JP2019164557A - Retrieval system - Google Patents

Abstract

To provide a retrieval system which executes various retrievals which transverse data in a plurality of existing database.SOLUTION: A retrieval system includes: a mapping system configured of metadata creation means which creates metadata structured from existing database, projection creation means which creates a projection for extracting specific information from the metadata, first mapping means which maps the projection to a class of information ontology database, and second mapping means which maps a projection item of the projection to a property of the class in a state in which the class and the projection are mapped with each other; and a data lake system configured of data association means which associates data items of a data file stored in the existing database based on the mapping, and storage means which stores the information of the data item in an atypical data structure database.SELECTED DRAWING: Figure 1

Description

  The present invention constructs an information ontology, associates it with a database of an existing information system, and extracts / joins data requested by the user based on the association of data in a plurality of existing databases associated by the association The present invention relates to a search system to present.

Conventionally, a search system has an information structure and function for associating existing data with an ontology, and by mapping the ontology constructed thereby with an existing information system database, the information processing target can be expanded by the ontology. Technology has been developed.

  Specifically, information in an existing database having a different data structure, grammar, and standard is mapped to each structure of the information ontology, thereby making the data in the existing database compatible with information standardized in the information ontology. Thus, by mapping a plurality of existing databases to a single information ontology, it becomes possible to make the data of each existing database having different data structures, grammars and standards compatible with each other through the information ontology.

  Patent Document 1 discloses a technique for providing a technique for improving user convenience when searching a plurality of databases. Specifically, (A) one or more query elements included in the first search query input by the user are extracted, and (B) a plurality of databases storing different types of data for each query element. (C) Based on the degree of association, the presence / absence of association with each of the plurality of databases is determined for each query element, and (D) each of the plurality of databases is associated with the database. If there is a query element determined to be, a second search query including the query element is generated. (E) Based on the second search query, the second search query is selected from the plurality of databases. A search program, apparatus, and method including processing for searching a corresponding database are disclosed.

  Patent Document 2 discloses an invention having an information structure and function for associating existing data with an ontology, and associating an ontology constructed thereby with a database of an existing information system. Specifically, information in an existing database having a different data structure, grammar, and standard is mapped to each structure of the information ontology, thereby making the data in the existing database compatible with information standardized in the information ontology. As a result, a search system is disclosed in which multiple existing databases are mapped to a single information ontology, so that the data in each existing database with different data structures, grammar, and standards can be mutually compatible through the information ontology. Yes.

  Patent Document 3 discloses a technique for associating data item names among a plurality of data schemas. Specifically, the item name of the target database is associated with the item name of the source database, and the discriminating relationship between the concepts from the data schema definitions and instance documents of the two databases (synonymous or Data schema mapping that has the function to store in the ontology by extracting the temporal order relation) and the function to narrow down the correspondence of data item names using the ontology A program and a computer system are disclosed.

JP2012-247869A JP 2010-86437 A JP 2007-179146 A

  Here, there is a need to extract data matching the request without excess or deficiency in response to the user's search request, and to process the data in accordance with the request and present it as a search result. .

  The prior art described in each of Patent Documents 1 to 3 only discloses mapping of information in an existing database to each structure of the information ontology, and each existing information is simply based on information standardized by the information ontology. Although data can be retrieved from a database, it is not possible to search and extract data related to information standardized by an information ontology from a plurality of existing databases and to present them by joining them together. For this reason, it is impossible to extract and present data without excess or deficiency in response to a user request, which is not sufficient for the above needs.

  Therefore, in view of the above problems, the present invention has an information structure and function for associating existing data with an ontology, thereby constructing an ontology, associating it with a database of an existing information system, and associating the association Provides a search system capable of executing various searches across data in a plurality of existing databases by associating data in a plurality of existing databases with each other through data standardized by an information ontology. There is.

