• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.193-206
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• 2012

Keys play a fundamental role in all data models. They allow database systems to uniquely identify data items, and therefore, promote efficient data processing in many applications. Due to this, support is required to discover keys. These include keys that are semantically meaningful for the application domain, or are satisfied by a given database. We study the discovery of keys from SQL tables. We investigate the structural and computational properties of Armstrong tables for sets of SQL keys. Inspections of Armstrong tables enable data engineers to consolidate their understanding of semantically meaningful keys, and to communicate this understanding to other stake-holders. The stake-holders may want to make changes to the tables or provide entirely different tables to communicate their views to the data engineers. For such a purpose, we propose data mining algorithms that discover keys from a given SQL table. We combine the key mining algorithms with Armstrong table computations to generate informative Armstrong tables, that is, key-preserving semantic samples of existing SQL tables. Finally, we define formal measures to assess the distance between sets of SQL keys. The measures can be applied to validate the usefulness of Armstrong tables, and to automate the marking and feedback of non-multiple choice questions in database courses.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.395-400
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• 1998

This paper presents a geotechnical information system(HGIS) developed for Korea Highway Corporation. To make a database for boring information, characterization study of boring data is carried out. Based on tile study, the HGIS database is developed as a relational database. The HGIS database consists of 23 tables including 13 reference tables. For an effective database management, a boring log program called GEOLOG is developed. GEOLOG can print boring log and store those data to tile HGIS database.

• The Korean Journal of Archival Studies
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• no.34
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• pp.57-105
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• 2012

The CAMS(Central Archives Management System) of NAK(National Archives of Korea) is an important system which receives and manages large amount of electronic records annually from 2015. From the point of view in database design, this paper analyzes the database schema of CAMS and discusses the direction of overall improvement of the CAMS. Firstly this research analyzes the tables for records and folders in the CAMS database which are core tables for the electronic records management. As a result, researchers notice that it is difficult to trust the quality of the records in the CAMS, because two core tables are entirely not normalized and have many columns whose roles are unknown. Secondly, this study suggests directions of normalization for the tables for records and folders in the CAMS database like followings: First, redistributing the columns into proper tables to reduce the duplication. Second, separating the columns about the classification scheme into separate tables. Third, separating the columns about the records types and sorts into separate tables. Lastly, separating metadata information related to the acquisition, takeover and preservation into separate tables. Thirdly, this paper suggests considerations to design and manage the database schema in each phase of archival management. In the ingest phase, the system should be able to process large amount of records as batch jobs in time annually. In the preservation phase, the system should be able to keep the management histories in the CAMS as audit trails including the reclassification, revaluation, and preservation activities related to the records. In the access phase, the descriptive metadata sets for the access should be selected and confirmed in various ways. Lastly, this research also shows the prototype of conceptual database schema for the CAMS which fulfills the metadata standards for records.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.221.2-221.2
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• 2003

Several Compendia are effective in relation with production and supply of pharmaceutical agents in Korea. Those compendia exists only in printed documents, which are not suitable for the analysis of their contents and inter-relationship among them when they have specifications on the same or related pharmaceutical agents. For the analysis of contents of Korean compendia, database system is desinged and all of the available data are entered into relational database system. Every specification was analyzed into several database tables, fields and relations between tables. (omitted)

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.11-28
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• 2001

The Korean functional Genomics Project focuses on stomach and liver cancers. Specimens collected by six hospital teams are used in BNA microarray experiments. Experimental conditions, spot measurement data, and the associated clinical information are stored in a relational database. Microarray database schema was developed based on EBI's ArrayExpress. A diagrammatic representation of the schema is used to help navigate over marty tables in the database. Field description, table-to-table relationship, and other database features are also stored in the database and these are used by a PERL interface program to generate web-based input forms on the fly. As such, it is rather simple to modify the database definition and implement controlled vocabularies. This PERL program is a general-purpose utility which can be used for inputting and updating data in relational databases. It supports file upload and user-supplied filters of uploaded data. Joining related tables is implemented using JavaScripts, allowing this step to be deferred to a later stage. This feature alleviates the pain of inputting data into a multi-table database and promotes collaborative data input among several teams. Pathological finding, clinical laboratory parameters, demographical information, and environmental factors are also collected and stored in a separate database. The same PERL program facilitated developing this database and its user-interface.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.265-273
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• 2000

