KR20130013233A - Method and apparatus for transformating relational database into owl ontology - Google Patents

Method and apparatus for transformating relational database into owl ontology Download PDF

Info

Publication number
KR20130013233A
KR20130013233A KR1020110074765A KR20110074765A KR20130013233A KR 20130013233 A KR20130013233 A KR 20130013233A KR 1020110074765 A KR1020110074765 A KR 1020110074765A KR 20110074765 A KR20110074765 A KR 20110074765A KR 20130013233 A KR20130013233 A KR 20130013233A
Authority
KR
South Korea
Prior art keywords
owl
rdf graph
rdf
class
ontology
Prior art date
Application number
KR1020110074765A
Other languages
Korean (ko)
Other versions
KR101244931B1 (en
Inventor
김명호
최지웅
Original Assignee
숭실대학교산학협력단
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 숭실대학교산학협력단 filed Critical 숭실대학교산학협력단
Priority to KR20110074765A priority Critical patent/KR101244931B1/en
Publication of KR20130013233A publication Critical patent/KR20130013233A/en
Application granted granted Critical
Publication of KR101244931B1 publication Critical patent/KR101244931B1/en

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28Databases characterised by their database models, e.g. relational or object models
    • G06F16/284Relational databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36Creation of semantic tools, e.g. ontology or thesauri
    • G06F16/367Ontology

Abstract

PURPOSE: An ontology web language(OWL) ontology conversion method for a relational type database and a device for the same are provided to generate an extra resource description framework(RDF) graph corresponding to each table without a complex join operation between tables included in the relational type database, thereby reducing OWL ontology conversion time. CONSTITUTION: An information extraction unit(210) extracts schema information and instance information from a relational type database. An OWL ontology generation unit(230) maps the schema information for a table stored in the relational type database on an OWL schema. The OWL ontology generation unit defines the instance information with an entity and generates OWL ontology composed of a generated RDF graph corresponding to each table. An identical entity determination unit(250) determines an identical OWL entity among OWL entities included in different RDF graphs. An deduction adding unit(260) adds a new deduction between the OWL entities, which are included in the different RDF graphs, to the OWL ontology. [Reference numerals] (210) Information extraction unit; (220) Relational type database; (230) OWL ontology generation unit; (240) Ontology database; (250) Identical entity determination unit; (260) Deduction adding unit

Description

Method of converting ontology of relational database and its apparatus {METHOD AND APPARATUS FOR TRANSFORMATING RELATIONAL DATABASE INTO OWL ONTOLOGY}

The present invention relates to a method and apparatus for converting an OWL ontology of a relational database, and more particularly, to a technique for inferring a relationship between entities after generating an OWL ontology from a relational database.

A relational database (R database) is a collection of data items consisting of a series of formalized tables. It is a database in which the structure of the database and the location of the data to be constructed are predetermined. Relational databases also serve as a major data source for delivering data to the Web through Web applications. However, in order to use relational database in semantic web based environment, which is a framework that allows a machine (computer) to process information and relationship between resources in a distributed environment such as the Internet. This must be converted into an OWL ontology.

The OWL (Ontology Web Language) is a language for expressing the ontology on the web and is being standardized by the World Wide Web Consortium (W3C). OWL adds more syntax to represent ontologies based on the existing Resource Description Framework (RDF) and RDF Schema. OWL syntax can be summarized as having three basic elements: class, property, and individual. In addition, OWL 2 Ontology, an additional version of OWL, provides classes, properties, individuals, and data values and is stored as semantic web documents. OWL 2 ontology can be used with information written in RDF, and OWL 2 ontology is mainly exchanged in the form of RDF documents.

The conventional relational database is converted into an OWL ontology using mapping rules as shown in Table 1 below.


Relational database

OWL Ontology

Schema
table Class
FOREIGN KEY (FK) Column Object property Column Data property,
XSD data type

Instance
Row Not specified,
Or anonymous object
Column a constant

Referring to Table 1, in a mapping rule for converting a conventional relational database into an OWL ontology, in the case of a schema, one table except a link table is mapped to a class, and a constraint that references data among columns included in the table ( A foreign key column that is a constrain maps to an object property, and a column that does not contain a foreign key maps to a data property and an XSD data type. In addition, instances are not specifically specified for creating objects for the row data included in the table, or anonymous objects are created. Columns that do not contain a forin key are mapped to constants.

