정보관리학회지 (Journal of the Korean Society for information Management)

  • 제36권4호
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  • Pages.253-277
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  • 2019
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  • 1013-0799(pISSN)
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  • 2586-2073(eISSN)
한국정보관리학회 (Korean Society for Information Management)
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형사사법정보의 빅데이터 활용방안 연구: 구조화 범주화 관점으로

A Study on the Use of Criminal Justice Information Big Data in terms of the Structuralization and Categorization

  • 투고 : 2019.11.17
  • 심사 : 2019.12.23
  • 발행 : 2019.12.30
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초록

4차 산업혁명시대를 맞아 데이터의 중요성은 심화되고 있으나, 개인정보보호 등의 문제로 데이터의 활용이 쉽지 않은 경우가 많이 있다. 형사사법정보는 범죄 예측 및 예방, 범죄수사 과학화, 양형합리화 등 다양한 활용가치가 예상됨에도 현재 개인정보보호와 형사사법정보 관련 법률적 해석 문제로 활용이 상당히 제한되고 있다. 본 연구는 형사사법정보의 구조화·범주화를 통해 '범죄데이터'로 전환하여 빅데이터로서 활용하도록 제안하였으며, '범죄데이터' 활용시 법률적 문제, 활용가치, 데이터 생성 및 활용시 고려사항을 전문가를 통해 검증하고 향후 전략적 발전방안을 도출하였다. 연구결과, '범죄데이터'는 개인정보보호문제는 해결된 것으로 보여지나, 형사사법정보 관련법에 명시할 필요는 있으며, 빅데이터 활용을 위해 분석 가능하도록 표준화된 형태로 정리되는 것이 시급함이 밝혀졌다. 향후 진행방향으로는 데이터 요소 도출, 용어사전 시소러스 구축, 데이터 등급화를 위한 개인민감정보 정의 및 등급지정, 비정형데이터의 정형화를 위한 알고리즘 개발 등을 제시하였다.

In the era of the 4th Industrial Revolution, the importance of data is intensifying, but there are many cases where it is not easy to use data due to personal information protection. Although criminal justice information is expected to have various useful values such as crime prediction and prevention, scientific investigation of criminal investigations, and rationalization of sentencing, the use of criminal justice information is currently limited as a matter of legal interpretation related to privacy protection and criminal justice information. This study proposed to convert criminal justice information into 'crime data' and use it as big data through the structuralization and categorization of criminal justice information. And when using "crime data," legal issues, value in use, considerations for data generation and use were verified by experts, and future strategic development plans were identified. Finally we found that 'crime data' seems to have solved the privacy problem, but it is necessary to specify in the criminal justice information related law and it is urgent to be organized in a standardized form for analysis to use big data. Future directions are to derive data elements, construct a dictionary thesaurus, define and classify personal sensitive information for data grading, and develop algorithms for shaping unstructured data.

키워드

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