• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.4
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• pp.319-344
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• 2018

As a part of the open science policy, this study compared the perception of research data sharing and utilization by academic field. Based on this, in - depth interviews were conducted with semistructured questions to the data task managers of 27 government - funded research institutes in science and technology. Among them, nine excellent organizations were selected from the viewpoint of data management and cases of research data collection and management were specifically presented. The State of the collection and management of research data by the participating research institutes is generally a pilot project stage, and the level of collection and establishment of data also differs by institution. In terms of institutions, they are divided into three levels: the level of collection and establishment of data(KIOM), the advanced level of it (KIST), And level of steps to start sharing (KRIBB, KRICT).

• Journal of Digital Contents Society
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• v.6 no.1
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• pp.1-5
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• 2005

This paper describes the main characteristics of Grid Services based on OGSA and a Grid service for aggregating service data element(SDE)s. In order to build a Grid Service, it needs to consider a systematic building approach from the high-level software architecture that represents the main system components and their interactions. The purpose of this paper is to design and implement an extended service data aggregator service in which SDE is a basic unit for collecting resource information. A GT3 based service data aggregator service is extended to apply the multiple collections based storage scheme for maintaining persistently SDEs with a XML DBMS Xindice. To provide efficient aggregating service for service data elements, which is running under wide area environment like Internet, the aggregator service is asynchronously operated by notification mechanism.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.515-519
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• 2009

As the application fields of sensor nodes are getting diverse these days, it is required to have a way of collecting various data that is suitable for these application fields. In the case that the real-time surveillance over the data is unnecessary, present data collecting methods, which collect and transfer the data directly, can cause a waste of energy and data loss, A new method that store the collected data in a local storage and acquire them by query later on is required for nonreal-time applications. NAND flash has energy efficiency and large capacity so it is suitable for sensor nodes, Sensor nodes support 4-10 KBytes small sized memory and it is hard to build an effective file system since NAND Flash doesn't support overwriting NAND flash. This paper discusses an implementation of NAND Flash file system in sensor node environments. The file system makes long-term data collecting possible by reducing transmission cost. It is expected that this file system will play a central role in sensor network environments as it can be applied to various fields which call for long term data collecting.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1567-1574
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• 2017

In this paper, we analyzed the stereotyped and non - stereotyped data in order to analyze the drama 's ratings. The formalized data collection collected 19 items from the four areas of drama information, person information, broadcasting information, and audience rating information of each broadcasting company. Atypical data were collected from bulletin boards, pre - broadcast blogs and post - broadcast blogs operated by each broadcasting company using a crawling technique. As a result of comparing the differences according to the four areas for each broadcaster from the collected regular data, the results were similar to each other. And we derived seven related words by analyzing the correlation of occurrence frequencies from unstructured data collected from bulletin boards and blogs of each broadcasting company. The derived associations were obtained through reliability analysis.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.65-72
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• 2020

Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.300-306
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• 2021

Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.95-101
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• 2023

Globally, the importance of utilization and management of marine spatial information is being maximized, and analyzing such data is emerging as a major driving force for R&D. In Korea, it is expected that collecting marine data from the past to the present and extracting its value will play an important role in the development of science in Korea in the future. In particular, marine static data constitutes a huge big database, and it is necessary to store and store the collected data without loss as high data collection costs and high-level observation techniques are required. In addition, the Disaster Safety Intelligence Convergence Center's "Marine Digital Twin Establishment and Utilization-Based Technology Research" task requires collection and analysis of marine data, so this paper conducts a current status survey of static marine data. And we present a series of algorithms that collect and store them in a database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.422-424
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• 2018

Recently there has been growing interest in big data analysis and methods for collecting data have been developed diversely but researchers are still not easy to collect and use these large scale data. In this paper, researchers try to compare and analyze the method of collecting big data by using several methods and present it. I hope that you can provide the results of your research if you select and use methods that match your research objectives.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.597-598
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• 2009

최근의 국가 민간의 정보시스템을 위협하는 공격들은 점점 더 복잡해지고 정교해지고 있다. 이러한 공격들에 대응하기 위하여 범국가적으로 사이버안전센터들이 설립 운영되고 있다. 그러나 이러한 대량의 정보보호 데이터를 수집 분석 대응하는 것은 여러 가지 어려움들이 존재한다. 그 문제의 본질적인 부분은 바로 방대한 데이터의 양(量)이다. 다수의 보안관제 대상 인프라들의 모든 보안데이터를 수집 하는 것은 사실상 불가능하며, 대부분의 센터들은 네트워크 접점에 중앙관리형 보안인프라를 설치함으로써 그 해결점을 찾고 있지만, 이는 최근의 나타나고 있는 다차원적인 공격에 대응하기에는 한계가 있다. 본 논문에서는 이러한 다차원 분석시스템의 기본데이터가 되는 여러 보안정보를 효과적으로 수집할 수 있는 보안정보 수집체계를 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.893-895
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• 2016

Data center has a lot of management efforts for the facility, energy, and efficient usage monitoring. Data center power management is important to make the data center have reliable service and cost-effective business. In this paper, IoT based energy measurements monitoring which gives support to energy consumption analysis including indoor, outdoor temperature condition. This converged information for energy analysis gives various aspects of energy consumption effects. With IoT big data, energy machine learning system can give the relation of energy components and measurements, it is the key information of the quick energy analysis in the just one month data trend for the prediction and estimation.