FIG. 1A illustrates an example of a relational database, and FIG. 1B illustrates an example of generating an OWL ontology schema using the conventional method of FIG. 1A. In FIG. 1A, four tables, 'PERSON', 'LECTURE', 'STUDENT', and 'DEPARTMENT', form a relationship by referencing or inheriting data from each other, and each table includes a unique column. Figure 1b shows the mapping of the OWL ontology schema with such a relational database using the mapping rules shown in Table 1. In FIG. 1B, each table is mapped to a class format, and each class is connected to an object attribute. Thus, one relational database can be formed into one RDF graph.

However, in the conventional method of converting to OWL ontology, there is an exception rule for mapping one link table to two object attributes, and when there are three or more columns included in the link table, one cannot convert to OWL ontology. There is a problem that a dependency on object creation occurs by forming a relational database of a single RDF graph. In addition, the conventional OWL ontology conversion method has a problem in that a specific rule for creating an object is not described, or has limitations in terms of scalability and flexibility of an ontology by creating an anonymous object.

SUMMARY OF THE INVENTION The present invention has been made in an effort to provide an OWL ontology inference method and apparatus for generating an OWL ontology without a join operation from a relational database and inferring various relationships between OWL entities of different RDF graphs. .

The OWL ontology conversion method according to an embodiment of the present invention comprises the steps of extracting schema information and instance information from a relational database, mapping the schema information for one or more tables stored in the relational database to an OWL schema, and the instance information. Defining an OWL entity, generating an OWL ontology composed of one or more RDF graphs corresponding to each table, and determining the same OWL entity between OWL entities included in the generated different RDF graphs. And adding new reasoning between the OWL entities included in the different RDF graphs to the OWL ontology.

In addition, the OWL schema, the table is mapped to one upper class, the column of the table is mapped to a data attribute, the key column of the column is a subclass, object attribute, data attribute dependent on the upper class Can be mapped.

In addition, the OWL entity may be created using the name of the table, the name of the key column and the data value of the key column.

In the determining of the same OWL entity, the subclass of the first RDF graph is subordinate to the subclass of the second RDF graph, and the data attribute of the first RDF graph is dependent on the data attribute of the second RDF graph. The data attribute of the first RDF graph is a key attribute of a higher class of the first RDF graph, the data attribute of the second RDF graph is a key attribute of a higher class of the second RDF graph, and the first RDF graph. If the data value of the subclass of the graph and the data value of the subclass of the second RDF graph are the same, the OWL object of the subclass of the first RDF graph and the OWL object of the subclass of the second RDF graph are the same OWL. Can be judged as an individual.

Further, an upper class of the first RDF graph is subordinate to an upper class of the second RDF graph, an object attribute of the first RDF graph is dependent on an object attribute of the second RDF graph, and An object property is a key property of an upper class of the first RDF graph, an object property of the second RDF graph is a key property of an upper class of the second RDF graph, and an OWL object of a lower class of the first RDF graph; If the OWL entity of the lower class of the second RDF graph is the same, the OWL entity of the upper class of the first RDF graph and the OWL entity of the upper class of the second RDF graph may be determined to be the same OWL entity.

The adding of the new inference may include: an object attribute between an upper class of the first RDF graph and a lower class of the second RDF graph, an upper class of the second RDF graph, and a lower class of the first RDF graph. Inference about the object properties of the liver may be added to the OWL ontology.

The OWL ontology converting apparatus according to another embodiment of the present invention comprises an information extraction unit for extracting schema information and instance information from a relational database, mapping the schema information of one or more tables stored in the relational database to an OWL schema, and An OWL ontology generator for generating an OWL ontology composed of one or more RDF graphs corresponding to each table by defining instance information as an OWL object, and the same OWL between OWL entities included in the generated different RDF graphs. The same entity determination unit for judging an entity and an inference addition unit for adding new reasoning between OWL entities to the OWL ontology.

The OWL ontology conversion method and apparatus according to the present invention can shorten the OWL ontology conversion time by generating separate RDF graphs for each table without performing complicated join operations between tables included in the relational database. In addition, by inferring the OWL ontology consisting of separate RDFs for each table first and then inferring more relations between the OWL entities. In addition, even when a relational database includes a link table containing three or more key columns, conversion to OWL ontology is possible. In addition, by creating named entities, you can overcome limitations in terms of ontology's scalability and flexibility.