  The search system according to the present invention is constructed and operated for the purpose of supporting a business process based on an information ontology that has a class that is made into a knowledge based on the concept of an object and that is associated with one or more properties that specify the class. In a search system that searches from an existing database used by an existing information system, metadata creation means for creating structured metadata from the existing database and structured by the metadata creation means Projection creation means for creating a projection for extracting specific information from the metadata, first mapping means for mapping the projection created by the projection creation means to a class of the information ontology database, and the first mapping Projection with class and projection mapped by means Based on mapping by the second mapping means for mapping the projection item to the property of the class, and mapping by the first or second mapping means, the data items of the data file stored in the existing database are A data lake system comprising an associating means for associating and an accumulating means for accumulating data item information in an atypical data structure database is provided.

  The metadata includes physical database information, information on data files stored in the database, information on connection between data files, information on data items in the data file, and information on valid data values of the data items. It is desirable.

  The projection creating means further comprises a unit database, and when the projection structure definition defines that the units are different with respect to the projection item of the data having the unit concept, the unit database has a compatibility method between the units. It is desirable to convert the unit by searching from.

  It is desirable to obtain information from an existing database via at least one projection mapped to the desired class by the mapping system by selecting a desired class from the information ontology.

  Therefore, according to the present invention, it is possible to execute various searches across data in a plurality of existing databases in order to associate data in a plurality of existing databases with each other through data standardized by an information ontology. Become.

It is the flowchart figure which showed the structure of the search system which comprises the mapping system which concerns on this invention. It is the flowchart figure which showed creation of the projection of the mapping system which concerns on this invention. It is the flowchart figure which showed the definition of the projection item of the mapping system which concerns on this invention. It is the flowchart figure which showed the search process of the search system which concerns on this invention. 1 is a structural block diagram of a mapping system according to the present invention. It is explanatory drawing which showed an example of the mapping system which concerns on this invention. (a), (b) is explanatory drawing which showed an example of the metadata of the mapping system based on the Example of this invention. It is explanatory drawing which showed an example of the mapping of the projection item and class which concern on the Example of this invention. It is explanatory drawing which showed an example of the mapping of the effective value list which concerns on the Example of this invention. It is the flowchart figure which showed the search and joining process of the search system of this invention. (a), (b) It is explanatory drawing which showed an example of the correlation of the data lake system based on the Example of this invention. (a), (b) It is explanatory drawing which showed an example of the correlation of the data lake system based on the Example of this invention. It is explanatory drawing which showed an example of the attribute information incidental to the data item accumulate | stored in the atypical data structure database which concerns on the Example of this invention.

  Hereinafter, an embodiment of the present invention will be specifically described with reference to the accompanying drawings.

  As shown in FIG. 1, the search system according to the present invention includes a mapping system 1 composed of steps 100 to 500, a data lake system 2 composed of steps 510 to 520 and search / join processing means 700, and a search. And processing means 600.

  This mapping system 1 has a class that becomes knowledge based on the concept of an object, and is constructed and operated for the purpose of supporting a business process based on an information ontology in which one or more properties specifying the class are linked. In a search system for performing a search from an existing database used by an existing information system, metadata creating means 100 for creating metadata of the existing database, and metadata created by the metadata creating means 100 Projection creation means 200 for creating a projection for extracting specific information, first mapping means 300 for mapping the projection created by the projection creation means 200 to a class of the information ontology database, and the first mapping Class and projection are mapped by means 300 The second mapping means 400 for mapping the projection item of the projection to the property of the class, and the second mapping means 400 maps the property having the valid value list and the projection item having the valid value list. And a third mapping unit 500 that maps the value of the effective value list of the projection item to the value of the effective value list of the property.

  In the mapping system 1, the mapping structure between the information ontology and the existing database defines the projection of the existing database approximate to the class definition based on the metadata of the existing database, and associates each part of the projection with each part of the information ontology. Can be realized.

