• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.225-233
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• 2007

This paper uses the taxonomy of 3 metadata schema(extraction metadata, warehouse, metadata, and user access metadata) to investigate how to manage metadata and what metadata to manage in data warehouse. In particular, this paper focuses on two kinds of metadata(warehouse metadata and user access metadata) and studies a case about metadata management in a real business world

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.49-54
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• 2018

A data warehouse is a system that collectively manages and integrates data of a company. And provides the basis for decision making for management strategy. Nowadays, analysis data volumes are reaching critical size challenging traditional data ware housing approaches. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we extend the data warehouse design methodology based on relational database using star schema, and have developed a consistent design methodology from information requirement analysis to data warehouse construction for large scale data warehouse construction based on MongoDB, one of NoSQL.

• Korea Journal of Hospital Management
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• v.28 no.3
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• pp.1-14
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• 2023

Purposes: It is very important to establish a clinical data warehouse based on a common data model to offset the different data characteristics of each medical institution and for drug surveillance. This study attempted to establish a clinical data warehouse for Dankook university hospital for drug surveillance, and to derive the main items necessary for development. Methodology/Approach: This study extracted the electronic medical record data of Dankook university hospital tracked for 9 years from 2013 (2013.01.01. to 2021.12.31) to build a clinical data warehouse. The extracted data was converted into the Observational Medical Outcomes Partnership Common Data Model (Version 5.4). Data term mapping was performed using the electronic medical record data of Dankook university hospital and the standard term mapping guide. To verify the clinical data warehouse, the use of angiotensin receptor blockers and the incidence of liver toxicity were analyzed, and the results were compared with the analysis of hospital raw data. Findings: This study used a total of 670,933 data from electronic medical records for the Dankook university clinical data warehouse. Excluding the number of overlapping cases among the total number of cases, the target data was mapped into standard terms. Diagnosis (100% of total cases), drug (92.1%), and measurement (94.5%) were standardized. For treatment and surgery, the insurance EDI (electronic data interchange) code was used as it is. Extraction, conversion and loading were completed. R language-based conversion and loading software for the process was developed, and clinical data warehouse construction was completed through data verification. Practical Implications: In this study, a clinical data warehouse for Dankook university hospitals based on a common data model supporting drug surveillance research was established and verified. The results of this study provide guidelines for institutions that want to build a clinical data warehouse in the future by deriving key points necessary for building a clinical data warehouse.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.273-276
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• 2023

This paper presents the integration of Digital twin and Blockchain-based Supply Chain Management (DB-SCM) in a smart warehouse to create a more efficient, secure, and transparent facility. The process involves creating a digital twin of the warehouse using sensors and IoT devices and then integrating it with a blockchain-based supply chain management system to connect all stakeholders. All data are collected and tracked in real-time as goods move through the warehouse, and smart contracts are automatically executed to ensure accountability for all parties involved. The study also highlights the critical role of effective supply chain management in modern business operations and the significance of smart warehouses, which leverage advanced technologies such as robotics, AI, and data analytics to optimize warehouse operations. Later, we discuss the importance of digital twins, which allow for creating a virtual representation of a physical object or system, and their potential to revolutionize a wide range of industries. Therefore, DB-SCM offers numerous benefits, including enhanced efficiency, improved customer satisfaction, and increased sustainability, and provides a valuable case study for organizations seeking to optimize their supply chain operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.101-104
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• 2004

Business Intelligence 나 DSS 구축과 운영을 위한 근간은 기업의 통합 데이터 인프라로서의 Data Warehouse 구축이 중심을 이룬다. Data Warehouse 는 통합적, 시계열적, 비휘발적, 주제중심적 Data로 구성된다. 이러한 특성이 이론적으로 정교함에도 불구하고 현실적인 프로젝트를 진행함에 있어서 많은 어려움을 발생시킨다. 이러한 문제의 가장 핵심적인 원인이라면 운영시스템의 변화에 따른 운영상의 리스크와 함께 Subject Area 의 요소적 변경에서 그 원인을 찾을 수 있다. 초기에 Data Warehouse 가 아무리 Business User 의 요구사항을 제대로 충족시킬 수 있다 하더라도 시간의 경과에 따라 운영시스템의 변화와 Subject Area 의 요소적 변경은 피할 수 없는 사실인데 이러한 환경에 유연하게 대처할 수 있는 Data Warehouse 가 구축되지 못한다면 결국 Data Warehouse 프로젝트는 현업의 Business 적 문제와는 거리가 먼 고비용을 투자하고 아무런 수익적 가치도 내지 못하는 거추장스러운 시스템에 지나지 않을 것이다. 본 논문에서는 Dimension 관리의 핵심이라고 할 수 있는Changing Dimension 관리 기법과 함께 EDW(Enterprise Data Warehouse)방식의 아키텍처를 중심으로 한 통합데이터모델과 함께 OLAP 메타데이터에 기반한 복합적이면서도 현실적인 Data Warehouse 설계를 제시하고자 한다