FIG. 1A illustrates an example of relational table data, and FIG. 1B illustrates an example of generating an OWL schema using a conventional method of the relational table data of FIG. 1A.
2 is a block diagram of an OWL ontology inference apparatus of relational data according to an embodiment of the present invention;
3 is a flowchart of an OWL ontology inference method of relational data according to FIG. 2;
4 is an exemplary diagram for describing generating relational table data of FIG. 1A as an OWL schema in the OWL ontology inference method according to FIG. 3;
5A and 5B are exemplary diagrams for explaining inference between identical OWL entities in different OWL ontology among the OWL ontology inference method according to FIG. 3.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. The terms used are terms selected in consideration of the functions in the embodiments, and the meaning of the terms may vary depending on the user, the intention or the precedent of the operator, and the like. Therefore, the meaning of the terms used in the following embodiments is defined according to the definition when specifically defined in this specification, and unless otherwise defined, it should be interpreted in a sense generally recognized by those skilled in the art.

FIG. 2 is a block diagram of an apparatus for converting an OWL ontology of a relational database according to an embodiment of the present invention, and FIG. 3 is a flowchart of a method for converting an OWL ontology of a relational database using the apparatus for converting an OWL according to FIG. 2.

The OWL ontology converter 200 includes an information extractor 210, a relational database 220, an OWL ontology generator 230, an ontology database 240, the same entity determiner 250, and an inference adder 260. Include. First, the information extracting unit 210 extracts schema information and instance information from the relational database 220 in which table data including a reference or inheritance relationship between a plurality of tables is stored (S310). In relational database 220, the structure of the database and the location of the data to be constructed are predetermined. The schema information is the structure of the relational database 220. It describes the relationship between the objects, the object composed of the property and the set of properties, and the constraints that must be maintained. 220 shows how the data is stored. The instance information refers to data values stored in the data structure of the relational database 220. The information extracting unit 210 outputs the information extracted from the relational database 220 to the OWL ontology generator 230.

Next, the OWL ontology generation unit 230 stores axioms that are explicit rules for the relational database to be used in the semantic web. The OWL ontology generator 230 maps schema information of a relational table composed of one or more tables stored in the relational database 200 to an OWL schema, defines instance information as an OWL object, and generates one or more corresponding tables. The OWL ontology consisting of the RDF graph is generated and stored in the ontology database 240 (S320). For example, in the relational database 220 in which four tables form a relationship with each other, the OWL ontology generator 230 maps a schema and an instance of the relational database 220 to an OWL schema and an OWL entity. The conversion rule to OWL ontology will be described in Table 2 below.


Relational database

OWL Ontology

Schema
table class
Key column Classes, object properties,
Data attributes, XSD data type
column Data attributes, XSD data type
Instance
low individual
Key column Object, constant column a constant

Referring to Table 2, when the schema of the relational database is converted into the OWL schema, the OWL ontology generator 230 maps one table to one super class, and the columns included in the table are data attributes and XSD data types. Map to. In this case, when the column is a key column with constraints such as a primary key and a forest key, the corresponding key column is mapped to a lower class, an object attribute, a data attribute, and an XSD data type that depend on the upper class. Thus, one RDF graph is generated for one table, and the relationships between classes in the RDF graph are maintained in dependencies.

In addition, when converting an instance of a relational database into an OWL instance, an object is created using data values of key columns among the columns of the table. Therefore, unlike the conventional OWL ontology conversion method, an anonymous entity is not generated by explicitly expressing a conversion rule. Hereinafter, the conversion to the OWL ontology will be described with reference to FIG. 4.

FIG. 4 is an exemplary diagram for explaining converting the relational database of FIG. 1A into an OWL ontology among the OWL ontology transformation methods according to FIG. 3.

Referring to FIG. 4, the OWL ontology generator 230 generates four RDF graphs in the form of an OWL schema using the mapping rules of Table 2 with respect to the relational database of FIG. 1A. For example, table 'PERSON' is mapped to a parent class that is an OWL schema, and table 'PERSON' is a parent column because it is a key column for the 'ID' column that receives a data reference request from another table among the columns included in the table. It is mapped to a subclass that is an OWL schema that depends on, and object attributes are created between OWL and superclasses, and data attributes are created between OWL schemas and data of each column. However, since the 'NAME' and 'GENDER' columns are not key columns, only data attributes that are OWL schemas between the data specified in the column and the parent class are created. In this way, one OWL ontology is created, consisting of four independent RDF graphs from the four tables associated with each other. In the present invention, the term "superclass" and "subclass" are used to describe the classes in the RDF graph separately, and do not mean a concept of inheritance between classes.