  This data lake system 2 is a non-schema-less database that includes a variety of data including “unstructured data” such as sensor log data, GPS (global positioning system) data, image / video data, and audio data. In this system, data is stored in a fixed data structure database, and in accordance with a search request from the user, data matching the request is searched for, extracted, and joined from the stored data and presented to the user. Specifically, the data lake system 2 includes an association unit 510 that associates data items of data files stored in an existing database, based on the mapping by the first to third mapping units by the mapping system 1, and the data items The information is stored in the atypical data structure database, and based on the user's request, the data item information stored in the atypical data structure database is searched according to the association between the data items. And a search / joining means 700 that extracts information items that match the above and joins the information of the extracted data items to present information.

  In the metadata creating means 100, the metadata is data related to data, and the metadata of the existing database is data related to data stored in the existing database. The metadata of an existing database includes physical database information, information on data files stored in the database, information on connection between data files, data file data item information, and data item valid data value information. is there. The metadata of these existing databases can be automatically generated from the catalog information held by the management system of the existing database. In addition, it is possible to supplement the missing information manually.

  The search system according to the present invention is a mechanism for combining an information ontology class that has been made into a knowledge as a specific concept and an existing database that has the same or equivalent information as the concept that has been made into knowledge in that class. Including existing database information with different data structure, grammar, and standards, mapping information on each structure of information ontology to make data of existing database compatible with data standardized by information ontology Good.

  Further, by mapping a plurality of existing databases to a single information ontology, the data of each existing database having different data structures, grammars, and standards can be interchanged through the information ontology.

  According to the present invention, the information ontology database does not have the instance data of the class, and the data in the database processed by the existing information system is handled as the instance data. Therefore, a plurality of existing databases can be used as they are. There is an effect that can be done.

  Projection creation in the projection creation means 200 is shown in the flowchart of FIG. 2, for example. In creating a projection starting from step 200, one data file in an existing database is selected in step 201. In step 202, it is determined whether or not to further select a data file. When selecting (Y), the process returns to step 201 to select another data file, and it is determined not to select (N) in the selection in step 202. Until the data file is selected. As a result, one or more data files in the existing database are selected.

If it is determined in step 203 that the number of selected data files is 2 or more (Y), the process proceeds to step 204, where the combination conditions for the selected data files are set, and the projection items in step 205 are defined. If the number of selected data files is 1 (N), the process skips step 204 and proceeds to step 205 to define a projection item. This definition is
1. Define a projection item that directly references a single data item.
2. Define a projection item that computes and derives a single data item.
3. Define a projection item that calculates and derives multiple data items.
4). Defines a constant that does not refer to a data item, or a projection item that is dynamically derived from the environment.
That is.

  Specifically, as shown in FIG. 3, it is determined in step 206 whether or not the projection item is a simple reference to a data item. If it is a simple reference (Y), the data item is selected in step 207. The If it is not a simple reference (N), the process proceeds to step 208. If the projection item refers to a data item (Y), the process proceeds to step 209 to select the data item, and the selection is completed in step 210. Until then, the selection of the data item in step 209 is repeated, and then the process proceeds to step 211 to define an expression for deriving the projection item. Further, even when the projection item does not refer to the data item in the determination in step 208, the process proceeds to step 211 to define an expression for deriving the projection item. In step 207 and steps 211 to 212, the names of the projection items are defined.

Thereafter, in step 213, a semantic data type is set. There is a semantic data type applied to the projection item (the indented data side is treated as a subtype of the data type of the previous line).
・ Logical type ・ String type ・ Variable length type ・ Fixed length type ・ Non-quantity code type ・ Numeric type ・ Integer type ・ Quantity integer type ・ Quantity level integer type ・ Non-quantity integer type ・ Passing integer type ・ Real number type ・Quantity real type ・ Quantity level real type ・ Passing real number type ・ Date time type

In step 214, the unit is set. As this unit,
-Units of measure: meters, grams, liters, degrees Celsius. . .・ Currency units: Japanese yen, US dollar, Euro, Hong Kong dollar. . . Etc. ・ Year-of-year: Western calendar, Japanese calendar. . .・ Time zone: Japan Standard Time, US West Coast Time (Daylight Saving Time). . . Etc. Thereby, it is possible to detect that the unit is different between the property mapped in the future and the projection item. When the user or the computer system detects that the units are different, the user or the computer system can obtain a knowledge for performing unit conversion by searching the unit database for a compatibility method between the units.

