• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.561-564
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• 2016

If using crime map which represents criminal section that violent crimes targeting women frequently happened, the police could prevent additional crimes by positioning themselves intensively in expected crime zones and each individual could avoid being damaged by referring information of criminal zones. In this paper, by analyzing crimes targeting women and offender information which is provided in public-opened datum portal, we suppose a system which prevents crimes that calculates locational danger and, by considering location and age group of users, provides user-customized information of danger. By crawling the criminals datum which is provided in public-opened datum portal, It collects them. About the areas which happened sexual crimes, calculating danger of crime based on statistical crime information including criminal information, residence of offenders, areas which happened sexual crimes, sentences and the number of crime, this system is able to visualize the areas which sexual crimes happened based on information of danger grade representing on user's location. The score of danger calculated in location unit can provide criminal information according to location and ages of users by interacting GIS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1337-1342
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• 2019

Medical institutions face the challenge of securing competitiveness among medical institutions due to the rapid spread of ICT convergence, and managing data that is growing at an enormous rate due to the emergence of big data and the emergence of the Internet of Things. The big data paradigm of the medical community is not just about large data or tools and processes for processing and analyzing it, but also means a computerized shift in the way people live, think and study. As the medical data is recently released, the demand for the use of medical data is increasing. Therefore, the research on disease detection system based on public data using open source that can help rational and efficient decision making was conducted. As a result of the experiment, unlike a simple disease inquiry or a symptom inquiry about a single disease provided by a public institution, related diseases are searched by a symptom or a cause.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.57-58
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• 2017

사물인터넷 환경의 다양한 기기에서는 매초마다 시스템 로그 데이터, 온도, 습도, 조도 및 위치 정보 등과 같은 데이터를 지속적으로 생성한다. 이렇게 생성된 데이터는 기기 안에서 대부분 소멸되거나 수집된다 하더라도 시스템 개선의 일부 목적으로 활용하는데 그칠 뿐이다. 본 논문에서는 각각의 사물인터넷 기기에서 발생하는 비정형 데이터를 스트리밍 방식을 통해 수집 서버로 전송하고 이를 유연한 스키마 구조를 가지는 NoSQL 데이터베이스에 적재하는 프레임워크 설계를 제안한다. 이렇게 수많은 장비로부터 수집된 로그 및 센싱 데이터는 빅데이터 분석을 통해 산업의 현장에서 생산성 향상을 위해 사용할 수 있으며 공공의 목적으로 도심지의 교통문제 해소와 재난 및 재해 예측에 활용될 수 있다.

• The Korean Society of Law and Medicine
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• v.22 no.4
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• pp.3-35
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• 2021

Inmitten der Flut der privaten und öffentlichen Information gilt die riesige Informationsmenge als Schlüsselressource im Zeitalter der 4. industriellen Revolution, repräsentiert durch Big-Data. Das Interesse an diesen wächst weltweit. Es gibt eine aktive Diskussion darüber, wie man Daten sichert und akkumuliert und wie man die gesammelten Daten sicher und effektiv nutzt. Gesundheitsdaten werden vor allem als die wertvollste Ressource bewertet, für die Big-DataTechnologie eingesetzt wird. Um Gesundheitsdaten sinnvoll zu nutzen, müssen verteilte Gesundheitsdaten integriert und den Benutzern in einer Form zur Verfügung gestellt werden, die für Forschung oder Inspektion verwendet werden kann. In einer Situation, in der große Länder um den Aufbau bzw. die Führung der Datenwirtschaft konkurrieren, wurden im August 2020 auch in Südkorea die sog. „3-Daten-Gesetze" geändert, die das Datenschutzgesetz(DSG) enthälten. Das DSG führte das Konzept der pseudonymen Informationen ein und baute eine Rechtsgrundlage für deren Verwendung auf. Als Folgemaßnahme kündigte die, Kommission für den Schutz personenbezogener Daten(Personal Information Protection Commission: PIPC)' die „Richtlinien für die Bahandlung mit pseudonymen Informationen" und, Ministerium für Gesundheit und Wohlfahrt' die „Richtlinien für die Verwendung von Gesundheitsdaten" an. Gesundheitsdaten stehen direkt in Zusammenhang mit Leben und Körper des Menschen und damit enthalten viele sensible Daten. Es handelt sich also um ein System, das aus einer vorsichtigeren und konservativeren Sicht unter der Voraussetzung verwendet werden kann, personenbezogene Daten sicherer zu schützen. Um die Hauptinhalte der „Richtlinien für Verwendung von Gesundheitsdaten" zu analysieren, überprüften wir zunächst die Hauptinhalte des überarbeiteten DSG. Danach durch die Analyse der wesentlichen Inhalte der „Richtlinien für Verwendung von Gesundheitsdaten" wurden Probleme wie Konflikte mit anderen Gesetzen und Verbesserungsmaßnahmen überprüft.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.273-287
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• 2015