In relational database management systems(RDBMS), a table consIn relational database management systems(RDBMS), a table consists of sets of records which are composed of a set of attributes. The number of distinct values(NDV) of an attribute denotes the number of distinct attribute values that actually appear in the database records, and is widely used in optimizing queries and supporting statistic queries. Object-relational database management systems(ORBBMSS), however, support the inheritance between tables which enforces an attribute defined in a super-table to be inherited in sub-tables automatically. Hence, in ORDBMSS, not only NDV of an attribute In a single table but also NDV of an attribute in multiple tables(HNDV) is needed. In this paper, we propose a method that calculates HNDV using arrays of attribute value intervals. In this method, an array of attribute value intervals is created for an attribute of interest In each table in a table hierarchy, and HNDV can be calculated or estimated by merging the arrays of attribute value intervals. The proposed method accurately calculates HNDV using small additional storage space and is efficient for an environment where only some of the tables in a table hierarchy are frequently updated.

• The Journal of Korean Medical History
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• v.33 no.2
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• pp.89-104
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• 2020

The purpose of this research is to build a database structure that can be useful for evidence-based medical practices by constructing the knowledge related to oriental medicine in the classical literature knowledge in a form that can utilize new forms of information technology. As a method, "database" is used as a keyword to search published studies in the field of oriental medicine, research is conducted on classic literature knowledge, and studies describing the contents of the data structure are found and analyzed. In conclusion, the original text DB for the preservation of the original texts and the presentation of the supporting texts should include 'Contents Text', 'Tree Structure', 'Herbal Structure', 'Medicine Manufacture', and 'Disease Structure' tables. In order to search, calculate, and automatically extract expressions written in the original text of the old literature, the tool DB should include 'Unit List', 'Capacity Notation List', 'CUI', 'LUI', and 'SUI' tables. In addition, In order to manage integrated knowledge such as herbal, medicine, acupuncture, disease, and literature, and to implement a search function such as comparison of similarity of control composition, the knowledge DB must contain 'dose-controlled medicine name', 'dose-controlled medicine composition', 'relational knowledge', 'knowledge structure', and 'computational knowledge' tables.

• The Journal of Information Systems
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• v.18 no.3
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• pp.327-349
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• 2009

Traditional keyword-based searching methods suffer from low accuracy and high complexity due to the rapid growth in the amount of information. Accordingly, many researchers attempt to implement a so-called semantic search which is based on the semantics of the user's query. Semantic information can be described using a semantic modeling language, such as Topic Map. In this paper, we propose a new method to map a topic map to a traditional Relational Database (RDB) without any information loss. Although there have been a few attempts to map topic maps to RDB, they have paid scant attention to handling multi-role topics. In this paper, we propose a new storage structure to map multi-role topics to traditional RDB. The proposed structure consists of a mapping table, role tables, and content tables. Additionally, we devise a query translator to convert a user's query to one appropriate to the proposed structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.571-574
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• 2003

This research is aimed to automate the generating process of the database from paper based table forms like this work. The registration table has so complicate table structures, ana in this research we used the registration tables as an example of general table structure understanding. We propose a table structure understanding system for some table types, and it has some steps. The first step is that the document images on paper are read from the image scanner. The second step is that a document image segments into some tables. In the third step, the character strings is extracted using image processing technology and the property of the character strings is determined. And the structured database is generated automatically. The proposed system consists of two systems. "Master document generation system" is used for the table form definition, and it doesn′t include the handwritten characters. "Structure analysis system for complete d table" is used for the written form, and it analyzes the table form filled in the handwritten character. We implemented the system using MS Visual C＋＋ on Windows, and it can get the correct extraction rate 98％ among 51 registration tables written by the different students.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.751-756
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• 2013

This paper describes the design and implementation of the multi-function learning community system. Recent trends and related researches regarding the learning community system are surveyed and analyzed. The function sections, data flows, database tables and system interface are designed. Manager and user's modes are implemented and we compare the system functions with other learning communities.