  Further, in step 216, it is determined whether or not there is a valid value list for the projection item. If not (N), the process returns to step 220 from the control routine. If there is (Y), the process proceeds to step 217 to create an effective value list, an effective value is added to the effective value list in step 218, and step 218 continues until it is determined in step 219 that there is no effective value. If no more (N), return to the base routine in step 220.

  In the project item definition work from step 205, an effective value is added to the list defined in the determination of step 230, and step 218 is continued until it is determined that there is no effective value in the determination of step 219. N) Return to the base routine at step 220.

Projection item definition work from step 205 is executed until there is no projection item defined in the determination in step 230, and if it is determined that all projection items have been defined (N), the process proceeds to step 231 in FIG. The search condition for the record that will be the projection range is defined (extraction condition setting). The search condition for the record that is the projection range is defined so as to provide exclusive information to other projections defined in the same existing database. If this exclusive projection definition is not guaranteed, certain data in the existing database is mapped to a plurality of information ontology classes, so that the concept represented by the information ontology becomes ambiguous. The projection creating means 200 ends in step 232 and returns to the main routine.

The first mapping unit 300 maps projections to information ontology database classes. However, projection and class mapping have the following restrictions.
• Projections cannot be mapped to multiple classes.
A class can be mapped to multiple projections.
A class cannot map multiple projections defined for the same existing database.
The mapping between information ontology classes and projections defined for any existing database is 1: 1.

  The second mapping unit 400 maps the projection item of the projection to the property of the class in a state where the class and the projection are mapped. Only those whose property data type and the semantic data type of the projection item match can be mapped. Only a project item having a valid value list can be mapped to a property having a valid value list.

  The third mapping unit 500 maps the value of the effective value list of the projection item to the value of the effective value list of the property in a state where the property having the effective value list and the projection item having the effective value list are mapped. It is something to be made.

  Information written in the language in the definition of the information ontology class, property, property valid value, etc., can be registered in any number of languages in the same language, and the same meaning for each language Is stored in a structure that can register an arbitrary number of different notations. This makes it possible to find the same information from "TV", "TV", "TV", "TV" in Japanese, "television" in English, "TV" in Chinese, etc. It is.

  The associating unit 510 associates data items of data files stored in the existing database based on the mapping by the first to third mapping units. The association may be associated in any manner, (1) may be associated by tagging the data item, or (2) associated by pointing to each other with pointer-type data. Alternatively, (3) the association may be performed by separately registering the association using a dictionary function or the like.

  The storage means 520 stores the information on the data items in an atypical data structure database. The storage may be configured, for example, by storing the information of each data item as a data value in an atypical form from a data file of an existing database, using the key information (PK) as a key value.

  According to the above configuration, when there is a user data search request, it is possible to target all kinds of data by using the data stored in the database of the atypical data structure, and Since the data can be managed in the associated state through the standardization of the information ontology, the search process can be performed using the association between the data when the request is made.

  The search processing means 600 is, for example, as shown in FIG. In the search process 600, first, in step 601, an information ontology is selected, and a predetermined class in the information ontology is selected. In step 603, the projection mapped to the selected class is acquired. In step 604, the structure definition of the projection is acquired. In step 605, the property / projection item of the class to be extracted is selected. In step 606, an extraction condition (search condition) is specified. In step 607, a search request for the existing database is generated. In step 608, the existing database is searched. In step 609, the search result data is acquired. In step 610, the units are changed and matched. In step 611, the search result data is returned. In step 612, the search processing operation is completed.

  Based on the user's request, the search / joining means 700 searches the data item information stored in the atypical data structure database along the association between the data items and extracts the data item that matches the request. The information of the extracted data items may be joined to obtain the information. In the search along the association, for example, when one data is selected from the data having the synonymous meaning, the other data may be selected at the same time. If the data has a meaningful association, if the previous data is selected, the subsequent data may be selected next. Further, in the joining, for example, the information of the extracted data items may be simply connected, or the extracted data items may be processed and connected, or the extracted data may be connected to each other. Addition / subtraction / division / division calculation processing may be performed.