In addition, the OWL ontology generator 230 defines an instance of the relational database as an entity (OWL instance) using the OWL schema class type and one key column (column) data value. For example, when the data of the 'ID' column of the 'STUDENT' table of FIG. 1A is' PS7369 ', in the' STUDENT 'RDF graph of FIG. 4, the' STUDENT 'of the upper class type, which is the OWL schema, and the key column' The upper class entity 'STUDENT_ID_PS7369' can be created using 'PS7369', which is the data of the ID column. In addition, a subclass object 'STUDENT.ID_PS7369' can be created using 'STUDENT ID' of a subclass type, which is an OWL schema, and 'PS7369', which is data of a 'ID' column, which is a key column. As such, the OWL ontology generator 230 generates each table in the relational database as an independent RDF graph, and defines each object to generate one OWL ontology.

Referring again to FIGS. 2 and 3, the same entity determination unit 250 next determines the same OWL entity among OWL entities included in a plurality of RDF graphs that constitute one OWL ontology generated by the OWL ontology generator. (S330). The purpose of determining whether the same object is between OWL objects is to determine the reference relationship or inheritance relationship between different table data. In this case, whether or not dependencies can be determined through axioms such as 'subClassOf', 'subPropertyOf', and 'HasKey' between each class.

The same entity determiner 250 determines whether or not there is an identity between classes generated from a key column in order to determine a reference relationship between tables in a relational database. For example, a subclass of the first RDF graph is subordinate to a subclass of the second RDF graph, the data attribute of the first RDF graph is dependent on the data attribute of the second RDF graph, and the data attribute of the first RDF graph is The key attribute of the parent class of the first RDF graph, the data attribute of the second RDF graph is the key attribute of the parent class of the second RDF graph, and the data value of the subclass of the first RDF graph and the child of the second RDF graph. If the data value of the class is the same, the OWL object of the subclass of the first RDF graph and the OWL object of the subclass of the second RDF graph are determined to be the same object. In this case, the conversion of the primary key (PK) column into the OWL ontology in the relational database 220 is called a key attribute.

In addition, the same entity determination unit 250 determines the identity between the upper classes generated from the table subject to determine the inheritance relationship between the tables in the relational database. In this case, the inheritance relationship is a kind of reference relationship, which means that the relationship between tables is not a simple reference but a parent-child relationship. For example, the superclass of the first RDF graph is dependent on the superclass of the second RDF graph, the object properties of the first RDF graph are dependent on the object properties of the second RDF graph, and the object properties of the first RDF graph are The key attributes of the parent class of the first RDF graph, the object attributes of the second RDF graph are the key attributes of the parent class of the second RDF graph, and the OWL objects of the subclasses of the first RDF graph and the subclasses of the second RDF graph. If the OWL objects of the same are the same, the OWL object of the upper class of the first RDF graph and the OWL object of the upper class of the second RDF graph are determined to be the same object.

5A and 5B are exemplary diagrams for explaining inference between identical OWL entities included in different RDF graphs among the OWL ontology transformation methods according to FIG. 3.

FIG. 5A illustrates a STSTENT DEP subclass of different RDF graphs in order to infer a reference relationship between a 'STUDENT' table and a 'DEPARTMENT' table in the relational database of FIG. 1A. ID's and 'DEP. Determine identity between entities of ID '. In this case, the 'STUDENT DEP. ID 'class is' DEP. ID 'class, and' STUDENT DEP. ID attribute is set to 'DEP. ID 'depends on the data attribute of the' IDUDENT DEP. The data attribute of class' ID 'is the key attribute of class' STUDENT', and the 'DEP. Data attribute of class' ID 'is a key attribute of class' DEPARTMENT', and the 'STUDENT DEP. ID 'data value and' DEP. ID 'class has the same data value,' STUDENT DEP. ID's and 'DEP. The object of ID 'is judged to be the same object.

