• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.168-170
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• 2003

In this paper, we discuss the concept of Spatio-Temporal Data Warehouse and analyze the organization model of spatio-temporal data. Based on the above, we found the framework of Spatio-Temporal Data Warehouse composed of data source, processing tools and application, which covers the whole process from building warehouse to supplying services.

• 한국병원경영학회지
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• 제28권3호
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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.

• Asia pacific journal of information systems
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• 제10권3호
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• pp.79-103
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• 2000

Data warehouse is an intelligent store of data. A metadata is critical for implementing data warehouse. Integrating data warehouse with its metadata helps create a more adaptive information system. This paper proposes a metadata-oriented data warehouse architecture that consists of seven components: legacy, extracting, operational data store, data warehouse, data mart, application, and metadata. A taxonomy for dataflow and metaflow is proposed for better understanding of the architecture. In addition, a metadata schema is built within the framework of the seven components. Lastly, the architecture with its metadata component is applied to a real-life data warehouse project for a large medical center in order to illustrate its practical usefulness.

• 한국컴퓨터정보학회논문지
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• 제23권3호
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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.

• 한국건설관리학회논문집
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• 제5권3호
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• pp.166-173
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• 2004

본 연구에서는 건설 관리자의 전자적 의사결정 지원을 위한 활용도구인 건설 데이터 웨어하우스의 시스템 프로토타입 개발에 대한 기초연구를 수행하였다. 건설 데이터 웨어하우스는 건설회사 내에서 별도 저장된 데이터에 접근하여 관리의 차원, 각 주제영역, 그리고 기술모듈별로 분석함으로써 전자적 정보를 제공하는 기술인 바, 이 기술의 건설산업 활용을 위하여 본 연구에서는 데이터 웨어하우스 기술의 기술적 특성을 검토하여 요소기술모듈과 사용주체에 대한 설정을 통한 건설 데이터 웨어하우스 시스템 프로토타입을 도출한다. 이러한 연구의 결과로서, 건설데이터 웨어하우스 시스템 프로토타입과 각 기술 모듈을 제시하고 이의 활용성을 사례연구를 통하여 검증함으로써 데이터 웨어하우스 기술의 건설산업 활용가능성을 확인하였다.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 추계학술발표대회 논문집
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• pp.337-340
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• 2008

As a 'Construction of Information System on GIS based and Resource Map', establish the strategic of design about construction of Spatial Data Warehouse for New & Renewable Energy For Construction of comfortable Spatial Data Warehouse, It suggested The Construction of Spatial Data Warehouse on Block(Grid) Based with Analyze into the old Data & Method of Study. For Decide the Block(Grid) Size, We need The Study of Data & Method. Also, we expect Standardize The Process of Change & Apply with Data. make the best use of New & Renewable Energy Part

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.403-413
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• 1999

Today's businesses are experiencing intensive global competition and the most accelerating pace of change ever. Competitors have sprung up that were not even on the business's radar. This environment impacts all decisions and strategies as business try to dominate their market or their industry merely to survive. So recently most of organizations are considering on building the data warehouse system to pursuit the business intelligence. We need the proper model to guide the approach to plan building data warehouse system when we want to plan it in considering the organizational status. Therefore we suggest a model to decide the approach to build data warehouse considering the project's environmental factors. First we review Ronald S. Swift(1998)'s five environmental factors that we have to consider when planing to build data warehouse. Then we propose a model to decide DW approach by the degree of those factors to be measured. DW approaches in this model are classified in conservative approach, technological approach, increasing approach. enterprise- wide approach, and ideal approach.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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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

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.403-413
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• 1999

Today's businesses are experiencing intensive global competition and the most accelerating pace of change ever. Competitors have sprung up that were not even on the business's radar. This environment impacts all decisions and strategies as business try to dominate their market or their marker or their industry merely to survive. So recently most of organizations are considering on building the data warehouse system to pursuit the business intelligence. We need the proper model to guide the approach to plan building data warehouse system when we want to plan it in considering the organizational status. Therefore we suggest a model to decide the approach to build data warehouse considering the project's environmental factors. First we review Ronald S. Swift(1998)'s five environmental factors that we have to consider when planing to build data warehouse. Then we propose a model to decide DW approach by the degree of those factors to be measured. DW approaches in this model are classified in conservative approach, increasing approach, enterprise wide approach, and ideal approach.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 국제컨퍼런스 디지털컨텐츠 활용을 통한 지식경영의 확산
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• pp.113-118
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• 1999

본 연구는 통합병원정보시스템 (Integrated Hospital Information System) 에서 의료용 데이터 웨어하우스 (Medical Data Warehouse) 부분의 보안 프로토타입 시스템을 메타데이터 기반으로 설계하고 구현하는 데 주안점을 두었다. 특히, 의료용 데이터 웨어하우스 중에서도 임상 데이터 웨어하우스 (Clinical Data Warehouse) 에 초점을 두었으며 이에 대한 프로토타입은 ㅈ 병원에 적용되어서 개발되었다.