• 정보관리연구
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• 제33권1호
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• pp.61-80
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• 2002

본 연구는 과학기술분야 해외 온라인 데이터베이스의 현황을 평가하고 조사한 것이다. 데이터베이스에 대한 평가는 과학기술정보 이용자나 정보 제공자에게 매우 중요한 과제로 인식되고 있다. 본 연구에서는 우선적으로 데이터베이스 평가에 대한 선행 연구를 간략하게 요약하였다. 그리고 현재 이용 가능한 해외 온라인 데이터베이스 618종을 대상으로 주제분야별, 발행처별, 갱신주기별, 온라인 이용방법별로 분석하였다. 또한 과학기술분야별로 주요한 온라인 데이터베이스를 간략하게 소개하였다.

• 정보관리연구
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• 제36권2호
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• pp.153-172
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• 2005

현재 저작권과 온라인 디지털 콘텐츠 산업발전법은 데이터베이스와 디지털 콘텐츠 제작자를 보호대상으로 하고 있다. 미국 데이터베이스 보고서의 추가 보호론에 데이터베이스는 경제 및 과학에 있어 그 중요성을 더해 가고 있으며, 인터넷 상의 핵심적 요소가 되어가고 있다. 그러므로 우리나라의 공공 민간 모두 데이터베이스의 법적 보호에 신중을 기해야 한다. 본 고에서는 과학기술 데이터베이스 법적 보호의 전반적인 문제점들과 현행법에 의한 과학기술 데이터베이스 보호의 핵심적인 내용과 추가적인 보호 문제를 깊이있게 다루었다. 과학기술 데이터베이스 산업의 발전이 국가의 경쟁력 확보에 중대한 몫을 차지하고 있다는 점을 고려할 때, 데이터베이스의 법적보호방안 마련은 데이터베이스의 지속적인 발전을 도모하기 위한 정책의 하나로서, 간과되어서는 안 될 중요한 사안 중의 하나이다.

• Genomics & Informatics
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• 제6권2호
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• pp.95-97
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• 2008

Many bioinformatics sites have managed local bio-databases, including major databases such as GenBank and PIR with update load. We have developed several programs to monitor the update status of these databases and to FTP them automatically. These programs can be used for maintaining local bio-databases as recent versions and providing up-to-date databases through FTP sites. Currently, the program serves major bio-databases and will extend to accommodate many more bio-databases.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.693-694
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• 2008

It is of importance to integrate several databases to improve its coverage and usage of large amount of biological information produced by diverse biological experiments. In this paper, we proposed a method to integrate the protein interaction databases with various naming schemes. The identifier (ID) mapping methods in the process of integration was also presented.

• Journal of Computing Science and Engineering
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• 제3권4호
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• pp.260-277
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• 2009

In this paper we propose a model for checking integrity constraints of mobile databases called Three-Level (3-L) model, wherein the process of constraint checking to maintain the consistent state of mobile databases is realized at three different levels. Sufficient and complete tests proposed in the previous works together with the idea of caching relevant data items for checking the integrity constraints are adopted. This has improved the checking mechanism by preventing delays during the process of checking constraints and performing the update. Also, the 3-L model reduces the amount of data accessed given that much of the tasks are performed at the mobile host, and hence speeds up the checking process.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권12호
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• pp.1418-1427
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• 1999

시간지원 데이타베이스 시스템은 자료의 과거 및 현재, 그리고 미래의 상태까지 관리함으로써, 사용자에게 시간에 따라 변화하는 자료에 대한 저장 및 질의 수단을 제공한다. 시간지원 데이타베이스는 경향 분석, 버전 관리, 의료 기록 관리 및 비디오 데이타 관리 등과 같이 자료의 시간적 특성이 중요시 되는 모든 분야에 폭 넓게 응용될 수 있다. 시간지원 데이타베이스에서의 집계는 시간 애트리뷰트를 고려하지 않은 기존의 집계와는 큰 차이가 있으며, 기존의 집계 처리 기법을 이용하여 효과적으로 처리될 수 없다. 본 논문에서는 시간지원 집계를 효율적으로 처리하기 위한 새로운 자료 구조인 PA-트리를 제안하고, 이를 이용한 시간지원 집계 처리 기법을 제안한다. 또한 본 논문에서는 제안된 PA-트리를 이용한 기법과 기존의 집계 트리를 이용한 기법의 성능을 최악 경우 분석과 실험을 통해 비교한다.Abstract Temporal databases manage time-evolving data. They provide built-in supports for efficient recording and querying of temporal data. Many application area such as trend analysis, version management, and medical record management have temporal aspects, and temporal databases can handle these temporal aspects efficiently. The aggregate in temporal databases, that is, temporal aggregate is an extension of conventional aggregate on the domain and range of aggregation to include time concept. The basic techniques behind computing aggregates in conventional databases are not efficient when applied to temporal databases. In this paper, we propose a new tree structure for temporal aggregation, called PA-tree, and aggregate processing method based on the PA-tree. We compare the PA-tree with the existing aggregation tree which has been proposed for temporal aggregate.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• Genomics & Informatics
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• 제7권1호
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• pp.49-51
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• 2009

Although abundant biology data have been accumulated in public biology databases, such as GenBank and PIR, few easy-interface services are provided for users to access or update them. We have developed a system, named BioStore, that is composed of several programs to aid users to not only access public data but also share their own data easily. The service can be used for maintaining a local database as a repository of raw data files of several public databases and distributing the data files to other users. Currently, BioStore manipulates major bio-databases and will expand to include more databases and more useful interfaces.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• Journal of Computing Science and Engineering
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• 제1권1호
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• pp.1-30
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• 2007

In this paper we have provided an extensive survey of the databases and other resources related to the current research in bioinformatics and the issues that confront the database researcher in helping the biologists. Initially we give an overview of the concepts and principles that are fundamental in understanding the basis of the data that has been captured in these databases. We briefly trace the evolution of biological advances and point out the importance of capturing data about genes, the fundamental building blocks that encode the characteristics of life and proteins that are the essential ingredients for sustaining life. The study of genes and proteins is becoming extremely important and is being known as genomics and proteomics, respectively. Whereas there are numerous databases related to various subfields of biology, we have maintained a focus on genomic and proteomic databases which are the crucial stepping stones for other fields and are expected to play an important role in the future applications of biology and medicine. A detailed listing of these databases with information about their sizes, formats and current status is presented. Related databases like molecular pathways and interconnection network databases are mentioned, but their full coverage would be beyond the scope of a single paper. We comment on the peculiar nature of the data in biology that presents special problems in organizing and accessing these databases. We also discuss the capabilities needed for database development and information management in the bioinformatics arena with particular attention to ontology development. Two research case studies based on our own research are summarized dealing with the development of a new genome database called Mitomap and the creation of a framework for discovery of relationships among genes from the biomedical literature. The paper concludes with an overview of the applications that will be driven from these databases in medicine and healthcare. A glossary of important terms is provided at the end of the paper.