  According to the above configuration, the data stored in the atypical data structure database is not simply extracted from the database according to the request, but is also associated with the standardization based on the information ontology. Since the data can be searched, extracted, and further joined, it is possible to provide a search system that can inquire data more in line with the user's request (in line with the user's intention).

  In the search / joining means 700, the data items stored in the atypical data structure database are accompanied by attribute information related to the constituent elements of the sentence, and are stored in the atypical data structure database along with the association of the data. When searching for the information of the data item, the search order may be determined based on the attribute information.

  According to the above configuration, the search according to the sentence configuration can be realized by determining the search order based on the attribute information that is the background of the data, and a more formal data inquiry can be performed.

  Specifically, the search / joining means 700 is, for example, as shown in FIG. In this search / joining process 700, first, in step 701, a user data search request is accepted. In accepting the request, specifically, it may be accepted by directly specifying a key value or the like using a function matched to an atypical data structure database (query by query), or GUI (Graphical Request operation means (for example, a text box for inputting a keyword of a data item to be requested) may be provided by the user interface and accepted by the means.

  In step 702, it is determined whether or not the attribute information related to the sentence component attached to the data item is to be used. Whether to use the attribute information may be determined according to a preset condition, or may be determined according to the content of a user request or a function to be used. When using (Y), the process proceeds to step 703.

  In step 703, the search order based on the attribute information is determined. In the determination of the search order, for example, the priority order of the attribute information may be determined, and the search order may be determined so that the search is performed by sorting according to the order.

  In step 704, a search request to the atypical data structure database is generated, and in step 705, a search process is performed to search for information on the data items stored in the atypical data structure database along the association between the data. In this case, if the user's request is a query that directly inquires, the query may be used as it is as a search request, or if it is based on GUI operation means, a new query with the specified parameter embedded may be issued. It may be generated. At this time, if there is a search order determined in step 703, it is followed. In step 706, the data item of the search result is extracted, and in step 707, the information of the extracted data item is joined. The information joined at step 708 is returned, and the search / join processing work is completed.

  From the above, when the mapping system according to the present invention is schematically described, a block configuration as shown in FIG. 5 is obtained. In this block configuration, the metadata 20 of the existing database extracted from the existing database includes at least database information, data file information, data file item information, and a data file item value list.

  A projective structure definition 30 exists at the conceptual upper part of the metadata 20 of the existing database. Projections are generated by this projection structure definition, specifically, data file selection, data file connection definition, data file item selection, data extraction definition, projection item expression definition, and projection item value list.

  This projection is mapped to a class included in the information ontology database 50 via a projection-information ontology mapping 40, the projection item is mapped to a class property, and the value of the projection item value list is the property value of the class. Mapped to list value.

  In FIG. 6, this will be described in more detail. The metadata 20 extracted from the existing database 10 includes database file information Tbl1, Tbl2, Tbl3, Tbl4 and database file item information C11, C12, C13, C21, C22, C23, C31, C32, C33, C41, C42, C43, and a database file item value list Lv.

  The database file information Tbl1, Tbl2, Tbl3, and Tbl4 are selected as data files through the data extraction condition 34 and the data file combination condition 35, and are generated into projections Prj1, Prj2, Prj3, and the database file item information C11 to C43 are Data file items are selected and projection items Pjc1-1 to Pjc3-3 are generated. Further, the database file item value list Lv is generated as a projection item value list Pjv. These constitute the projective structure definition 30.

  The projections Prj1, Prj2, and Prj3 are mapped to the classes Cls1, Cls2, and Cls3 of the information ontology database 50 via the projection-information ontology mapping 40. At the same time, for example, projection items Pjc1-1 and Pjc2-1 are mapped to the class property Prp1-1 of the class Cls1, and projection items Pjc1-2 and Pjc2-2 are mapped to the class property Prp1-2. Projection items Pjc1-3 and Pjc2-3 are mapped to the block patty Prp2-1. The projection item value list Pjv is mapped to the class property value list Prpv.

