No abstract

In this study, we analysed the statistical association between e-journal use and research output at the institution level in South Korea by performing comparative and diachronic analyses, as well as the analysis by field. The datasets were compiled from four different sources: national reports on research output indicators in science fields, two statistics databases on higher education institutions open to the public, and e-journal usage statistics generated by 47 major publishers. Due to the different data sources utilized, a considerable number of missing values appeared in our datasets and various mapping issues required corrections prior to the analysis. Two techniques for handling missing data were applied and the impact of each technique was discussed. In order to compile the institutional data by field, journals were first mapped, and then the statistics were summarized according to subject field. We observed that e-journal use exhibited stronger correlations with the number of publications and the times cited, in contrast to the number of undergraduates, graduates, faculty members and the amount of research funds, and this was the case regardless of the NA handling method or author type. The difference between the maximum correlation for the amount of external research funding with two average indicators and that of the correlation for e-journal use were not significant. Statistically, the accountability of e-journal use for the average times cited per article and the average JIF was quite similar with external research funds. It was found that the number of e-journal articles used had a strong positive correlation (Pearson’s correlation coefficients of r > 0.9, p < 0.05) with the number of articles published in SCI(E) journals and the times cited regardless of the author type, NA handling method or time period. We also observed that the top-five institutions in South Korea, with respect to the number of publications in SCI(E) journals, were generally across a balanced range of academic activities, while producing significant research output and using published material. Finally, we confirmed that the association of e-journal use with the two quantitative research indicators is strongly positive, even for the analyses by field, with the exception of the Arts and Humanities.

Citing literature is a very important activity for scholars in writing articles. Many publishers and libraries build citation databases and provide citation reports on scholarly journals. Cited-by linking is a service representing what an article cites and how many times it cites a specific article within a journal database. Recently, information services based on DOIs (Digital Object Identifiers) have been increasing in number. CrossRef, a non-profit organization for the DOI registration agency, maintains the DOI system and provides the cited-by linking service. Recently, the number of Korean journals adopting DOI is also rapidly increasing. The Korea Institute of Science and Technology Information (KISTI) supports Korean learned societies in DOI related activities in collaboration with CrossRef. This study analyzes cited patterns of Korean DOI journal articles using CrossRef's cited-by linking data and a Korean journal citation database. This analysis has been performed in terms of publication country and the language of journals citing Korean journal articles. The results show that DOI, SCI(E) (Science Citation Index (Expanded)), and English journals are more likely to be cited internationally

Today, citation index information is used as an outcome scale of spreading technology and encouraging research. Article citation information is an important factor to determine the authority of the relevant author. Google Scholar uses the article citation information to organize academic article search results with a rank algorithm. For an accurate analysis of such important citation index information, large amounts of bibliographic data are required. Therefore, this study aims to build a fast and efficient system for large amounts of bibliographic data, and to design and develop a system for quickly analyzing cited information for that data. This study also aims to use and analyze citation data to be a basic element for providing various advanced services to the academic article search system

Through a series of precise text handling processes, including automatic extraction of information from documents with knowledge from various fields, recognition of entity names, detection of core topics, analysis of the relations between the extracted information and topics, and automatic inference of new knowledge, the most efficient knowledge base of the relevant field is created, and plans to apply these to the information knowledge management and service are the core requirements necessary for intellectualization of information. In this paper, the knowledge base, which is a necessary core resource and comprehensive technology for intellectualization of science and technology information, is described and the usability of academic information services using it is evaluated. The knowledge base proposed in this article is an amalgamation of information expression and knowledge storage, composed of identifying code systems from terms to documents, by integrating terminologies, word intelligent networks, topic networks, classification systems, and authority data