Extracting Entity Relationship Diagram (ERD) From Relational Database Schema

Hala Khaled Al-Masree 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.3

Database Reverse Engineering (DBRE) is an operation used to extract requirements from any system. The operation is implemented to facilitate the understanding of the system that has a little documentation about design and architecture. DBRE is a very important process used when database designers would like to expand the system or transition to the latest technology in DBRE fields. In the relational database model DBRE try to extract Entity Relationship Diagram (ERD) from relational database schema. Database designers find content of the data for a lot of attributes are not related with their names. In this paper, proposed methodology used to extract ERD from relational database schema with the attributes related with their names, both types of entities regular and weak entity, relationships and keys, which are found in the table that has extracted the relational database schema. The basic inputs of this approach are relational database schema that generated from database. The relational database schema used to extract the information about ERD. After that, obtain information that contain keywords help database designers to extract entities and their attributes semantics related with their names from relational database schemas. Then, Determine primary keys, foreign keys and constraints of the database system. In the final step, the ERD is successfully extracted

객체-관계형 데이터베이스 설계를 위한 UML 확장 - Oracle11g를 중심으로-

주경수 ( Kyung-soo Joo ),조도형 ( Do-hyung Jho ) 한국인터넷정보학회 2011 인터넷정보학회논문지 Vol.12 No.6

현재의 응용시스템들은 복합관계성으로 관련지어진 복합객체를 갖고 있다는 특징을 갖는다. 이러한 특징은 기존의 관계형 데이터베이스로 표현하기에는 한계가 있어 관계형 데이터베이스는 객체-관계형 데이터베이스로 확장되었다. 이에 따라서 기존의 관계형 데이터베이스 설계 방법론과 같은 객체-관계형 데이터베이스 설계 방법론이 요구된다. 본 논문에서는 스테레오타입과 태그값 그리고 제약조건을 이용한, UML 클래스다이어그램 확장에 기반하여 객체-관계형 데이터베이스를 위한 통합된 설계방법론을 개발한다. 아울러 확장된 UML 클래스다이어그램을 객체-관계형 데이터베이스 스키마로의 변환을 위한 가이드라인을 제시한다. 개발한 설계방법론에서 사용하는 객체-관계형 모델은 SQL:1999를 이용하였으며, 객체-관계형 데이터베이스 구현은 Oracle11g로 하였다. 많은 객체-관계형 DBMS는 존재하지만 객체-관계형 데이터베이스설계에 있어서 일관된 방법론은 제시되지 않았다. 본 논문에서 제시하는 방법론을 적용함으로써 일관된 방법으로 객체-관계형 데이터베이스 설계를 가능하게 한다. 사례 연구로, 제안한 설계방법론을 컴퓨터교실 예약시스템에 대하여 적용한다. The current applications can be characterized as consisting of complex objects related by complex relationship. Therefore the relational database has been extended to object-relational database because of the complex objects. Accordingly, we need database design methodology for object-relational database. In this pager, we develop an integrated design methodology based on a extended UML class diagram for object-relational database. We make the extend UML class diagram by adding new stereotypes for object-relational database. Also we propose a guideline for transforming the extended UML class diagram to object-relational database schema. We use SQL:1999 as a object-relational data model and Oracle11g as a target object-relational database. We can build more easily and efficiently object-relational database for Oracle11g by using our methodology. Finally we applied our methodology on a computer classroom reservation system for evaluation the methodology.

