• ETRI Journal
• /
• 제44권5호
• /
• pp.780-793
• /
• 2022

Large-scale ontology management is one of the main issues when using ontology data practically. Although many approaches have been proposed in relational database management systems (RDBMSs) or object-oriented DBMSs (OODBMSs) to develop large-scale ontology management systems, they have several limitations because ontology data structures are intrinsically different from traditional data structures in RDBMSs or OODBMSs. In addition, users have difficulty using ontology data because many terminologies (ontology nodes) in large-scale ontology data match with a given string keyword. Therefore, in this study, we propose a (graph database-based ontology management system (GOMS) to efficiently manage large-scale ontology data. GOMS uses a graph DBMS and provides new query templates to help users find key concepts or instances. Furthermore, to run queries with multiple joins and path conditions efficiently, we propose GOMS encoding as a filtering tool and develop hash-based join processing algorithms in the graph DBMS. Finally, we experimentally show that GOMS can process various types of queries efficiently.

• 한국컴퓨터정보학회논문지
• /
• 제22권11호
• /
• pp.57-63
• /
• 2017

The recent sudden increase of big data has characteristics such as continuous generation of data, large amount, and unstructured format. The existing relational database technologies are inadequate to handle such big data due to the limited processing speed and the significant storage expansion cost. Thus, big data processing technologies, which are normally based on distributed file systems, distributed database management, and parallel processing technologies, have arisen as a core technology to implement big data repositories. In this paper, we propose a design methodology for large-scale database based on MongoDB by extending the information engineering methodology based on E-R data model.

• 한국전자통신학회논문지
• /
• 제7권5호
• /
• pp.1095-1101
• /
• 2012

최근 데이터 양이 폭발적으로 증가함에 따라, 데이터를 저장하고 검색하고 다루기 위한 대규모 데이터베이스 시스템이 등장하였다. 이 환경에서는 일관성과 가용성, 결함 허용 등 다양한 이슈가 존재한다. 이 논문에서는 데이터 관리와 트랜잭션 관리가 분리된 구조를 갖는 대규모 데이터베이스 시스템에서, 효율적인 범위 질의 방법에 대하여 다룬다. 동일한 구조에서 두 모듈의 독립성을 보장하고, 팬텀 문제를 해결하기 위하여 파티션을 이용한 범위 질의 방법에 대한 연구가 있었지만, 범위 질의가 키 값으로 명세되는 경우에만 효율적이었다. 이에 이 논문에서는 키 값이 아닌 다른 속성으로 범위 질의가 주어질 때 효율을 개선할 수 있는 방법을 제안하고자 한다. 제안하는 방법에서는 분리된 두 모듈의 독립성은 보장하며, 부분 인덱스를 사용함으로써 범위 질의를 위한 오버헤드를 줄일 수 있다.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
• /
• pp.1079-1084
• /
• 2002

Systems engineering technology development program for Korea next-generation high-speed railway(KNHR) system in progress is a national large-scale system development program that is not only a large-size and complex but also multi-disciplinary in nature. Using the RDD-IOO, a systems engineering tool, the KNHR program can establish requirements traceability and development process management in the course of development. This paper presents the results from a computer-aided systems engineering application to KNHR system technology development project over the three years of activities. The traceability among the system design database in the vertical direction of SE process, as the results of the first year and the second year research was accomplished. The database in both the requirement management domain and the project management domain was developed and set up the traceability between them in the horizontal direction of the SE process in the V model as the results of the third year research. Therefore, KNHR design database was built to support the life-cycle management of the system as well as to reuse the knowledge in future programs. In the following development phase, this database will be utilized to accomplish the test and integration activities providing a baseline database. The outcome of the study contributes to the establishment of the model-based systems engineering approach as a best practice in the accumulation and advancement of systems engineering technology for railway system development.

• Journal of Information Processing Systems
• /
• 제18권3호
• /
• pp.374-388
• /
• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• 국제학술발표논문집
• /
• The 5th International Conference on Construction Engineering and Project Management
• /
• pp.648-651
• /
• 2013

The information generated in large-scale and complex construction projects are transferred continuously and transformed into project products on the long span life cycle. Therefore, information flow management is related with the success of project directly. However, certain characteristics of large-scale and complex construction projects make the solving the problem more difficultly. Although several information retrieval systems support the information management system, it is not suitable to grasp information flows. Hence, we developed an information retrieval system specialized with the information flow based on a preceding research. The system consists of a relation-based database and the process information transferring relation inference application module. The system enables project managers to manage the entire project process more efficiently and each project member to work their own task being served the information flow retrieval results.

• 산업경영시스템학회지
• /
• 제25권4호
• /
• pp.22-31
• /
• 2002

A high-speed rail system represents a typical example of large-scale multi-disciplinary systems, consisting of subsystems such as train, electrical hardware, electronics, control, information, communication, civil technology etc. The system design and acquisition data of the large-scale system must be the subject under strict configuration control and management. Not only the requirements of the large-scale system dictate the contracts with the suppliers but also become the basis for the development process, project execution, system integration, and testing. The requirements database provide the system design specification of all development activities. Using the RDD-100, a systems engineering tool, the Korea next-generation high-speed rail program can establish requirements traceability and development process management in performing the enabling train technology development projects. This paper presents the results from a computer-aided systems engineering application to the Korea next-generation high-speed railway project. Especially, the focus of the study was on requirement management and PBS(Product Breakdown Structure) management.

• International Journal of Computer Science & Network Security
• /
• 제21권12호
• /
• pp.280-292
• /
• 2021

Enterprise Resource Planning (ERP) is a software that manages and automate the internal processes of an organization. Process speed and quality can be increased, and cost reduced by process automation. Odoo is an open source ERP platform including more than 15000 apps. ERP systems such as Odoo are all-in-one management systems. Odoo can be suitable for small and medium organizations, but duo to efficiency limitations, Odoo is not suitable for the large ones. Furthermore, Odoo can be implemented on both local or public servers in which each has some advantages and disadvantages such as; the speed of internet, synced data or anywhere access. In many cases, there is a persistent need to have more than one synchronized Odoo instance in several physical places. We modified Odoo to support this kind of requirements and improve its efficiency by replacing its standard database with a distributed one, namely CockroachDB.

• 국제학술발표논문집
• /
• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
• /
• pp.556-560
• /
• 2011

Players of construction projects proceed with each work process by information gathering, modification and communication. Due to the complex and long-span lifecycle projects increased, it became more important to grasp this mechanism for the successful project performance in construction project. Hence, most project information management systems or knowledge management systems equip information retrieval system. There are two logic to infer the meaning of retrieval target; inductive reasoning and deductive reasoning. The former is based on metadata explaining the target and the later is based on relation between data. To infer the information flow, it is necessary to define the correlation between players and work processes. However, most established information retrieval systems are based on index search system and it is not focused on correlation between data but data itself. Thus, this research aims to research on process of information flow retrieval system for large-scale construction projects.

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
• /
• pp.15-20
• /
• 2005

We developed a database system to enable efficient and high-throughput transposon analyses in rice. We grow large-scale mutant series of rice by taking advantage of an active MITE transposon mPing, and apply the transposon display method to them to study correlation between genotypes and phenotypes. But the analytical phase, in which we find mutation spots from waveform data called fragment profiles, involves several problems from a viewpoint of labor amount, data management, and reliability of the result. As a solution, our database system manages all the analytical data throughout the experiments, and provides several functions and well designed web interfaces to perform overall analyses reliably and efficiently.