  Thus, for example, when class Cls2 is selected, projections Prj1 and Prj2 are selected, Pjc1-1 to Pjc2-3 are selected as projection items, and database file information Tbl1 to Tbl4 are selected as metadata, respectively. Based on this, an item of an existing database is selected, and data is downloaded according to the extraction condition.

  An example of retrieving information in a specific existing database from the information ontology is shown below.

  As shown in FIG. 7 (a), for example, metadata db01 created based on an existing database has a product classification code and a product classification name as product classification information, and SKU, representative JAN code 8 as product information. It has 13 digits, representative JAN code, product name and classification, SKU, company code, purchase start, purchase end and purchase price as purchase information, company code and company as supplier company information Have a name. In addition, as shown in FIG. 7B, the metadata db02 has a department CD and a department name as product department information, a product name CD, a product name and department CD as product name information, and a product CD as sales product information. , Commodity CD country, commodity CD item, commodity CD check digit, commodity name, commodity receipt display name, commodity name CD and registration date, country CD and country name as EAN country CD information, business partner information It has CD and supplier name, has product CD, supplier company, start date and end date as purchase information, and has product CD, start date, end date and price as price information.

  Also, as shown in FIG. 8, a class of an information ontology database having, as properties, a product name, a product short name, a product classification, a product supplier company, a product purchase start date, a product purchase end date, and a product purchase price (: Electrical products), the product name is projected: the product name of db01 electrical appliance and the projection: the product name of db02 electrical appliance is mapped, and the product abbreviated name is projected: the product receipt display name of db02 electrical appliance is mapped For product classification, projection: db01 electrical product product classification name and projection: db02 electrical product department name is mapped, product supplier company projection: db01 electrical appliance company name and projection: db02 electrical product transactions The name is mapped and the product purchase start date is projected: db01 electrical product purchase start and projection: db02 electrical product start date is mapped, and the product purchase end date Projection: db01 appliances purchase end and projection: db02 appliances end date is mapped, about the product purchase price projection: db01 purchase price of electrical appliances is mapped.

  Further, as shown in FIG. 9, in this embodiment, the projection: projection item of db01 electrical appliance: the product category name has a product category code and product category name as a valid value list, and the projection: projection item of db02 electrical appliance. : The department name is accompanied by a department CD and a department name as a valid value list, and these are mapped to class: appliance property: valid value list product classification and formal name.

  An example of searching for product information in an existing database from the information ontology with the above configuration is shown below. When a user obtains a list of audiovisual products and their purchase price from an existing database, the user scans and selects a class: appliance from the information ontology. As described above, the class: electrical appliance has property: product name, property: product short name, property: product classification, property: product purchase end date, and property: product purchase price. Also, the class: electrical appliance is mapped to the projection: db01 electrical appliance and the projection: db02 electrical appliance. The user selects property: product name, property: product classification, property: product purchase price as items necessary for the list.

  Property: Product name, Property: Product classification, Projection: db01 electrical appliance, Projection: db02 It is mapped to the corresponding projection item of electrical appliance, but the purchase price is projected: Projection of db01 electrical appliance: Purchase Only the price is mapped. For this reason, projection: db01 electrical appliance is selected as the projection to be used. Property: product name is mapped to projection item: product name, property: product classification is mapped to projection item: product classification code, property: product purchase price is mapped to projection item: purchase price.