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.448-474
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• 1998

Data warehouse (DW) is important for analytical processing. Metadata is a key to its architecture. This paper proposes an architecture that consists of seven components. To illustrate data warehouse environment (DWE), this Paper proposes taxonomies having four flows. on the basis or the taxonomies and metadata, this paper proposes a methodology for building the data warehouse and metadata simultaneously. This integrated development methodology (IDM) consists of seven phases: (i) preparatory phase, (ii) requirement analysis phase, (iii) data warehouse development phase, (iv) operational data store development phase, (v) data mart development phase, (vi) metastore development phase, and (vii) maintenance phase. A metastore system is Proposed to help develop metadata interactively. An illustrative example is investigated to demonstrate the usefulness of IDM.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.98-99
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• 2021

The number of fires in the Korean distribution warehouse increased by about 350 from 1,070 in 2014 to 1,416 in 2020. In addition, the fire load increases with the scale of the distribution warehouse, and even if the automatic sprinkler operates, there is a limit to the direct intrusion of the water source into the ignition source, and the detector is often installed on a high ceiling. The sensing time is often delayed. In order to improve the fire safety of such distribution warehouses, the US NFPA stipulates in detail the contents related to the facility, such as sprinkler water discharge standards, rack-type warehouse installation height restrictions, and regulations on collection and equipment. However, in Japan, the goods loaded inside the distribution warehouse are not classified in detail, and it is considered that the fire safety for the distribution warehouse is low due to the relaxation regulations of the fire prevention section. Therefore, in this study, common problems are classified into material, spatial, and safety management characteristics through the cases of distribution warehouse fires that occurred in Korea and abroad, and the problems related to distribution warehouses in Korea and abroad are compared and analyzed. And present basic materials for improving the life safety standards of future distribution warehouse facilities.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.20-27
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• 1999

This study presents an Automated Warehouse Management System (AWMS) using a bar-code system The AWMS has been designed to be associated with an Integrated Production Management System (IPMS), which basically includes the following four modules i.e the sales management, production management, material management, and data management. Now, whenever storage or retrieval of the material occurs in the warehouse, the events could be processed quickly and accurately only through reading the 13 digit bar-code including 5 digit position code and simply typing in the number of material. Consequently, the AWMS associated with IPMS could automatically coincide the item counts on document with those in the warehouse. Also, this makes it possible to identify the material quantities in real time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.254-257
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• 1996

Executive information system (EIS) is a computer-based information system that supports decision makings and management activities for senior executives. Data warehouse is a database that receives data copies from legacy systems and external data sources. Data warehouse is typically optimized for decision supports and can be an attractive solution for EIS implementation. This paper proposes an architecture for implementing EIS by the use of data warehouse. The architecture consists of ten implementation layers. Interrelationships among these layers are investigated for an effective EIS implementation. An EIS prototype for a real-life enterprise is implemented to demonstrate the usefulness of the proposed architecture.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.507-514
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• 2006

Various application systems are developed using RFID as a part of ubiquitous computing, and it is expected that RFID chip will become wide-spread for the distribution industry especially. Efficient and efact intelligent-type of warehouse management system is essential for small-to-medium-sized enterprises in the situation having a trouble in the viewpoint of expense and manpower. In this paper, we implement small-scale warehouse management system using log-based context awareness technology. This system is implemented to be controlled on web, configuring clients to control RFID readers and building up DBMS system in a server. Especially, it grasps user's intention of storing or delivering based on toE data for the history of user's access to the system and it reports user's irregular pattern of warehouse use and serves predictive information of the control of goods in stock. As a result, the proposed system can contribute to enhance efficiency and correctness of small-scale warehouse management.