초록

Abstract

The purposes of this study are to evaluate the navigability of three web-based mapping applications and to suggest how to improve the navigability of all web-based mapping applications. With these purposes, this study conducted a web-based survey congruent with a think aloud and systematic observation for individual participants, followed up by a focus group with all participants. Based on the findings, recommendations are proposed for web-based mapping applications that include a standard click and drag panning function in mapping applications, a scaled zooming option, increased text for icons and buttons, and other potential changes to computer hardware for increased navigability in these applications. By improving the navigability of web-based mapping applications, the learning time may be reduced for each application and the speed at which users’ geographic information needs are met will be quicker.

초록

본 연구의 목적은 1) 소설 속 지명 데이터베이스(DB)를 구축하고, 2) 확장 가능한 지명 DB를 위해 자동으로 지명을 추출하여 데이터베이스를 갱신하며, 3) 데이터베이스 내의 소설지명과 용례를 검색하고 시각화하는 파일럿시스템을 구현하는 데 있다. 특히, 학습자료(training)에 해당하는 말뭉치(corpus)를 확보하기 어려운, 소설지명과 같이 현재 잘 쓰이지 않는 개체명을 자동으로 추출하는 것은 매우 어려운 문제이다. 효과적인 지명 정보 추출용 학습자료 말뭉치 확보 문제를 해결하기 위해 본 논문에서는 이미 수작업으로 구축된 웹 지식(어휘사전)을 활용하여 학습에 필요한 충분한 양의 학습말뭉치를 확보하는 방안을 적용하였다. 이렇게 확보된 학습용 코퍼스와 학습된 자동추출 모듈을 가지고, 새로운 지명 용례를 찾아 추가하는 지명 데이터베이스 확장 도구를 만들었으며, 소설지명을 지도 위에 시각화하는 시스템을 설계하였다. 또한, 시범시스템을 구현함으로써 실험적으로 그 타당성을 입증하였다. 끝으로, 현재 시스템의 보완점을 제시하였다.

Abstract

This study aimed to design a semi-automatic web-based pilot system 1) to build a Korean novel geo-name, 2) to update the database using automatic geo-name extraction for a scalable database, and 3) to retrieve/visualize the usage of an old geo-name on the map. In particular, the problem of extracting novel geo-names, which are currently obsolete, is difficult to solve because obtaining a corpus used for training dataset is burden. To build a corpus for training data, an admin tool, HTML crawler and parser in Python, crawled geo-names and usages from a vocabulary dictionary for Korean New Novel enough to train a named entity tagger for extracting even novel geo-names not shown up in a training corpus. By means of a training corpus and an automatic extraction tool, the geo-name database was made scalable. In addition, the system can visualize the geo-name on the map. The work of study also designed, implemented the prototype and empirically verified the validity of the pilot system. Lastly, items to be improved have also been addressed.

초록

Abstract

Emerging Web 2.0 services such as Twitter, Blogs, and Wikis alongside the poorly- structured and immeasurable growth of information requires an enhanced information organization approach. Ontology has received much attention over the last 10 years as an emerging approach for enhancing information organization. However, there is little penetration into current systems. The purpose of this study is to propose ontology implementation and methodology. To achieve the goal of this study, limitations of traditional information organization approaches are addressed and emerging information organization approaches are presented. Two ontology data models, RDF/OW and Topic Maps, are compared and then ontology development processes and methodology with topic maps based medical information retrieval system are addressed. The comparison of two data models allows users to choose the right model for ontology development.

초록

세계에는 수많은 도서관이 있지만 어떤 시스템도 이 모든 도서관에 대한 정보를 총체적으로 제공하는 기관은 없다는 인식에서, 본 연구에서는 위키원리 기반 도서관지도정보시스템을 구축하고자 하였다. 또한 구글지도서비스를 매쉬업함으로써 도서관위치정보서비스도 제공하고자 하였다. 새로운 서비스 시스템이 개발됨에 따라, 이 시스템을 통해 제공될 정보의 효과적 조직 및 관리를 위해 새로운 메타데이터를 개발할 필요가 있었으며, 이를 위해 델파이 연구기법을 적용하였다. 델파이 전문위원으로 대학, 전문, 학교, 공공, 국가도서관의 사서를 포함하여 도서관 지도정보의 전문가인 연구소의 연구원 및 대학의 교수진 등 총 13명을 위촉하였다. 이들을 대상으로 한 제 3차에 걸친 델파이 설문분석과정을 통해, 초기 메타데이터 항목에 대한 추가, 수정, 삭제가 이루어졌으며, 도서관 위치정보, 도서관 정보, 장서정보, 행사정보로 구성된, 4개 부문 49개 항목의 메타데이터가 최종적으로 제안되었다.

