• Journal of KIISE:Databases
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• v.31 no.2
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• pp.174-182
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• 2004

In order to produce information the author usually reference other authors' work. A citation index leads users to papers by citations. Citations lead the user to desired information. In this paper, KSCI(Korea Science Citation Index) which defines the relationships between citing documents and cited documents has been constructed. KSCI System is to solve problems for recursive retrieval in ISI's SCI(Science Citation Index) Path Encoding Indexing technique was used to solve the problems. From the analysis of data, this system has efficiency about 8.98% in the aspect of data storage. In the aspect of retrieval, there was efficiency between citing documents and cited documents, especially there was over 40% of efficiency in the retrieval of cited documents. It is concluded that suggested KSCI system will provide efficient storage and retrieval system.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.65-80
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• 2013

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.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.4
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• pp.271-289
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• 2004

In this study, we analyze out citing and cited references among researchers, using KSCI (Korean Science Citation Index) database that is developed by KISTI. we generate and analyze that impact factor and immediate index with same method in JCR's. KSCI's impact factor and immediate index compared to JCR's, and with this basis, this study propose the need of development KSCI database and present new service model for evaluate of domestic journals.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.283-308
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• 2008

In this study, we testify that network structural attributes of a citation network can explain other aspects of journal citation behaviors and the importances of journals. And we also testify various citation impact indicators of journals including JIF and h-index to verify the difference among them especially focused on their ability to explain an institution's local features of citation behaviors. An institutional citation network is derived using the articles published in 2006-2007 by biotechnology faculties of Y University. And various journal citation impact indicators including JIF, SJR, h-index, EigenFactor, JII are gathered from different service sites such as Web of Science, SCImago, EigenFactor.com, Journal-Ranking.com. As a results, we can explain the institution's 5 research domains with inter-citation network. And we find that the co-citation network structural features can show explanations on the patterns of institutional journal citation behavior different from the simple cited frequency of the institution or patterns based on general citation indicators. Also We find that journal ranks with various citation indicators have differences and it implies that total-based indices, average-based indices, and hybrid index(h-index) explain different aspects of journal citation pattern. We also reveal that the coverage of citation DB doesn't be a matter in the journal ranking. Analyzing the citation networks derived from an institution's research outputs can be a useful and effective method in developing several library services.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.189-207
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• 2016

Sharing and reutilizing of research data could not only enhance efficiency and transparency of research process, but also create new science through data integrating and reinterpretationing. Diverse policies about research data sharing and reutilizing have been developing, along with extending of research evaluating spectrum that across research data citation rate to social impact of research output. This study analyzed the scale and citation number of research data which has not been analyzed before in korea through data citation index using Kruskal-Wallis H analysis. As result, genetics and biotechnology are identified as subject areas which have most huge number of research data, however the subject areas that have been highly cited are identified as economics and social study such as, demographic and employment. And Uk Data Archive, Inter-university Consortium for Political and Social Research are analyzed as data repositories which have most highly cited research data. And the data study which describes methodology of data survey, type and so on shows high citation rate than other data type. In the result of altmetrics of research data, data study of social science shows relatively high impact than other areas.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.77-94
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• 2002

In this study we analyze the present situation of cited and citing references among researchers, based on Korean Science Citation Index developed by Korea Institute of Science & Technology Information. There are some differences on the rank of frequently cited journals between JCR of ISI and KSCI, especially in the field of mechanical engineering. The purpose of this study is to find an efficient way of constructing KSCI database and to propose a service model which can be available as a tool to evaluate research activities and to provide researcher with basic information resources.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.7-29
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• 2017

Data citation remains in its infancy, although providing the citation to a journal article is a typical norm in an academic community. This study examines the need for data citation, its principles and guidelines for improving the issue. In addition, the study investigates cases that established data citation mechanism, including DataCite, Dataverse Network and Data Citation Index that define elements of data citation and provide relevant services. At the end, it explores the current state of data citation in Korea through the analysis of citations to dataset from Korean General Social Survey.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.205-221
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• 2015

The impact of a journal is commonly used as the impact of an individual paper within that journal. It is problematic to interpret a journal's impact as a single paper's impact of the journal, so there are several researches to measure a single paper's impact with its own citation counts. This study applied 8 impact indicators to Korean Citation Index database and examined discipline bias of each indicator. Analyzed indicators are simple citation counts, PageRank, f-value, CCI, c-index, single publication h-index, single publication hs-index, and cl-index. PageRank has the least discipline bias at highly ranked papers and journal bias in a discipline. On the contrary, simple citation counts showed strongly biased results toward a certain discipline or a journal. KCI database provides only simple citation counts. It needs to show PageRank (global indicator) to discover influential papers in diverse areas. Furthermore it needs to consider to provide the best of local indicators. Local indicators can be calculated only with papers in users' search results because they uses citation counts of citing papers and the number of references. They are more efficient than global indicators which explore the whole database. KCI should also consider to provide Cl-index (local indicator).

• Journal of Information Management
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• v.36 no.3
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• pp.183-193
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• 2005

Korean Academy of Medical Sciences began developing Korean Medical Citaton Index(KoMCI) database in 2002, and has announced the impact factors of Korean medical journals published since 2000. In July 2005, Korea Research Foundation also announced the KCI impact factor of journals covering all subject areas for the 2003 and 2004. We compared the impact factor(IF), impact factor excluding self-citation(ZIF), and self-citation impact factor(SIF) of KoMCI 2004 and KCI 2004 in order to disclose why there is such a great difference in the values of impact factors between two databases. Out of 72 medical journals in both database, 59 journals were compared after excluding the missing data in KCI. Mean IF of KoMCI 2004 was 0.2 and that of KCI 2004 was 0.03(p=0.0000). Mean ZIF of KoMCI was 0.06 and that of KCI was 0.01(p=0.000). Mean SIF of KoMCI was 0.139 and that of KCI was 0.02(p=0.0000). We presumed that the major difference in the impact factor values was originated from the fact that KCI does not control the authority of journal names cited in the references. We strongly recommend that it is necessary to control the authority especially if Korea Research Foundation wants to ensure the validity and reliability of KCI data in the evaluation of korean journals.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.119-143
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• 2011

This study identifies the characteristics of recent citation-based indicators for assessing a single paper in the context of their co-relationships. Five predefined indicators were examined with three variants of h-index which are convened in this study; the formers are PageRank, SCEAS Rank, CCI, f-value, and single paper h-index and the latters are $h_S$-index, h1-index, and $h_S$1-index. The correlation analysis and cluster analysis were performed to group the indicators by common characteristics, after which the indicators were calculated with the dataset from KSCI DB. The results show statistical evidence that distinguishes h-index type indicators from others. The characteristics of the indicators were verified with citation frequency factors using correlation analysis. Finally, the implications for applications and further studies are discussed.