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재난 상황 판단 지원을 위한 한국 학술지 논문의 저자 소속기관 식별 및 협업관계 분석 연구
김병규(Byungkyu Kim),유범종(Beom-Jong You),심형섭(Hyoung-Seop Shim) 한국컴퓨터정보학회 2021 韓國컴퓨터情報學會論文誌 Vol.26 No.12
본 논문에서는 재난 상황에서의 신속하고 효과적인 의사결정 및 대응을 지원하기 위하여 학술연구 논문의 저자소속 기관을 식별하고 이를 바탕으로 협업관계 분석연구를 수행하였다. 이를 위해 국내 학술지 69종에 수록된 재난안전유형 논문 2,308건을 대상으로 KISTI의 한국과학기술인용 색인데이터베이스와 기관식별데이터를 기반으로 실험데이터를 구축하였다. 협업관계 분석은 기관, 기관유형, 기관지역, 대학기관의 단위별로 출현빈도 등의 통계 현황을 비교 분석하고, 사회네트워크분석 기법을 사용하여 각각의 동시출현 네트워크의 기본 속성과 주요 중심성 지수를 산출하고 분석하였다. 또한 단위별 네트워크 협업관계를 전체적으로 조망할 수 있도록 시각화 맵을 생성 및 제시하였다. 본 연구의 결과는 효과적인 재난 대응을 지원하는 기관 및 협업 그룹의 탐색 활동과 관련 정보서비스체계 기반 마련에 기여할 수 있을 것으로 기대된다. In this paper, in order to support rapid and effective decision-making and response in disaster situations, we identified the author"s organization of academic research papers and conducted a collaborative relationship analysis study based on this. For this purpose, 2,308 papers in 69 Korean academic journals classified by disaster and safety type were selected for analysis and experimental data were constructed based on the Korea Science Citation Database (KSCD) and institutional identification data provided by KISTI. Collaborative relationship analysis was conducted for each of the four units (Institution, Institution type, Institution region and University department type). First, statistical status such as frequency of appearance was compared, and basic properties and main centrality index of each co-occurrence network were calculated and analyzed using Social Network Analysis Method. In addition, a visualization map was created and presented for each network so that the collaborative relationship could be viewed and understood as a whole. The results of this study are expected to contribute to the search activities of institutions and cooperative groups that support effective disaster response and to lay the foundation for the information service system.
조혜찬 한국정보법학회 2016 정보법학 Vol.20 No.3
The importance of big data as a new source of industry development is rapidly on the rise globally. Commonly referred to as being in the “Big Data Era,” business analysts observe that big data will create new value both in public and private sectors. Empirical research shows that the financial industry will perhaps benefit the most from big data capabilities by utilizing large amount of personal information. Korea begins putting a significant value on big data potentials. Korean financial institutions have necessarily demanded deregulation of utilizing personal information to fully take advantage of big data systems for their businesses. Likewise, the Korean government wants to promote a favorable environment for big data utilization. One tangible effort is to relax the regulatory burdens as shown in Big Data Personal Information Protection Guideline (“Big Data Guideline”) published by a governmental authority, the Korea Communications Commission. According to the guideline, personal information managers can collect, use and transfer publicly available information and customer’s usage history information without prior consent if the information is de-identified. However, Korean regulatory agencies are rather cautious of allowing personal information utilization by virtue of big data because they experienced a series of high profile and serious personal information leakage incidents by big corporations in recent times. The Korean Personal Information Protection Act (“PIPA”), known as one of the far-reaching and austere personal information protection laws in the world, is a byproduct of this heightened concern. PIPA strictly requires prior informed consent when a person collects or utilizes other person’s personal information. With the backdrop of this arguably tense atmosphere in Korea, this thesis will attempt to deal with the relevant legal issues surrounding financial institutions’ use of publicly available information and usage history information without prior consent. First, it is posited that it is too risky for financial institutions to solely rely on the Big Data Guideline because it is an administrative rule, lacking relevant statutory basis. Second, de-identification as a sole prerequisite to consent exemption is a vulnerable method. Information profiling enables re-identification of once de-identified personal information, and thus the re-identified information should be subject to PIPA’s prior consent requirement. Especially, much of usage history information is sensitive information where PIPA adds extra caution. Third, taking publicly available personal information for profit is against the Constitutional right of self-determination on personal information. In order to fully appreciate the merits of big data but minimizing infringement of personal information rights, this thesis delivers two possible suggestions. First, PIPA should be amended with possibly three options to relieve or relax the current statutory regulation. The administrative rule alone, possibly conflicting with PIPA, falls short of truly encouraging financial institutions to benefit the value of big data given the reality of harsh potential penalties under PIPA. Secondly, anonymization should be adopted instead of de-identification as a pre-condition to allow personal information utilization without prior consent as UK, EU and Japan.
김진영,이석형,서동준,김광영 한국디지털콘텐츠학회 2016 한국디지털콘텐츠학회논문지 Vol.17 No.6
Science and technology contents (research papers, patents, reports) are the most common reference material for researchers involved in research and development in the fields of science and technology. Based on various search elements (title, abstract, keyword, year of publication, name of journal, name of author, publisher, etc.), many services are available for users to search science and technology contents and bibliographic information owned by libraries. Authority data on organization name can be useful as an element for author identification and as an element to search for results produced by specific organizations. However, organization name is not taken into account by current search services for domestic academic information and bibliographic records. This study analyzes organization name data contained in the metadata of science and technology contents, which are the basis of the establishment of authority data, and proposes a method and system based on string containment and exact string matching.