Meanwhile, FIG. 5B illustrates the sameness between an object of 'PERSON' and an object of 'STUDENT', which are upper classes of different RDF graphs, to infer the inheritance relationship between the 'PERSON' table and the 'STUDENT' table in the relational database of FIG. 1A. do. In this case, the 'PERSON' class depends on the 'STUDENT' class, the object properties of the 'PERSON' class are dependent on the object properties of the 'STUDENT' class, and the object properties of the 'PERSON' class are the key properties of the 'PERSON' class. , And if the object property of class 'STUDENT' is a key property of class 'STUDENT' and the class 'PERSON ID' which is a subclass of 'PERSON' is the same as class 'STUDENT ID' which is a subclass of 'STUDENT', The object of 'and the object of' STUDENT 'are regarded as the same object.

Referring to FIGS. 2 and 3 again, the inference adding unit 260 adds a new reasoning between the same OWL entities to the OWL ontology (S340). The OWL ontology generator 230 generates RDF graphs in which each table of the relational database is independent of each other. Therefore, there is no inference between different RDF graphs. However, the inference adder 260 adds new inferences between independent RDF graphs according to the determination result of the same entity determiner 250.

For example, in the case of FIG. 5A, the STUDENT DEP. ID's and 'DEP. Since the object of ID 'is considered to be the same object, the subclass' DEP.', Which is subordinate to the object of 'DEPARTMENT' which is another superclass from the object of the superclass' STUDENT '. An object attribute is added to the object with ID '. In addition, a subclass 'STUDENT DEP.' That depends on an object of another parent class 'STUDENT' from an object of the parent class 'DEPARTMENT'. An object attribute is added to the object with ID '.

Meanwhile, in the case of FIG. 5B, since the object of 'PERSON' and the object of 'STUDENT' are determined to be the same object, a subclass' depending on the object of another parent class' STUDENT 'from an object of' PERSON ', which is a superclass, STUDENT ID "," STUDENT DEP. An object attribute is added to the object with ID '. In addition, an object attribute is added from the object of the upper class 'STUDENT' to the object 'PERSON ID', which is a subclass that depends on another object of the upper class 'PERSON'.

FIG. 6A illustrates an example of a relational database including a link table, and FIG. 6B illustrates an example of converting the relational database of FIG. 5A into an OWL ontology using the OWL ontology transformation method of FIG. 3.

Referring to FIG. 6A, the 'ORDER ITEM' table becomes a link table. The link table refers to a case in which a plurality of columns included in the table have a primary key (PK) and an attribute of a forin key (FK). As an exception of the mapping rules shown in Table 1 of the conventional OWL transformation method, one table is mapped to two object attributes during OWL transformation of a relational database. However, in the conventional OWL conversion method, when there are three or more columns included in the link table, there is no rule for mapping the OWL ontology. However, when the OWL transformation of the relational database of FIG. 6A is performed using the mapping rules shown in Table 2, it is possible to convert the OWL ontology as shown in FIG. 6B.

In the OWL transformation method of the present invention, each table is generated as a separate RDF graph, and the OWL ontology conversion is possible even if two columns do not necessarily exist in the link table because the new relationship is inferred by identifying the sameness of the OWL entity among them. Do. In FIG. 6B, when the same entity described above is determined, a new reference relationship is formed between the RDF graph of the 'ORDER' table and the RDF graph of the 'ORDER ITEM' which is the link table and the RDF graph of the 'PRODUCT' table. .

The OWL ontology conversion method and apparatus according to the present invention can shorten the OWL ontology conversion time by generating separate RDF graphs for each table without performing complicated join operations between tables included in the relational database. In addition, by inferring the OWL ontology consisting of separate RDFs for each table first and then inferring more relations between the OWL entities. In addition, even when a relational database includes a link table containing three or more key columns, conversion to OWL ontology is possible. In addition, by creating named entities, you can overcome limitations in terms of ontology's scalability and flexibility.

The present invention has been described above with reference to the preferred embodiments described with reference to the drawings, but is not limited thereto. Accordingly, the invention should be construed by the description of the claims, which are intended to cover obvious variations that can be derived from the described embodiments.