베베른의 ≪관현악을 위한 변주곡 작품 30≫에 대한 관계형 데이터베이스 기반 음고 차원 분석

김진호 ( Jin Ho Kim ) 한국음악학회 2012 한국음악학회논문집 음악연구 Vol.49 No.-

본 논문은 오스트리아의 작곡가 베베른(Anton von Webern, 1883-1945)의 ≪관현악을 위한변주곡 작품 30≫의 악보를 컴퓨터 프로그래밍 모델인 관계형 데이터베이스 모델로 표현한 후이를 SQL(Structured Query Language)이라는 컴퓨터 언어를 통해 데이터를 조작, 연산, 검색하는 작업을 음악분석에 갈음하는 것으로 보며, 이러한 분석 과정과 결과, 이익 등을 다루고 있다. 악보의 한 음표는 데이터베이스에서의 하나의 실체로 생각될 수 있다. 음표는 음가, 음의 강도등 매개변수적 특성 값을 갖는다. 우리의 데이터베이스 체계에서 각각의 특성 값은 하나의 열위에 있는 여러 행들 혹은 칼럼들(rows/columns)에서 원자적 값들로 표현된다. ≪변주곡≫의 모든 음표들을 이러한 열과 행들의 총체인 관계형 테이블들(tables)로 표현한 새로운 컴퓨터 악보는 다양한 음악분석적 접근을 용이하게 해준다. 관계형 데이터 모델로의 악보 표현은 이후에 이어질특별한 어떤 분석, 즉 컴퓨터를 통해 요소들의 관계성을 아주 쉽고 빠르며 대규모로 확인하는 작업을 실행하기 위해 행해진 것이다. 예술적이고 복잡한 대규모의 현대음악에 대해 이렇게 쉽고 빠르며 대규모로 행해진 분석이 가능할 수 있었던 것은 악보에 제시되었던 요소들의 관계성을 악보에 비해 보다 용이하게 확인해줄 수 있는 다른 표현, 즉 관계형 데이터 모델로의 악보 표현이 있었기 때문이다. 어렵게 한번 만들어진 악보가 그 이후 여러 분석자들에게 분석의 대상이 될수 있는 것처럼, 우리의 컴퓨터 악보 역시 이후의 여러 분석자들에게 각자의 방식과 지향에 따라 분석될 수 있는 대상이 될 것이다. We utilized a computer in order to represent the score of Anton Webern`s Variations for Orchestra op.30 (1941) by the relational data model, and to analyze this relational data score in various ways: A note in a score, as other musical objects, can be considered as an entity in a database having some parametrical properties. In our database system, these are represented by atomic values in some columns on a line. The representation of all notes in a score in the relational form of tables as a totality of columns and lines facilitates the access to the music analysis of open character: Using SQL language, each can interrogate following each problematic our database which represents and stores a score in the relational data form. As an example of application of the concept of the "Relational Database-aided Music Analysis", the score of Webern`s Variations for Orchestra is both represented and stored in the relational data model, and analyzed not only in a classificatory and paradigmatic way but also from the point of view of information theory, set theory, etc.: All serial sets, all intervals, and all chords in the score are retrieved, as a result one can constitute total serial map of the score, verify the predominant intervals and chord types are recognized and calculated.

Privacy Disclosure and Preservation in Learning with Multi-Relational Databases

Hongyu Guo,Herna L. Viktor,Eric Paquet 한국정보과학회 2011 Journal of Computing Science and Engineering Vol.5 No.3

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

Privacy Disclosure and Preservation in Learning with Multi-Relational Databases

Guo, Hongyu,Viktor, Herna L.,Paquet, Eric Korean Institute of Information Scientists and Eng 2011 Journal of Computing Science and Engineering Vol.5 No.3

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

데이터베이스에서 관계의 추출 및 그래프 데이터베이스를 이용한 시각화 방법

박우창(Uchang Park) 한국정보기술학회 2016 한국정보기술학회논문지 Vol.14 No.10

One of drawbacks of relational DBMS is finding relationships between data because relationship between data is separated between tables. In this paper, we propose a method to visualize the relationship in the relational database by using graph database which is suitable to represent entity and its relationship. First, we transform the schema of relational database to schema graph, and change tuple or attribute of tuple as node and foreign key or relationship of attribute to edges, store to graph database and finally visualize data using visualization interface of graph database. Visualization gives intuitive understanding of data relationship, and utilizing graph database gives us additional merits of querying the visual data recursive query easily.

함수적 종속관계를 이용한 XML DTD의 관계형 스키마 변환

이중화,이만식,윤홍원,Lee Jung-hwa,Lee Man-sik,Yun Hong-won 한국정보통신학회 2004 한국정보통신학회논문지 Vol.8 No.7

본 논문에서는 XML DTD를 관계형 데이터 베이스 스키마로 변환하기 위해 제안된 Hybrid Inlining 알고리즘을 확장하여 기존의 알고리즘이 갖고 있는 N:N 관계를 갖는 DTD의 정규화 위배 사항에 대해서 알아보고 이를 해결하기 위해 Hybrid Inlining 확장 알고리즘을 제안한다. 또한 실험을 통해 본 논문에서 제안한 알고리즘이 N:N 관계를 갖는 DTD의 정규형 위배 문제를 해결하였음을 입증하였다. We have to convert XML DTD into relational database schema for storing XML Document at relational database. Hybrid inlining algorithm are used for converting XML DTD to relational database schema. But this method have some problem. That is the relational database schema have N:N relationship are created according this method are not satisfied with third normal from. Therefore, We proposed Extended Hybrid inlining algorithm for solving this problem in this paper.

μE – Automation Framework

Mohammad Almseidin,Khaled Alrfou’ 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.3

The Entity-Relationship and relational database schema are the most popular methodology for designing database. Several tools have been developed to support drawing an ER - diagram or drawing Relational Database Schema (RDB). This paper aims to develop framework called μE that can help database designers for mapping ER-diagram to Relational database schema and vice versa. μE is an automation framework for mapping. μE framework improves reverse engineering techniques and useful with legacy system. Architecture and implementation of μE framework are present in this paper.

