• Title/Summary/Keyword: 공공데이터 활용

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The College Reputation System using Public Data and Sentiment Analysis (공공데이터와 감성분석을 이용한 대학평판시스템)

  • Kim, Eun-Ah;Lee, Yon-Sik
    • Convergence Security Journal
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    • v.18 no.1
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    • pp.103-110
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    • 2018
  • Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.

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Open Research Data Policy Trends and Domestic Status (오픈 연구데이터 정책 동향 및 국내 현황)

  • Choi, Myung-Seok
    • Proceedings of the Korean Society for Information Management Conference
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    • 2017.08a
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    • pp.97-97
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    • 2017
  • 최근 연구 환경과 연구 패러다임이 데이터 중심으로 변화되고 있다. 특히, 공공 연구성과의 개방과 공유에 기반한 오픈 사이언스(Open Science)가 과학 연구의 글로벌 어젠더로 새롭게 부각되고 있다. OECD는 오픈 사이언스를 정책의제로 채택하고 있으며, 미국, 영국, 호주 등 세계 선진국에서는 공공자금이 투입된 연구과제로부터 생산된 연구데이터의 체계적인 관리와 쉬운 접근, 재사용을 통한 가치 창출을 위해 데이터 관리 계획(Data Management Plan)을 비롯한 오픈 연구데이터 정책을 적극적으로 시행하고 있다. 하지만 국내에서는 연구데이터를 공유 활용하기 위한 법제도적 기반과 관련 인프라가 아직 미흡한 실정이다. 이 연구에서는 오픈 연구데이터를 위한 세계 각국의 정책 동향을 소개한다. 그리고, 국가과학기술연구회 소속 22개 정부출연 연구기관과 국내 20개 대학의 연구자를 대상으로 조사한 연구데이터 생산, 관리, 활용 현황과 데이터 공유 활용을 위한 시사점과 개선방향을 살펴본다.

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A Location Recommendation Model for Public Sports Facilities (공공데이터를 활용한 도시 내 공공체육시설 위치 추천)

  • Lim, Joo-Young;Paeng, So-Yeon;Lee, Ga-Eun;Lee, Chan-Nyoung;Koo, Jae-Sung;Ahn, Seo-Hyun;Kang, Min-Ji;Kim, Jin;Lee, Jee Hang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.365-367
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    • 2022
  • 본 논문에서는 서울시를 대상으로 2020년 기준 자치구별 공공체육시설의 개수를 분석하고, 도출된 서비스 지역 적정 개소 수를 기준으로 추가 설치가 필요한 자치구 내 입지를 예측하였다. 기존 공공 체육시설 수와 선행연구의 입지 지표를 활용해 회귀분석을 바탕으로 유의한 입지요인을 도출하고, 이를 변수로 한 k-means 군집화를 통해 자치구별 입지 후보군이 될만한 행정구역상 동을 구분하였다. 이후 선정된 행정구역 내 기준 인구 당 공공체육시설 비율이 같아지도록 공공체육시설 설치 개수를 결정한 다음 각 구역의 중심점으로부터 가까운 동 순으로 공공체육시설의 추가 설치가 필요한 동을 선정하였다.

A Location Guide App Service for Electric Vehicle Charging Station using Public Data (공공데이터를 활용한 전기차 충전소 위치 안내 앱 서비스)

  • Kim, Jong-Woo;Oh, Sang-Hun;Min, Kyung-Hwi;Kim, Ki-Hyuk;Jung, Deok-Gil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.370-372
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    • 2017
  • Recently, at home and abroad, as the demand and supply of electric vehicles have increased, the spread of charging stations for electric vehicles is accordingly spreading out. In this paper, we provide the location, price, and service information of the electric car charging station through the big data analysis by using Open API of the public data and evaluation service provided by KEPCO, thereby inducing communication among users.