200: OWL ontology converter 210: information extraction unit
220: relational database 230: OWL ontology generator
240: ontology database 250: the same object determination unit
260: adding reasoning

Claims (12)

Extracting schema information and instance information from the relational database;
Mapping the schema information of at least one table stored in the relational database to an OWL schema, defining the instance information as an OWL entity, and generating an OWL ontology composed of one or more RDF graphs generated for each table. ;
Determining the same OWL entities among the OWL entities included in the generated different RDF graphs; And
And adding new inferences between OWL entities included in the different RDF graphs to the OWL ontology.
The method of claim 1, wherein the OWL schema,
OWL ontology of a relational database where the table maps to one superclass, the columns of the table map to data attributes, and the key columns of the columns map to subclasses, object attributes, and data attributes that depend on the superclass. How to convert.
The method of claim 1, wherein the OWL entity,
OWL ontology conversion method of the relational database is generated using the name of the table, the name of the key column and the data value of the key column.
The method of claim 1, wherein determining the same OWL entity comprises:
A subclass of the first RDF graph is subordinate to a subclass of the second RDF graph, the data attribute of the first RDF graph is dependent on the data attribute of the second RDF graph, and the data attribute of the first RDF graph is A key attribute of a higher class of the first RDF graph, a data attribute of the second RDF graph is a key attribute of a higher class of the second RDF graph, and a data value of the lower class of the first RDF graph and the second attribute And the OWL object of the lower class of the first RDF graph and the OWL object of the lower class of the second RDF graph as the same OWL object if the data values of the subclass of the RDF graph are the same.
5. The method of claim 4,
An upper class of the first RDF graph is dependent on an upper class of the second RDF graph, an object property of the first RDF graph is dependent on an object property of the second RDF graph, and an object property of the first RDF graph The key property of the upper class of the first RDF graph, the object property of the second RDF graph is the key property of the upper class of the second RDF graph, and the OWL object and the first object of the lower class of the first RDF graph. 2 If the OWL object of the lower class of the RDF graph is the same, OWL ontology conversion method of the relational database to determine the OWL object of the upper class of the first RDF graph and the OWL object of the upper class of the second RDF graph as the same OWL object. .
The method of claim 4 or 5, wherein adding the new inference,
Inference about object properties between an upper class of the first RDF graph and a lower class of the second RDF graph and an object property between an upper class of the second RDF graph and a lower class of the first RDF graph are included in the OWL ontology. How to convert OWL ontology of relational database to add.
An information extraction unit for extracting schema information and instance information from a relational database;
OWL ontology that generates the OWL ontology consisting of one or more RDF graphs generated by mapping the schema information of one or more tables stored in the relational database to an OWL schema and defining the instance information as an entity. Generation unit;
An identical entity determination unit that determines the same OWL entity among the OWL entities included in the generated different RDF graphs; And
And an inference adder for adding new inferences between OWL entities included in the different RDF graphs to the OWL ontology.
The method of claim 7, wherein the OWL schema,
OWL ontology of a relational database where the table maps to one superclass, the columns of the table map to data attributes, and the key columns of the columns map to subclasses, object attributes, and data attributes that depend on the superclass. Inverter.
The method of claim 7, wherein the OWL entity,
The OWL ontology converter of the relational database is generated using the class format of the OWL schema and the data value of the key column of the columns of the table.
The method of claim 7, wherein the same entity determination unit,
A subclass of the first RDF graph is subordinate to a subclass of the second RDF graph, the data attribute of the first RDF graph is dependent on the data attribute of the second RDF graph, and the data attribute of the first RDF graph is A key attribute of a higher class of the first RDF graph, a data attribute of the second RDF graph is a key attribute of a higher class of the second RDF graph, and a data value of the lower class of the first RDF graph and the second attribute And an OWL object of a lower class of the first RDF graph and an OWL object of a lower class of the second RDF graph as the same OWL object if the data values of the subclass of the RDF graph are the same.
The method of claim 10,
An upper class of the first RDF graph is dependent on an upper class of the second RDF graph, an object property of the first RDF graph is dependent on an object property of the second RDF graph, and an object property of the first RDF graph The key property of the upper class of the first RDF graph, the object property of the second RDF graph is the key property of the upper class of the second RDF graph, and the OWL object and the first object of the lower class of the first RDF graph. 2 If the OWL objects of the lower class of the RDF graph are the same, the OWL ontology converter of the relational database determines that the OWL object of the upper class of the first RDF graph and the OWL object of the upper class of the second RDF graph are the same OWL objects. .
The method of claim 10 or 11, wherein the inference addition unit,
Inference about object properties between an upper class of the first RDF graph and a lower class of the second RDF graph and an object property between an upper class of the second RDF graph and a lower class of the first RDF graph are included in the OWL ontology. OWL ontology converter for the relational database to add.
KR20110074765A 2011-07-27 2011-07-27 Method and apparatus for transformating relational database into owl ontology KR101244931B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
KR20110074765A KR101244931B1 (en) 2011-07-27 2011-07-27 Method and apparatus for transformating relational database into owl ontology