  Projection: db01 electrical appliance is structured from db01 metadata, Projection item: Product name is in data file item: Product name, Projection item: Product classification code is Data file: Product classification item: In the product classification code, the projection item: purchase price is mapped to the data file: purchase item: purchase price. Mapping from this two-layer mapping to information ontology (class: electrical appliance) → existing database: db01 is performed. When the existing database: db01 is an RDBMS, the following SQL is obtained as a request from the ontology to the existing database from the metadata of the existing data: db01.

select Product classification. Product classification code as product classification,
Product. Product name as product name,
Purchase. Purchase price as Product purchase price
from Product Classification
left join product on (Product classification. Product classification code = Product. Classification)
left join purchase on (product.SKU = purchase.SKU);

  Since the user needs a list of audiovisual products, the user sets property: value of effective value list of product category, product category: 2 (audio video product) as a search condition. Property: Value of product category effective value list, Product category: 2 is mapped to Projection item: Value of product category effective value list, Product category code: DD200 (see FIG. 9). Thereby, the condition is added to the SQL as follows.

select Product classification. Product classification code as product classification,
Product. Product name as product name,
Purchase. Purchase price as Product purchase price
from Product Classification
left join product on (product classification, product classification code = product. classification)
left join purchase on (product.SKU = purchase.SKU);
when Product classification. Product classification code = 'DD200';
Necessary information can be obtained by executing this request on the existing database: db01.

  An example of associating data items in an existing database based on mapping through an information ontology is shown below. This embodiment will be described with reference to the mapping example of FIG. 9 and FIGS. 11 and 12.

  FIG. 11 shows an example when the data items stored in the existing database are each stored in the atypical data structure database. The data item is composed of a key value (key) and a data value (Value), and each value is held without any limitation on data type, length, or the like. FIG. 11A shows an example of a state in which data items are not associated, and FIG. 11B shows an example of a state in which data items are associated by tag data.

  FIG. 12 shows an example when the data items stored in the existing database are accumulated in the atypical data structure database and associated with each other, as in FIG. 12A shows an example of a state in which data items are associated by pointer type data, and FIG. 12B shows an example in which the association of data items is separately registered by a dictionary function.

  In the example of mapping shown in FIG. 9, in class: appliance property: merchandise supplier company, projection: db01 appliance company name and projection: db02 appliance supplier name are mapped. Further, as another mapping example shown in FIG. 9, in the class: electrical property: product purchase price, the projection: db01 purchase price of the electrical appliance is mapped, and the property: via the product supplier company. , Projection: db01 is associated with the company name of the appliance and Projection: db02 is associated with the supplier name of the appliance. This will be described below with reference to these mapping examples in FIG.

  The search system according to the embodiment includes a company code and company name (Rec1) of a supplier company of metadata db01, a transaction CD and a supplier name (Rec2) of metadata db02 as shown in FIG. On the other hand, as shown in FIG. 11B, these data items are associated with each other based on the mapping. The association may be associated in any manner. (1) As shown in FIG. 11B, if the data items have the same meaning, the same tag data (in this example, “ Tag (product supplier company tag)), or (2) as shown in FIG. 12 (a), by having pointer type data and pointing to each other, Also good. In the example of FIG. 12A, “equal” has the same meaning and is a mutual pointer, “previous” is a pointer to the preceding data, and “next” is a pointer to the following data. (3) As shown in FIG. 12B, the association may be performed by separately registering the association using a dictionary function or the like. In the example of FIG. 12B, first, an association between properties of a class is registered with Dec Item 1, and Dec Items 2 to 4 show an example of registering an association between each property and a data item mapped to each property.

  In addition to the above, the search system according to the embodiment specifically shows the purchase price of the purchase of the metadata db01 as shown in FIG. As described above, the data items of the transaction CD and the supplier name (Rec2) in the metadata db02 may be associated with each other based on the mapping. About the specific aspect of an association means, you may link | relate by what kind of aspect similarly to the example of said (1)-(3).

  An example of determining the search order based on the attribute information related to the constituent elements of the sentence attached to the data item stored in the atypical data structure database is shown below. This embodiment will be described with reference to FIG.