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SNA Pattern Analysis on the Public Software Industry based on Open API Big Data from Korea Public Procurement Service (조달청 OPEN API 빅데이터를 활용한 공공 소프트웨어 산업의 SNA 패턴 분석)

  • KIM, Sojung lucia;Shim, Seon-Young;Seo, Yong-Won
    • Informatization Policy
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    • v.24 no.3
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    • pp.42-66
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    • 2017
  • This study investigated the ecological change of public software industry, comparing the pre and post structure of industry network based on the application of the regulation restricting large company participation in public software market. For this purpose, we used big data of the software market from Korea Public Procurement Service and used the SNA(Social Network Analysis) methodology which is being actively used in the area of social science recently. Finally, we highlighted the contribution of open public data. By analyzing order and contract data of the public software industry for 3 years - from 2013 to 2015 - we found out two main things. First, we observed that Power Law distribution had been going on in the public software industry, regardless of the external impact of regulation. Second, despite the existence of such Power Law distribution, we also observed the ecological change of industry structure from year to year. We presented the implication of such findings and discussed the advantage of open public data as the original motivator of this study.

A Study on Estimating Housing Area per capita using Public Big Data - Focusing on Detached houses and Flats in Seoul - (공공빅데이터를 활용한 1인당 주거면적 추정에 관한 연구 - 서울의 단독 및 다세대 주택을 중심으로 -)

  • Lim, Jae-Bin;Lee, Sang-Hoon
    • Journal of the Korean Regional Science Association
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    • v.36 no.1
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    • pp.51-67
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    • 2020
  • The purpose of this study is to estimate the housing area per capita for verifying if the public Big Data, of the building ledger and resident registration ledger, can be used as well as the National Census and Housing Survey. The Mankiw and Weil (MW) model was constructed by extracting samples of general detached houses and flat houses from the public big data, and compared with the result from traditional survey method. Then, the MW models of 25 municipalities in Seoul was established. As a result, it can be confirmed that it is possible to establish MW models comparable to regular surveys using public big data, and to establish a model for each basic localities which was difficult to use as a regular survey method. Public Big Data has the advantage of expanding the knowledge frontier, but there are some limitations because it uses data generated for other original purposes. Also, the difficult process of accessing personal information is a burden to carry out analysis. It is expected that continuing research should be needed on how public Big Data would be processed to complement or replace traditional statistical surveys.

Optimal Location Modeling for Elementary Student's Care facility using Public Data (공공데이터를 활용한 초등학생 돌봄시설의 최적입지 선정)

  • Lee, Ji-Won;Kim, Ji-Young;Yu, Ki-Yun;Yang, Sung-Chul
    • Journal of Cadastre & Land InformatiX
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    • v.49 no.2
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    • pp.109-122
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    • 2019
  • The expansion of double-income households is increasing the social interest in child care. In particular, children's entrance into elementary school is considered to be the main cause of women's career break as well as childbirth. This study proposes an optimal location selection method for caring facilities for elementary school students. As a candidate for care facilities, we selected existing child care facilities. We proposed a dual structure evaluation method that considers locational characteristics as well as mathematical optimization when selecting the optimal location. The experiment was conducted in Songpa-gu, Seoul. A total of 36 optimal locations were selected from a total of 258 candidate facilities. First, the evaluation criteria were established using public data, and the primary candidate facilities were selected by ranking the location scores. At this time mesh resampling method was used to integrate various public data into one. Next, the final care facilities were selected using the p-median method. The results chosen are not only the optimal location considering total distance but also satisfy various location criteria considering the characteristics of the care facility. We expect that the proposed method will contribute to public data convergence or utilization and it will be helpful for policy decision when selecting the optimal location for public facilities.