동아시아 4개 언어 한자어 데이터베이스의 구축과 과제

신웅철 단국대학교 동양학연구원 2022 東洋學 Vol.- No.86

In this paper, we introduced the construction process and current status of the “CJKV Sinoxenic Words Database,” which connects Sinoxenic words in Korean, Chinese, Japanese, and Vietnamese, focusing on the meaning of vocabulary, and presented an attempt on the possibility of supplementation and expansion. This database was established for the purpose of analyzing and identifying the nature of East Asian civilization through common cultural assets called Chinese characters. In the existing database construction covering Sinoxenic words in various East Asian languages, the vocabulary of different languages was connected through notation, so it does not properly refelct the difference in register of Sinoxenic vocabulary in each language. The design of this database focused on semantic correspondence, not on the notation or form of Sinoxenic words. First of all, the Korean entry words, which is the reference point for database construction, was selected from the “Basic Korean Dictionary”. Subsequently, not only did it respond meaningfully to the Korean words, but it also selected Chinese, Japanese, and Vietnamese equivalents that did not have a large gap in terms of vocabulary regiter. The Sinoxenic words from four languages divided into four separate tables for each language, and the same ID was assigned to the corresponding Sinoxenic words. The vocabulary of each language table is connected to the structure of a Relational Database through an ID based on semantic response. In addition, in each vocabulary of the four East Asian languages, semantic information was cited and entered from a dictionary of a certain size or larger for each language. And based on that, tags representing the semantic attributes of vocabulary were included as separate fields. It can be pointed out that the limitation of this database is that it is a closed structure that contains information on a limited layer of individual vocabulary in a plan manner. In the future, it will be possible to increase the usability and academic value of this database by creating a dataset that describes the relationship between individual vocabulary in the form of RDF to facilitate visualization of data and linkage with other databases. In addition, it is necessary to aim for a cyclical model in which the research results on East Asian civiliazation created through this database are reflected in the expansion and supplementation of the database. 본 논문에서는 한국어, 중국어, 일본어, 베트남어의 한자어를 어휘의 의미를 중심으로 연결한 ‘동아시아 4개언어 한자어 데이터베이스’의 구축 과정과 현황에 대해 소개하고 향후 보완 및 확장의 가능성에 대한 시론을제시하였다. 이 데이터베이스는 한자어라는 공통 문명 자산을 통해 동아시아 한자문명의 성격을 분석하고 규명하기 위한 목적으로 구축되었다. 기존에 시도된 동아시아 여러 언어의 한자어를 망라하는 데이터베이스 구축에서는 표기를 매개로 서로 다른 언어의 어휘를 연결한 것이었기 때문에 동형 한자어가 각 언어에서 갖는어휘적 위상의 차이가 적절히 반영되지 못하는 한계가 확인된다. 본 데이터베이스의 설계에서는 단어의 표기나 형태가 아닌 의미적 대응 관계에 주안점을 두었다. 우선 데이터베이스 구축의 기준점이 되는 한국어 표제어를 “한국어 기초사전”에 수록된 한자어로부터 선별하였다. 이어서 한국어 표제어에 의미적으로 대응할뿐만 아니라 사용역의 측면에서도 격차가 크지 않은 중국어, 일본어, 베트남어의 대역어를 선정하였다. 이렇게 선별하여 확보한 표제어 및 대역어는 언어별로 4개의 별도 테이블로 나누어 작성하였고 서로 대응하는 표제어와 대역어에는 동일한 ID를 부여하였다. 의미적 대응에 기반한 ID를 통해 각 언어별 테이블의 어휘가 관계형 데이터베이스의 구조로 연결된다. 또한 동아시아 네 언어의 각 어휘에는 각 언어 별로 일정 규모이상의 사전으로부터 의미정보를 인용하여 입력하였고, 그것을 바탕으로 어휘의 의미속성을 대표할만한 태그를 별도의 필드로 수록하였다. 본 데이터베이스의 한계로는 개별 어휘라는 한정된 층위의 개체 정보를 평면적으로 수록한 닫힌 구조라는점을 지적할 수 있다. 향후 RDF 형식으로 개별 어휘 간의 관계성을 입체적으로 기술한 데이터셋을 작성하여데이터의 시각화와 타 데이터베이스와의 연계를 용이하게 함으로써 본 데이터베이스의 사용성과 학술적 이용가치를 높일 수 있을 것이다. 또한 본 데이터베이스를 통해 창출된 동아시아 한자문명에 대한 연구 성과가 다시 데이터베이스의 확장 및 보완으로 반영되는 순환적 모델을 지향해야 한다.

다단계 객체 모델을 다단계 관계형 데이터베이스로 변환

심갑식 진주산업대학교 1997 산업과학기술연구소보 Vol.- No.4

In a multilevel database application, all of the entities(which include the representation of the humans, events, and activites of some slice of the real world of interest) are classified at different security levels. The multilevel object model captures the static aspects of the application. That is, it defines the object, the relationships between objects, the security levels of the objects, and those of the relationships. This paper presents methodologies of mapping the object model(classes, cover storied, assocciations, single inheritance and multiple inheritance) into a multilevel relational database. The focus is on the relational model as it is still the most popular one for multilevel environments. Designing a good multilevel relational database is a two-step process. During the first step, the object model is transformed into a collection of relations. During the second step, the relations are normalized accoiding to a theory of multilevel relational databases yet to be developed. This paper is concerned with just the first step.