• Digital Contents
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• no.10 s.65
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• pp.84-88
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• 1998

이 코너는 수많은 데이테베이스 가운데 가장 유용하게 사용되고 있는 DB를 주제별로 정리함으로써 업무에 도움을 주고자 마련했다. 정보검색에 경험이 많은 전문 정보검색사에게는 익숙한 DB들이 많겠지만 특정 주제 분야별로 중요하게 다뤄지는 DB들을 정리해 그 차이를 살펴 볼 수 있기를 바란다.

• Digital Contents
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• no.9 s.64
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• pp.76-83
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• 1998

이 코너는 수많은 데이터베이스 가운데 가장 유용하게 사용되고 있는 100개의 DB를 주제별로 정리함으로써 업무에 도움을 주고자 마련했다. 정보검색에 경험이 많은 전문 정보검색사에게는 익숙한 DB들이 많겠지만 특정 주제 분야별로 중요하게 다뤄지는 DB들을 정리해 그 차이를 살펴 볼 수 있기를 바란다.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.87-96
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• 2004

When watershed spatial database is constructed from DEM, hydrological geographic characteristics of watershed can be easily extracted. And the characteristics can be assigned and managed as the attribute of spatial database. In this study the scheme of constructing framework spatial database which is basic information for managing watershed information is examined. We established framework spatial data and defined the relationship of the data. And framework spatial database of test site was constructed. In this study, HyGIS(Hydrological Geographic Information System) which is developed by domestic technology for making hydrological spatial data and developing water resources system is used. Hydrological geographic characteristics and spatial data is extracted by HyGIS. And the data from HyGIS is used for constructing framework spatial database of test site. Finally, this study suggests the strategy of constructing framework spatial database for developing watershed management system based on river network.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.676-693
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• 2016

Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.

• Digital Contents
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• no.7 s.62
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• pp.44-46
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• 1998

한국데이터베이스진흥센터는 조선일보와 공동으로 지난달 23일 한국종합전시장 회의실에서 제6회 데이터베이스 산업 활성화를 위한 세미나를 정보통신부의 주관아래 개최했다. 매일경제신문사, 한국경제신문사, 한국정보문화센터 등이 후원한 이번 세미나에서는 DB산업의 특성과 육성방향(이두명 중앙대학교 교수), DB업계의 문제와 대응전략(진영돈 한국DB산업협동조합 이사장), 정보통신부의 DB산업 육성 정책(김 호 정보통신부 정보통신진흥과장), 주요 선진국의 DB육성 정책(정현수 한국전자통신연구원 실장), DB산업 발전을 위한 공공기관의 역할(강홍렬 정보통신정책연구원 연구위원)등의 주제발표가 있었다. 발표된 내용을 간략히 소개한다.

• Spatial Information Research
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• v.20 no.1
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• pp.59-69
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• 2012

For the USN(Ubiquitous Sensor Network) environment which generally uses spatial sensor data as well as aspatial sensor data, a sensor database system to manage these sensor data is essential. In this reason, some sensor database systems such as TinyDB, Cougar are being developed by many researchers. However, since most of them do not support spatial data types and spatial operators to manage spatial sensor data, they have difficulty in processing spatial sensor data. Therefore, this paper developed a spatial sensor database system by extending TinyDB. Especially, the system supports spatial data types and spatial operators to TinyDB in order to manage spatial sensor data efficiently and provides the memory management function and the filtering function to reduce the system overload caused by sensor data streams. Lastly, we compared the processing time, accuracy, and memory usage of the spatial sensor database system with those of TinyDB and proved its superiority through the performance evaluation.

• Digital Contents
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• no.10 s.5
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• pp.34-37
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• 1993

• Digital Contents
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• no.10 s.5
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• pp.38-46
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• 1993

• Digital Contents
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• no.11 s.6
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• pp.45-48
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• 1993

• Digital Contents
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• no.9 s.4
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• pp.53-58
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• 1993