• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.151-170
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• 2021

The domain name should be registered and used with the minimum length in consideration of the user's web accessibility and convenience. In addition, it is necessary to increase the status and authority of the library by allowing the type, region, and characteristics of the library to be known only by the domain name, and to consider the convenience of users. In this study, the situation of the state designated second-stage public domain and the second-stage public domain of educational institutions of similar character and size to the library are analyzed, and problems with the domain of libraries that do not have the second-stage domain are identified. Finally, second-stage public domains of national library (nl), public library (pl), and small library (sl) are proposed for each type of library, and the university library (lib. university domain) and school library (lib. School domain) proposed to use as the second-stage domains of the educational institution. The purpose is to allow users to intuitively know that these domains are libraries, to identify the type of library, and to know the characteristics and regions of the library. To this end, a joint effort by the academic community, the library community, and the Library Information Policy Committee is needed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.79-80
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• 2023

정부는 공공데이터의 품질 관리를 위하여 공공데이터 품질관리 수준평가를 진행하여 공공데이터 품질을 관리하고 있다. 파일 형식의 공공데이터를 진단 시 품질진단 담당자가 대량의 파일데이터를 필드명과 필드 내 데이터에 의존하여 수작업으로 도메인을 판단하여 진단한다. 때문에 품질진단의 정확성을 신뢰하기 어렵고 진단에 많은 시간이 소요된다. 본 논문은 파일형식의 공공데이터 품질진단의 정확성을 확보하고 진단 소요시간을 단축하기 위해 데이터 분포 통계를 이용한 CSV 형식의 공공데이터 도메인 판별 모델을 제안하였다. 제안된 모델을 적용하면 공공데이터 품질의 정확성을 향상하고 진단 소비 시간을 단축시킬 것으로 기대된다.

• Review of KIISC
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• v.30 no.4
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• pp.77-89
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• 2020

이 연구는 우리나라 정부의 공공데이터 공개 제도에 따른 공공데이터 품질관리체계를 이해하고, 공공기관이 신뢰성 있는 데이터를 위해 품질 점검을 시행하면서도 효과적인 관리를 하기 위한 방안에 관한 것이다. 공공데이터법과 공공데이터 품질관리체계를 이해하고, 저품질 공공데이터의 오류와 발생원인에 대해 알아본다. 오류 데이터 분석을 통한 보안위협에 따른 위험 분류를 통해 효과적인 대응방안을 도출하는 것을 목표로 한다. 이를 위해 공공데이터를 데이터 품질 점검하여 도메인별 오류데이터를 살펴보고, 오류데이터 발생원인에 대한 분석을 통해 보안위협과 공공데이터를 사용하는 사용자 측면과 기관 측면의 보안 문제를 분류하였다. 분류된 오류 발생원인별 보안문제를 기준으로 데이터 품질관리를 통한 개선방향을 제시하고, 품질관리 오류 개선방향별 데이터보안 정책별 보안기술을 비교 정리하여, 데이터 보안기술을 통한 품질관리 오류 개선 연계 대응방안을 제안하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.81-86
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• 2022

In this work, we propose a method for automatically determining the domain of columns of file data structured by csv format. New data can be generated through convergence between data and data, and the consistency of the joined columns must be maintained in order for these new data to become an important resource. One of the methods for measuring data quality is a domain-based quality diagnosis method. Domain is the broadest indicator that defines the nature of each column, so a method of automatically determining it is necessary. Although previous studies mainly studied domain automatic discrimination of relational databases, this study developed a model that can automate domains using the characteristics of file data. In order to specialize in the domain discrimination of file data, the data were simplified and patterned using a regular expression, and the contents of the data header corresponding to the column name were analyzed, and the suffix used was used as a derived variable. When derivatives of regular expressions and suffixes were added, the result of automatically determining the domain with an accuracy of 95% greater than the existing method of 87% was derived. This study is expected to reduce the quality measurement period and number of people by presenting an automation methodology to the quality diagnosis of public data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.259-284
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• 2013

