clicking the deletion button. 
     In step S 115 , the KPI management unit  110  registers the KPI calculation information of the application catalog corresponding to desired KPI calculation information of the asset by the user. In the embodiment, “PLC” as a component of Line A is registered in the required sub-assets type  504 , and the throughput of the PLC or the like is registered in the required sub KPI  505 . 
     In step S 116 , the KPI management unit  110  determines whether calculation of the KPI of another asset is necessary for calculation of a desired KPI of the asset or not. Specifically, it determines whether or not the KPI (sub KPI) of the asset such as the PLC or the like as a component of Line A is necessary to calculate the throughput of Line A as a desired KPI. When it is determined in step S 116  that calculation of the KPI of another asset is necessary, the unit advances to step S 117 . When it is determined that the calculation is unnecessary, the unit advances to step S 118 . The process in step S 117  will be described with reference to  FIG. 11 . 
     In step S 118 , the KPI management unit  110  calculates a desired KPI by using the obtained KPI calculation information. Specifically, the KPI management unit  110  calculates the throughput of Line A as a desired KPI by the required sub-assets type  504  “PLC”, the required sub KPI  505  “throughput”, and the execution frequency  506  “1 day” registered in the application catalog. 
     In step S 119 , the KPI management unit  110  generates a catalog related to the generated KPI and registers it as an asset catalog and a data catalog. Specifically, the throughput of Line A is registered in the asset catalog of Line A, and the value of the throughput generated together with the storage destination of data is registered in the data catalog. Referring to the asset catalog of  FIG. 3 , “throughput” and information of the data catalog are registered in the KPI of the line asset  301 , and a state like the PLC asset in which those information is registered is obtained. 
       FIG. 11  is a diagram illustrating an example of the process flow of the data management system of the embodiment, and illustrates the details of the process of step S 117  in  FIG. 10 . When it is determined in step S 116  in  FIG. 10  that calculation of the KPI of another asset is necessary for calculation of a desired KPI of the asset, the process of  FIG. 11  is started (S 121 ). 
     In step S 122 , the KPI management unit  110  extracts an asset list necessary to calculate a desired KPI from the asset catalog of the asset. In the case of the asset catalog illustrated in  FIG. 3 , as the asset list necessary to calculate the throughput from the asset catalog of Line A, three sub assets “asset011”, “asset012”, and “asset013” corresponding to PLCs constructing Line A are extracted. 
     In step S 123 , each of the assets in the obtained asset list is inquired for a sub KPI necessary to calculate a desired KPI. Specifically, each of the obtained three sub assets is inquired for a sub KPI necessary to calculate the throughput of Line A. For the PLCs constructing Line A, the throughput of each of the PLCs is inquired. The throughput of each of the PLCs inquired in this step is the KPI calculation information obtained in step S 118  in  FIG. 10 . 
     KPI Calculation Process 
       FIG. 12  is a diagram explaining a method of calculating the throughput of a PLC which is necessary to calculate a desired KPI (throughput of Line A) from a data catalog associated with the KPI of the PLC asset. 
     In the example of  FIG. 12 , in the case where only a timestamp and a counter value exist as a KPI and a throughput does not exist in a PLC asset, (1) first, a table for registering a throughput is generated in the PLC asset. (2) Next, the KPI management unit  110  calculates the throughput at the time of registration of each timestamp from the timestamp and the counter value and registers it in a corresponding throughput column. 
     Since the counter value at the time of the timestamp “2018-12-20 00:00:00” is “0” and the counter value at the time of the timestamp “2018-12-20 01:00:00” is “15”, throughput “15” at the time of the timestamp “2018-12-20 01:00:00” is registered. Since the counter value at the time of the timestamp “2018-12-20 02:00:00” is “24” and the counter value at the time of the timestamp “2018-12-20 01:00:00” is “15”, “9” as the difference between the throughputs “24” and “15” is registered at the time of the timestamp “2018-12-20 02:00:00”. 
       FIG. 13  is a diagram explaining a method of calculating a KPI of a line from KPIs of devices constructing the line. In the embodiment, in the case where Line A is constructed by two PLCs, a method of calculating the throughput of Line A from the throughputs of the PLCs will be described. 
     In the case where throughputs are registered as KPIs of PLCs or in the case of calculating a throughput, a method of calculating the throughput of Line A by using the throughputs of the PLCs will be described.
     (1) First, a column for registering a desired KPI in a line asset is generated.   (2) Next, a PLC1 table  1501  and a PLC2 table  1502  storing throughputs at the time of timestamps of PLC1 and PLC2 from the data catalog associated with the PLC asset are read from the data lake.   (3) Subsequently, the throughputs of PLC1 and PLC2 are compared and the value of the smaller one of the throughputs is set as the throughput of Line A. PLC1 and PLC2 have the information of the same timestamp. For example, since the throughput of PLC1 is “15” and the throughput of PLC2 is “11” at the time of the timestamp “2018-12-20 01:00:00”, the throughput of Line A is calculated as “11”. Similarly, since the throughput of PLC1 is “9” and the throughput of PLC2 is “6” at the time of timestamp “2018-12-20 02:00:00”, the throughput of Line A is calculated as “6”. The throughput of the entire line is determined by the value of smaller one of the throughputs of the two PLCs constructing the line.   

     As described above, even in the case where the throughput of Line A is not included as a desired KPI in the line asset, by referring to or calculating the throughputs of the PLCs constructing the line, the throughput of Line A can be obtained. 
     According to the embodiment as described above, the users in the layers of a factory, manufacture lines constructing the factory, devices constructing the manufacture lines, and the like can obtain a desired KPI in each layer without having the knowledge of the other layers. 
     The manager of a factory or a manufacture line can grasp a KPI such as the throughput of the factory or the manufacture line without specialized knowledge on the storage location of IoT data of devices constructing the manufacture line and context of IoT data. 
     Without having specialized knowledge regarding an object to be analyzed (for example, a manufacture line or PLCs constructing a manufacture line), reuse of an analysis application having different contexts such as data units or data acquisition times of on-site data (for example, data of PLCs) can be realized in short manhour.