Abstract

This study aimed to construct the Library Map Information System(LMIS) based on the Wiki theory of Web 2.0. We built this system because there was no collective source of information about every library in the world. Also, this system was developed to provide a library location information service by mashing-up with the Google Map. Through this study, the metadata applied to the newly constructed system was developed by using the Delphi method. A total of 13 experts including librarians of schools, public, academic, special, and national libraries as well as LIS faculty members and researchers, were commissioned as Delphi experts. Through three rounds of a Delphi survey analysis, the addition, modification, and deletion of the initial metadata elements was accomplished, and then the library contact/location information, library information, collection information, and event information was proposed. The metadata for LMIS was organized into four sectors and then 49 elements, each assigned to a sector.

초록

Abstract

Even though the overall scholarly community has recognized a dramatic growth and changes in the Information Science research in Korea over the last few decades, there are still only few studies that have identified the changes in terms of long-term and dynamic point of view. We have analyzed 1,007 IS-research articles from leading Korean journals in KCI (Korea Citation Index), published between 2000 and 2011. To discern the trendline of changes in research interests over time, we conducted a time-series analysis by developing grounded subject scheme from the article set and checking the growth rate of the number of published articles and title keywords. A comparative analysis was also conducted by constructing and comparing co-word maps over time to discover visible changes in research topics over this 12-year period of the IS-research in Korea. As a result, we identified some developments and transformations in major subject areas and knowledge structure of the IS-research in Korea over time. The major trend we discovered is that IS-studies over the 12-year period evolved from system-oriented research to library-application research. The changes are especially observed in knowledge management, Web-based system evaluation, and information retrieval areas. When compared to the results of other studies, the result of our study may serve as an evidence of the localization of Korean IS-studies in the first decade of the 21st century.

초록

다양한 매체와 유형으로 생산되는 정보자원에 대한 이용이 높아짐에 따라, 정보자원을 기술하기 위한 정보조직의 도구로서 메타데이터에 대한 중요성이 높아지고 있다. 본 연구에서는 메타데이터 분야의 연구 영역을 파악할 수 있도록 동시출현단어 분석을 사용하여 메타데이터 분야의 지적 구조를 규명하고자 하였다. 이를 위하여 1998년 1월 1일부터 2016년 7월 8일까지 Web of Science 핵심컬렉션에 등재된 저널에 게재된 문헌을 대상으로 ‘metadata’라는 질의어로 Topic 검색을 수행하여, 총 727건의 논문에 대한 서지정보를 수집하였다. 이 중 저자 키워드를 가진 410건의 논문의 저자 키워드로 수집하고, 전처리 과정을 거쳐 저자 키워드 총 1,137개를 추출하여 최종적으로 빈도수 6회 이상의 키워드 37개를 분석대상으로 선정하였다. 이후 메타데이터 분야의 지적구조 규명을 위해 첫째, 네트워크 분석을 통하여 2개 영역 9개 군집을 도출하였으며, 메타데이터 분야 키워드들의 지적 관계를 시각화하고, 중심성 분석을 통한 전역 중심 키워드와 지역 중심이 높은 키워드를 제시하였다. 둘째, 군집분석을 실시하여 형성된 6개의 군집을 다차원축적지도상에 표시하였으며, 각 키워드들 간의 상관관계에 따른 지적구조를 제시하였다. 이러한 연구의 결과는 메타데이터 분야의 지적구조를 시각적으로 파악할 수 있게 하며, 향후 메타데이터 관련 교육과 연구의 방향성 모색에 유용하게 사용될 수 있을 것이다.

Abstract

As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word ‘metadata’. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.