Design of Dataset Archive for AI Education (인공지능 교육을 위한 데이터셋 아카이브 설계)

  • Lee, Se-Hoon;Noh, Ye-Won;Noh, Yeon-Su
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.233-234
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    • 2022
  • 본 논문에서는 효율적인 AI 교육을 위한 데이터셋 아카이브와 데이터 활용을 위한 프로그래밍 플랫폼과의 연동 모듈을 제안한다. 데이터셋 아카이브는 공공데이터를 전처리하여 생성한 데이터를 모아 설계하며, 프로그래밍 플랫폼 코드비(CodeB)와 연동하여 데이터를 활용할 수 있도록 한다. 코드비(CodeB)는 파이썬 블록 프로그래밍 플랫폼으로 연동을 통해 데이터를 활용한 프로그래밍이 가능하다.

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On Study of Rural Regional Development Planning by using GIS (GIS를 활용한 농촌지역개발계획 수립에 관한 연구)

  • Kim, Sang-Bum;Rhee, Sang-Young;Kim, Eun-Ja;Kim, Yong-Wook
    • Proceedings of the Korean Society of Community Living Science Conference
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    • 2009.09a
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    • pp.96-96
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    • 2009
  • 최근 이상적인 계획안 수립을 위한 주요 요건은 대상지역의 물리적 비물리적 현황에 대한 충분한 이해와 검토에서 출발한다고 해도 과언이 아니다. 차별화된 계획 혹은 아이디어는 지역이 지닌 특성과 문제점에 대한 분석을 통하여 가능하기 때문이다. 다시 말해 현재 상황에 대한 철저한 인식을 바탕으로 미래에 대한 구체적인 계획안은 도출될 수 있기 때문이다. 이 과정에서 해당 지역의 구성원이자 대표적인 이해당사자인 거주민들은 해당지역의 주요 속성정보 제공자로서 중요한 역할을 담당한다. 기존 계획수립과정에서 활용되어 왔던 자료는 주로 지자체 등 공공기관에서 제공하는 공공데이터를 기반으로 하고 있지만, 이러한 공공데이터의 활용은 최신정보의 제공 및 디테일한 지역의 특성을 포괄적으로 반영하는 데 일정부분 한계를 지니고 있다. 이러한 한계를 극복할 수 있는 대안으로, GIS 기법과 양방향 인터넷 등 다양한 첨단 IT기술을 활용한 주민참여형 계획수립에 주목하고 있다. 본 연구는 GIS를 활용한 해외사례를 고찰하고 이를 통하여 도출된 지역분석기법을 예산군에 적용함으로서 향후 주민참여형 지역기본 계획수립에 대한 활용방안을 제시하였다.

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Big Data Analysis for Public Libraries Utilizing Big Data Platform: A Case Study of Daejeon Hanbat Library (도서관 빅데이터 플랫폼을 활용한 공공도서관 빅데이터 분석 연구: 대전한밭도서관을 중심으로)

  • On, Jeongmee;Park, Sung Hee
    • Journal of the Korean Society for information Management
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    • v.37 no.3
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    • pp.25-50
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    • 2020
  • Since big data platform services for the public library began January 1, 2016, libraries have used big data to improve their work performance. This paper aims to examine the use cases of library big data and attempts to draw improvement plan to improve the effectiveness of library big data. For this purpose, first, we examine big data used while utilizing the library big data platform, the usage pattern of big data and services/policies drawn by big data analysis. Next, the limitations and advantages of the library big data platform are examined by comparing the data analysis of the integrated library management system (ILUS) currently used in public libraries and data analysis through the library big data platform. As a result of case analysis, big data usage patterns were found program planning and execution, collection, collection, and other types, and services/policies were summarized as customizing bookshelf themes for the book curation and reading promotion program, increasing collection utilization, and building a collection based on special topics. and disclosure of loan status data. As a result of the comparative analysis, ILUS is specialized in statistical analysis of library collection unit, and the big data platform enables selective and flexible analysis according to various attributes (age, gender, region, time of loan, etc.) reducing analysis time. Finally, the limitations revealed in case analysis and comparative analysis are summarized and suggestions for improvement are presented.