Public information has been collected in various fields with huge costs in order to serve public purposes such as public agencies' policy-making. However, the collected public information has been overlooked as silos. In korea, many attempts have been made to open the public information to the public only to result in limited extent, where OpenAPI data is being presented by some agencies. Recently, at the national level, the LOD(Linking Open Data) project has built the national DB, initiating the ground on which the linked data will be based for their active availability. This study has outlined overall problems in earlier projects which have built up national linking systems based on linked data for public data use. A possible solution has been proposed with a real experience of having set up an existing national DB of Korean public agencies.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.299-308
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• 2006

As recently XML is becoming the standard of exchanging web documents and public documentations, XML data are increasing in many areas. To retrieve the information about XML documents efficiently, the semantic web based on the ontology is appearing. The existing ontology has been constructed manually and it was time and cost consuming. Therefore in this paper, we propose the semi-automatic ontology generation technique using the data mining technique, the association rules. The proposed method solves what type and how many conceptual relationships and determines the ontology domain level for the automatic ontology generation, using the data mining algorithm. Appying the association rules to the XML documents, we intend to find out the conceptual relationships to construct the ontology, finding the frequent patterns of XML tags in the XML documents. Using the conceptual ontology domain level extracted from the data mining, we implemented the semantic web based on the ontology by XML Topic Maps (XTM) and the topic map engine, TM4J.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.189-195
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• 2022

The Korean government has made it a major national task to contribute to the revitalization of the creative economy, such as creating new industries and jobs, by encouraging the private opening and utilization of public data. The Korean government is promoting public data quality improvement through activities such as conducting public data quality management level evaluation for high-quality public data retention. However, there is a difference in diagnosis results depending on the understanding and data expertise of users of the public data quality diagnosis tool. Therefore, it is difficult to ensure the accuracy of the diagnosis results. This paper proposes a public data quality management level evaluation domain rule mapping model applicable to validation diagnosis among the data quality diagnosis standards. This increases the stability and accuracy of public data quality diagnosis.

• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.113-117
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• 2013

팀 버너스 리에 의해 '시멘틱 웹'은 1998년 제안되었으나 현재 새롭게 생성되고 있는 데이터 혹은 자연어 형식의 데이터를 시멘틱 검색을 위해 활용하기에는 아직까지 온톨로지 데이터베이스가 따라가지 못하고 있다. 이를 위해 온톨로지 구축의 구성요소인 공리(axiom)를 공공을 위한 데이터로 개발하여 시멘틱 검색에 활용하는 개념적 모델을 제안한다. 공리 데이터베이스는 단일 도메인에서 벗어난 시멘틱 검색을 위한 데이터베이스로서 도메인 온톨로지 구축에 기본적인 요소들을 제공하고, 이용자들이 시멘틱 검색을 통해 보다 만족한 정보검색을 할 수 있도록 한다. 또한 온톨로지 데이터를 확보하기 위해 정보생산자로부터 사전어휘에 대한 온톨로지 트리플을 생성하는 실험을 하였다. 온톨로지 자동구축에 대한 연구와 개발이 활발하지만 보편적 시멘틱 검색을 위해 정보생산자와 정보관리자가 많은 부분 데이터를 생성하고 검증해야할 필요가 있다.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.158-168
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• 2017

As the big data technologies advance, there is an increasing interest in systematic methodologies for data-based policy determination especially in the public health area. This study proposes a method to develop an issue detection model through the collaboration with domain experts in order to intelligently detect major socio-national issues on infectious diseases based on data. At first, the factors influencing the 'domestic inflow of foreign infectious diseases' are determined and variables representing the factors are set. Thereafter, by using system dynamics methods, the causal analysis is made to find causal map indicating main influential factors. In this process, an empirical modeling is conducted through collaboration between data analysts and experts in the infectious disease domain. The proposed issue detection approach based on domain knowledges will make it possible to make a decision on policies more efficiently if the detection system is capable of continuos monitoring of the related issues.