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
KR20110074765A KR101244931B1 (en) 2011-07-27 2011-07-27 Method and apparatus for transformating relational database into owl ontology

Publications (2)

Publication Number Publication Date
KR20130013233A true KR20130013233A (en) 2013-02-06
KR101244931B1 KR101244931B1 (en) 2013-03-18

Family

ID=47893711

Family Applications (1)

Application Number Title Priority Date Filing Date
KR20110074765A KR101244931B1 (en) 2011-07-27 2011-07-27 Method and apparatus for transformating relational database into owl ontology

Country Status (1)

Country Link
KR (1) KR101244931B1 (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103810338A (en) * 2014-02-13 2014-05-21 北京邮电大学 Field oriented internet of things resource modeling system
KR20220146110A (en) 2021-04-23 2022-11-01 현대자동차주식회사 Adhesion type Corner Module and the Method of Controlling thereof
KR20220149162A (en) 2021-04-30 2022-11-08 김민수 Electric Motor Wheel to Drive Shaft

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101650005B1 (en) * 2014-01-14 2016-08-22 한국과학기술원 A method for avoiding cross-node join in the database stored in a distributed manner for a large-scale social network system

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100902843B1 (en) * 2007-07-23 2009-06-16 고려대학교 산학협력단 Method for ontology form creation from a database and Apparatus thereof

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103810338A (en) * 2014-02-13 2014-05-21 北京邮电大学 Field oriented internet of things resource modeling system
KR20220146110A (en) 2021-04-23 2022-11-01 현대자동차주식회사 Adhesion type Corner Module and the Method of Controlling thereof
KR20220149162A (en) 2021-04-30 2022-11-08 김민수 Electric Motor Wheel to Drive Shaft

Also Published As

Publication number Publication date
KR101244931B1 (en) 2013-03-18

Similar Documents

Publication Publication Date Title
Sevilla Ruiz et al. Inferring versioned schemas from NoSQL databases and its applications
Barbau et al. OntoSTEP: Enriching product model data using ontologies
Panov et al. OntoDM: An ontology of data mining
Bikakis et al. The XML and semantic web worlds: technologies, interoperability and integration: a survey of the state of the art
Third et al. Linked data indexing of distributed ledgers
US20120102456A1 (en) System and Method of Annotating Class Models
EP2506140A1 (en) Ontology updating apparatus, method and system
Khattak et al. Mapping evolution of dynamic web ontologies
KR101244931B1 (en) Method and apparatus for transformating relational database into owl ontology
Li et al. Graph-based semantic evolution for context information management platforms
Welten et al. Dams: A distributed analytics metadata schema
Berkani et al. A value-added approach to design BI applications
Fan et al. Mapping fuzzy RDF (S) into fuzzy object‐oriented databases
Zhang et al. Construction of fuzzy ontologies from fuzzy XML models
Tong Mapping object-oriented database models into RDF (S)
Biletskiy et al. Identification and resolution of conflicts during ontological integration using rules
US20230072311A1 (en) Apparatus and method for transforming unstructured data sources into both relational entities and machine learning models that support structured query language queries
Malik et al. Remote access capability embedded in linked data using bi-directional transformation: Issues and simulation
Minutolo et al. An automatic method for deriving OWL ontologies from XML documents
Rivero et al. MostoDE: A tool to exchange data amongst semantic-web ontologies
Yang Variable weight semantic graph‐based ontology mapping method
Alaoui et al. Automatic Mapping of Relational Databases to OWL Antology
Chaouni et al. MDA based-approach for UML Models Complete Comparison
Bhatt et al. OntoMove: A knowledge based framework for semantic requirement profiling and resource acquisition
Palmonari AER IA: Extending SKOS for the practical, yet well-founded, representation and integration of Web schemas in the large.

Legal Events

Date Code Title Description
A201 Request for examination
E902 Notification of reason for refusal
E701 Decision to grant or registration of patent right
GRNT Written decision to grant
FPAY Annual fee payment

Payment date: 20170117

Year of fee payment: 5

FPAY Annual fee payment

Payment date: 20180108

Year of fee payment: 6

FPAY Annual fee payment

Payment date: 20190216

Year of fee payment: 7