  In the search system according to the embodiment, the data items stored in the unstructured data structure database are 5W2H (Who, What, When, Where, Why, How, How Many (How Much)) as shown in FIG. You may attach the attribute information regarding a sentence component. In other words, the attribute information is information serving as a background when target data is collected. In the example of FIG. 13, for example, the case of sensed data in a manufacturing operation is shown. As shown in the embodiment, when the accumulated and searched data is the log data of the sensor, the detected date / time information attached to the log data or which sensor is detected is detected. What is necessary is just the information of an apparatus, or the positional information on where it was detected.

  As shown in FIG. 13, the search system according to the embodiment relates to When, for example, when searching for the next data based on the association between data items from image data having “Image01” as a key value. Attribute information is given the highest priority, and then the priority order of attribute information related to Where is set higher. The search system according to the embodiment sorts the data by the value of the attribute information according to the setting, and the image data and the attribute information (When is “20170930” and Where is “factory A”) match. The search order can be determined so that “Voice01” having a key value in the item to be searched is prioritized over “Voice02”. Thereby, the search system according to the embodiment can be extracted according to the purpose of the user.

  The program in the present invention may be provided in a state stored in a computer-readable storage medium. The storage medium can store the program in “a tangible medium that is not temporary”. The storage medium can include any suitable storage medium such as HDD or SDD, or a suitable combination of two or more thereof. The storage medium may be volatile, non-volatile, or a combination of volatile and non-volatile. The storage medium is not limited to these examples, and any device or medium may be used as long as it can store the program.

  Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various changes and modifications based on the present disclosure. Therefore, it should be noted that these variations and modifications are included in the scope of the present disclosure. For example, the functions included in each means, each step, etc. can be rearranged so that there is no logical contradiction, and a plurality of means, steps, etc. can be combined or divided into one. . Moreover, it is good also as combining suitably the structure shown to each embodiment.

DESCRIPTION OF SYMBOLS 100 Metadata production | generation means 200 Projection production means 300 1st mapping means 400 2nd mapping means 500 3rd mapping means 600 Search processing means 700 Search and joining processing means

Claims (7)

An existing information system constructed and operated for the purpose of supporting a business process based on an information ontology that has a class that becomes knowledge based on the concept of an object and that is linked with one or more properties that specify the class. In a search system that searches from an existing database in use,
Metadata creation means for creating structured metadata from the existing database;
Projection creating means for creating a projection for extracting specific information from the metadata structured by the metadata creating means;
First mapping means for mapping the projection created by the projection creation means to a class of an information ontology database;
A second mapping means for mapping a projection item of the projection to a property of the class in a state where the class and the projection are mapped by the first mapping means;
A mapping system comprising:
An association means for associating data items of the data file stored in the existing database based on the mapping by the first or second mapping means;
Storage means for storing information of the data items in an atypical data structure database;
And a data lake system comprising: a search system comprising: The mapping system, when the projection item is mapped to the property by the second mapping means, and when there is a valid value list for the projection item and the property, the value of the valid value list of the projection item is displayed. A third mapping means for mapping to the value of the valid value list of the property,
The search system according to claim 1, wherein the association unit associates data items of data files stored in the existing database based on the mapping by the first to third mapping units.   The metadata creation means includes physical database information from the existing database, information on data files stored in the database, information on connection between data files, data item information of the data file, and valid data values of the data items. 3. The search system according to claim 1 or 2, wherein structured metadata including: is created.   4. Information from an existing database is obtained by said mapping system via at least one projection mapped to a desired class by selecting a desired class from said information ontology. The search system according to any one of the above items.   Based on the user's request, the data item stored in the atypical data structure database is searched along with the association between the data items to extract the data item that matches the request, and the extracted data item The search system according to any one of claims 1 to 4, wherein the information is obtained by joining the information. The data items stored in the atypical data structure database are accompanied by attribute information related to sentence components,
5. The search order is determined based on the attribute information when searching for information on data items stored in the atypical data structure database along the association of the data. The search system according to any one of the above.   The projection creation means further comprises a unit database, and when it is detected that the unit of the mapped property is different with respect to the projection item of the data having the unit concept, the projection item and the property have 4. The search system according to claim 3, wherein a compatibility method between units is searched from the unit database and unit conversion is performed.

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