This study aimed to investigate the impact of the epidemic disease including Middle East Respiratory Syndrome Coronavirus (MERS) on the usage of public libraries. Such disease yields anxiety throughout the nation and discourages social activities in general. 18,711,453 records from 303 public libraries were examined with "big data retrieval & analysis platform for public libraries" located in Sejong National Library. The results are as follows. First, in 2015, when MERS was prevalent, the daily mean of books checked out was 64,645.05, showing decrease of 6,300 per day compared to that of 2014. Second, in 2014, the daily mean of books checked out from July 5th to August 19th was greater than that of from April 4th to May 19th and that of from May 20th to July 4th, implying the impact of summer vacation on the increase in books checked out in public libraries. Third, in 2015, the daily mean of books checked out from July 5th was greater than during MERS outbreak(from May 20th to July 4th), while it did not show statistically significant difference with that of before the outbreak. Fourth, the daily mean of books checked out did not show statistically significant difference between 2014 and 2015 before and during the outbreak, while it showed statistically significant difference between 2014 and 2015 after the epidemic period. The results indicate that MERS and the anxiety it brought nationwide had an impact on the daily mean of books checked out in public libraries after the epidemic period rather than during the outbreak.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.149-152
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• 2024

본 논문에서는 자치구별 집 가격과 인프라 데이터를 통한 분석을 기반으로, 저렴한 주택 지역에 입주하는 사람들의 우려와 관련하여 좋은 동네와 안좋은 동네의 차이를 다각도로 조망하고자 한다. DataSet은 서울 열린 데이터 광장과 보건의료 빅데이터 개방 시스템에서 수집한 공공데이터를 활용한다. dependent variable로는 자치구별 인프라 데이터셋을 사용하였으며, independent variable는 자치구별 집 가격을 기반으로 데이터 분석을 수행한다. 본 논문에서는 다양한 분석 기법을 활용하여 모델의 정확도와 신뢰성을 향상시키고, 이를 토대로 동네의 특징과 주거 환경의 차이를 명확히 도출하여 결론을 이끌어내고자 한다.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.19-25
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• 2020

Big data analytics are indispensable today in various industries and public sectors. Therefore, in this study, we will utilize big data analysis to search for improvement plans for domestic tourism services using the LDA analysis method. In particular, we have tried an exploratory approach that can improve tourist satisfaction, which can improve revisit and service, especially in Seoul, which has the largest number of foreign tourists. In this study, we collected and analyzed statistical data of Seoul City and Korea Tourism Organization and Internet information such as SNS via R. And we utilized text mining methods including LDA. As a result of the analysis, one of the purposes of visiting South Korea by foreigners was gastronomic tourism. We will try to derive measures to improve the quality of services centered on gastronomic tourism.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.133-145
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• 2022

As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.95-96
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• 2021

본 논문에서는, 서울시 자치구별 공공데이터를 활용한 분석 정보를 통해, 도시가 어떤 구조와 산업으로 형성되었는지 알아본다. 데이터 분석을 통해 얻어진 서울의 특징과 도시(자치구별)의 교통 측면, 상업, 데이터에서 발견한 정보를 통해 도시 특성과 구조를 알아본다. 본 논문에서 연구한 결과는 스마트 도시 정책에 활용하여 도시 기본 설계시 교통, 주거, 상업 등의 효율성을 증대 시키는데 기본 자료로 활용할 수 있다.