• Informatization Policy
• /
• v.26 no.1
• /
• pp.25-45
• /
• 2019

With the advent of the data economy, interest in using big data has increased, but conflicts with protecting personal information have been also steadily raised. In this regard, major countries are accelerating use of big data by exempting de-identified, pseudonymous personal information from protection. However, these policies have been made without the understanding that the economic value of personal information has been actually changing slowly. This paper presents the concept of 'collected information' and defines it as having public interest and therefore, not the exclusive property of the collector of such information. The paper shows the collected information has public interest in terms of personal information protection, connectivity, and universal service and public goods. It also specifies that the 'data governance' cannot be applied to the current data utilization framework that depends upon the holder's consent; rather, it raises the need to improve the practices of information provision consent or provide the beneficiary right of information use to the information holder in order to ensure the proper 'data governance' that will turn market failure into success.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.483-486
• /
• 2021

With the explosive increase in data, the 'big data era' has arrived, focusing on deriving new values and insights through data. With the development of data analysis technology, the importance of data analysis and utilization in the field of diagnosis and treatment as well as prevention is expanding, while the use of big data is emerging in the healthcare field. Moreover, as the three data-related laws (Personal Information Protection Act, Information and Communication Network Act, and Credit Information Act) were passed in January 2020, it became possible to use a wide range of big data through pseudonym information. However, the use of healthcare big data is still struggling due to various policies and regulations, inconsistent data quality, and the absence of specialized personnel. Therefore, in this study, examines the current state of use of big data in the healthcare field, and analyzes the challenges, overseas cases, plans, and expected effects for activation of healthcare big data.

• The Korean Society of Law and Medicine
• /
• v.22 no.4
• /
• pp.3-35
• /
• 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 Korean Medical classics
• /
• v.18 no.4 s.31
• /
• pp.155-165
• /
• 2005

진당시기대상한론치법적연구유(晋唐時期對傷寒論治法的硏究有): 왕숙화운용당시성행적(王叔和運用當時盛行的)‘한(汗), 토(吐), 하(下), 온(溫), 구(灸), 자(刺), 수(水), 화(火)’등팔법(等八法), 귀납료상한론적증치경험(歸納了傷寒論的證治經驗); 손사막근거자기적임상경험(孫思邈根據自己的臨床經驗), 파상한론적태양병편진행료(把傷寒論的太陽病篇進行了)‘이방명법(以方名法), 안법류증(按法類證)’, 저시해시기대상한론육경병치법적대표성적연구(這是該時期對傷寒論六經病治法的代表性的硏究), 저종연구유원시화력사적국한성(這種硏究有原始和歷史的局限性), 종중국의학대상한론육경병치법적연구력사고려(從中國醫學對傷寒論六經病治法的硏究歷史考慮), 저성위료후세적치법연구적선구자(這成爲了後世的治法硏究的先驅者), 구유비상대적영향(具有非常大的影響). 재송대대상한론치법적연구상(在宋代對傷寒論治法的硏究上), 기관건작용적의가유방안시화주굉(起關鍵作用的醫家有龐安時和朱肱). 타문대상한론치료원칙적천발(他們對傷寒論治療原則的闡發), 대륙경병적분석귀납(對六經病的分析歸納), 이급제시구체적치법상(以及提示具體的治法上), 도주출료공헌(都做出了貢獻). 방안시주장료응안인(龐安時主張了應按人), 지(地), 시제정치료적사상(時制定治療的思想); 주굉이(朱肱以)‘병유표본(病有標本), 치유선후(治有先後)’위치료원칙(爲治療原則), 여상한론상결합진행치료(與傷寒論相結合進行治療), 대후세의가산생료영향(對後世醫家産生了影響). 도료금원대성무기(到了金元代成無己), 류완소(劉完素), 왕호고등(王好古等), 대내경내용각자이사상관점(對內經內容各自以思想觀点), 분별안변증론치총결료육경병적치료규율(分別按辨證論治總結了六經病的治療規律), 동시대증후화방약진행료분석(同時對證候和方藥進行了分析), 천명료구체적육경병치법적병리전귀(闡明了具體的六經病治法的病理轉歸), 도유기독창성(都有其獨創性). 성무기용내경해석료상한론(成無己用內經解釋了傷寒論), 총결해기(總結解肌) 발한(發汗) 중제발한(重劑發汗) 해표행수(解表行水) 화해(和解) 공비 지열(止熱) 삼설등치법, 위후세대상한론치법적연구개벽료도로, 인이갱가명확화해적개념(因而更加明確和解的槪念), 병응용지금(幷應用至今). 류완소제창료주화론(劉完素提倡了主火論), 중시료상한론한(重視了傷寒論汗), 토(吐), 하삼법적연구(下三法的硏究), 창립료신량해표법(創立了辛凉解表法), 대후세온병치료적발전대래료흔대영향. 왕호고작위이수학파(王好古作爲易水學派), 운용장부적한열허실이론결합약미효능(運用臟腑的寒熱虛實理論結合藥味效能), 탐색료상한론육경병적치료규율(探索了傷寒論六經病的治療規律), 강조료양명병적익진액적치료원칙(强調了陽明病的益津液的治療原則), 대후세연구상한론치법급여료흔대적계발. 이상대상한론치법연구(以上對傷寒論治法硏究), 불근성위당시임상의학적선도(不僅成爲當時臨床醫學的先導), 이차성위료후세연구상한론치법적기초(而且成爲了後世硏究傷寒論治法的基礎).

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.2
• /
• pp.287-304
• /
• 2020

There have been a number of legal & policy studies on the affecting factors of big data utilization, but empirical research on the composition factors of personal information regulation or data combination, which acts as a constraint, has been hardly done due to the lack of relevant statistics. Therefore, this study empirically explores the priority of personal information regulation factors and data combination factors that influence big data utilization through Delphi Analysis. As a result of Delphi analysis, personal information regulation factors include in order of the introduction of pseudonymous information, evidence clarity of personal information de-identification, clarity of data combination regulation, clarity of personal information definition, ease of personal information consent, integration of personal information supervisory authority, consistency among personal information protection acts, adequacy punishment intensity in case of violation of law, and proper penalty level when comparing EU GDPR. Next, data combination factors were examined in order of de-identification of data combination, standardization of combined data, responsibility of data combination, type of data combination institute, data combination experience, and technical value of data combination. These findings provide implications for which policy tasks should be prioritized when designing personal information regulations and data combination policies to utilize big data.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.57-71
• /
• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.