• Journal of Information Technology Services
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• v.4 no.2
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• pp.61-69
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• 2005

RFID is used for tracking systems in various business fields these days and these systems brought considerable efficiencies and cost savings to companies. Real-time based information acquired through RFID devices could be a valuable source of information for making decisions if it is combined with decision support tools like OLAP of a data warehouse that has originally been designed for analyzing static and historical data. As an effort of extending the data source of a data warehouse, RFID is combined with a data warehouse in this research. And OLAP is designed to analyze the dynamic real-time based information gathered through RFID devices. The implemented prototype shows that ubiquitous computing technology such as RFID could be a valuable data source for a data warehouse and is very useful for making decisions when it is combined with online analysis. The system architecture of such system is suggested.

• 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 Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.72-79
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• 2007

OMG's Common Warehouse Metamodel is now a single data warehouse metadata standard. Interchange of metadata between data warehousing tools and metadata repositories made easy and convenient by using CWM. In this paper, we present the origin, importance and architecture of CWM, and offer an application case.

• The Journal of Fisheries Business Administration
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• v.31 no.2
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• pp.119-132
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• 2000

One of most important wort to build Fisheries Policy Information Systems(FPIS) is related to connect the data warehouse between fisheries departments, This paper presents the developing strategies to build the FPIS. First, developing the FPIS needs to compensate the laws and regulations with assistance of fisheries departments. Second, FPIS developer needs to cooperate the related fisheries departments deeply, Third, developing the data warehouse will be contribute to improve criterion and statistics of fisheries data. Forth, For experts of systems use the FPIS, they are needed to educate for appling the systems in the fisheries environments.

• International Commerce and Information Review
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• v.7 no.1
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• pp.55-74
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• 2005

Recently, many enterprises have attempted to construct data warehousing systems for decision-support. Data warehouse is an intelligent store of data that can aggregate vast amounts of information. Building DW requires two important development issues:(i) DW for the decision making of business users and (ii) metadata within it. Most DW development methodologies have not considered metadata development; it is necessary to adopt a DW development methodology which develops a DW and its metadata simultaneously. Metadata is a key to success of data warehousing system and is critical for implementing DW. That is, metadata is crucial documentation for a data warehousing system where users should be empowered to meet their own information needs; users need to know what data exists, what it represents, where it is located, and how to access it. Furthermore, metadata is used for extracting data and managing DW. However, metadata has failed because its management has been segregated from the DW development process. Metadata must be integrated with data warehousing systems. Without metadata, the decision support of DW is under the control of technical users. Therefore, integrating data warehouse with its metadata offers a new opportunity to create a more adaptive information system. Therefore, this paper proposes a DW development methodology from a metadata perspective. The proposed methodology consists of five phases: preparatory, requirement analysis, data warehouse (informational database) development, metastore development, and maintenance. To demonstrate the practical usefulness of the methodology, one case is illustrated

• IE interfaces
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• v.15 no.2
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• pp.159-171
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• 2002

Data Warehouses integrate data from multiple heterogeneous information sources and transform them into a multidimensional representation for decision support applications. Data warehousing has emerged as one of the most powerful tools in delivering information to users. Most previous researches have focused on marketing, customer service, financing, and insurance industry. Further, relatively less research has been done on data warehouse systems in the complex manufacturing industry such as ship production, which is characterized complex product structures and production processes. In the ship production, data warehouse systems is a requisite for effective cost analysis because collecting and analysis of diverse and large of cost-related(material/production cost, productivity) data in its operational systems, was becoming increasingly cumbersome and time consuming. This paper proposes architecture of the data warehouse systems to support cost analysis in the ship production. Also, in order to illustrate the usefulness of the proposed architecture, the prototype system is designed and implemented with the object of the enterprise of producing a large-scale ship.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.57-62
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• 2004

In these days, application systems for processing information using database is increasing. Enterprises holding a lot of data do not possess needed data but instead include unrelated, independent and individual data. As a result, it only contains disparate data. Disparate data is ambiguous and it does not support current integrated information. In response to the above problems, data warehouse may provide a solution. Building a data warehouse needs a systematic design because of its complexity. This paper describes an efficient design methodology using visual environment for data warehouse to cope with the requirements of end users. Also, the system is able to process existential SQL query.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.119-130
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• 2005

A spatial data warehouse is a system that stores geographical information as a subject oriented, integrated, time-variant, non-volatile collection for efficiently supporting decision. This system consists of a builder and a spatial data warehouse server. A spatial data warehouse server suspends user services, stores transferred data in the data repository and constructs index using stored data for short response time. Existing methods that construct index are bulk-insertion and index transfer methods. The Bulk-insertion method has high clustering cost for constructing index and searching cost. The Index transfer method has improper for the index reconstruction method of a spatial data warehouse where periodic source data are inserted. In this paper, the efficient index reconstruction method using a partial index in a spatial data warehouse is proposed. This method is an efficient reconstruction method that transfers a partial index and stores a partial index with expecting physical location. This method clusters a spatial data making it suitable to construct index and change treated clusters to a partial index and transfers pages that store a partial index. A spatial data warehouse server reserves sequent physical space of a disk and stores a partial index in the reserved space. Through inserting a partial index into constructed index in a spatial data warehouse server, searching, splitting, remodifing costs are reduced to the minimum.

• Asia pacific journal of information systems
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• v.7 no.1
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• pp.7-24
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• 1997

Executive information system (EIS) is a computer-based information system that supports decision makings ana 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-fife enterprise is implemented to demonstrate the usefulness of the proposed architecture.

• 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.