• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.63-100
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• 2013

Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. Scientific research is changing because of the paradigm shift. It is all being affected by the data deluge, and a data-intensive science paradigm is emerging. Hence, paradigm shift in scientific research led to increase of value and importance of scientific data. Essential to the creative research and development for scientific data can be reused efficiently is the sharing and utilization of establishing management system. Establishing of management system for sharing and utilization of scientific data should be done at the national level, but compared with Europe, Australia, the United States, China, the management system of Korea doesn't have not linkage or efficiency or internal stability. Australia, the United States, China continues to expand a Mid- and Long-Term policy making, legislation, its investment in infrastructure, so as to promote the utilization of data, such as collection, management and maintenance of scientific data through the relevant agencies at the national level. This study consider legislation cases and management policies of the above countries to the end to that establish management system for the efficient and fair sharing and utilization of scientific data and the legal system, and that provide scientific data legislation and policies related to the future of our country.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.4
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• pp.81-93
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• 2010

This study is to suggest a model for preservation and circulation of scientific data as Records. Analysis for national trends in U.S., British, Australia, Europe about scientific data was performed. Foreign advanced programs on management of scientific data were surveyed and analyzed. The analyzed programs were DataCite, WDS, PANGAEA, Dataverse, BSRN, DLESE, GCMD and SEDIS. Common implications were deducted from each program. With the results of analyzing the programs, this study proposed a model for preservation and circulation of scientific data.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.117-135
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• 2019

Data journals and data papers have grown and considered an important scholarly practice in the paradigm of open science in the context of data sharing and data reuse. This study investigates a total of 713 data papers published in Scientific Data in terms of author, citation, and subject areas. The findings of the study show that the subject areas of core authors are found as the areas of Biotechnology and Physics. An average number of co-authors is 12 and the patterns of co-authorship are recognized as several closed sub-networks. In terms of citation status, the subject areas of cited publications are highly similar to the areas of data paper authors. However, the citation analysis indicates that there are considerable citations on the journals specialized on methodology. The network with authors' keywords identifies more detailed areas such as marine ecology, cancer, genome, database, and temperature. This result indicates that biology oriented-subjects are primary areas in the journal although Scientific Data is categorized in multidisciplinary science in Web of Science database.

• Genomics & Informatics
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• v.18 no.2
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• pp.14.1-14.11
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• 2020

Phenotyping is a major issue for wheat agriculture to meet the challenges of adaptation of wheat varieties to climate change and chemical input reduction in crop. The need to improve the reuse of observations and experimental data has led to the creation of reference ontologies to standardize descriptions of phenotypes and to facilitate their comparison. The scientific literature is largely under-exploited, although extremely rich in phenotype descriptions associated with cultivars and genetic information. In this paper we propose the Wheat Trait Ontology (WTO) that is suitable for the extraction and management of scientific information from scientific papers, and its combination with data from genomic and experimental databases. We describe the principles of WTO construction and show examples of WTO use for the extraction and management of phenotype descriptions obtained from scientific documents.

• Food Science and Industry
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• v.51 no.3
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• pp.218-228
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• 2018

The government should establish internationally harmonious regulations for effective import and export of necessary resources to other countries. However, the use and the number of pesticides used for the same purpose on same crops are depending on the soil and the climate where the crops are grown. Therefore, if internationally harmonized standards are difficult to establish, it is mandatory to conduct a risk assessment based on scientific data to reflect the domestic situation in order to avoid trade friction or conflict between countries. The government is preparing the implementation of a more regulated PLS (positive list systme) than the existing pesticide management system for safer pesticide management reflecting the recent increasing imported food, changing dietary habits, and changing climate. In order for effectively safe and scientific management of pesticides, the government should strive to communicate with consumers properly and the perception of pesticides by consumers should also be changed.

• Journal of Information Management
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• v.42 no.3
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• pp.55-69
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• 2011

In the modern scientific R&D, the efficient acquisition, curation, analysis and visualization are core elements of the science development. The value of scientific data is very important in data intensive research. An output of scientific data is drastically increasing. However we have only each individual system of scientific data in now. Therefore We feel a lack of efficiency of scientific data. In this paper, We analyze an economic ripple effects in terms of production inducement effect, added value inducement effect, labor inducement effect and forward backward linkage effect of national scientific data center construction using an input-out analysis of the bank of Korea(2009). We also examine an economic propriety of national scientific data center construction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• Journal of Information Management
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• v.42 no.2
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• pp.85-102
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• 2011

Conventionally, scientific data visualization is thought of as one of activities performed by scientists during the scientific data analysis. However, recently, there exits a set of research papers which count scientific data visualization as a independent research area. They show the research subjects for studying the scientific data visualization technology and methods. In case, a scientist or group of scientists can not solve their own visualization problem due to the unskillfulness and inexperience on using visualization tool. Therefore, it needs to help them by the systematic way for solving the problem. In this study, we analyze and propose the national level scientific visualization support system for scientists. In particular, we first analyze the existing papers and find out the critical success factors. Then, by integrating the findings of the analysis, we propose the research areas which need to be focused, and the strategic direction and specific research topics for scientific data visualization support system in national level.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.153-164
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• 2005

The paper presents time and cost effective remote sensing technology to estimate recharge potential of fresh water shallow aquifers for their sustainable management in arid ecosystem. Precipitation measurement of Raudatain Basin in Kuwait from TRMM data has been made and integrated with geological, geomorphological and hyrological data, to estimate the recharge potential of the basin. The total potential recharge to the area is estimated as 333.964 MCM annually. The initial losses are estimated at $60\%$ of the net precipitation .The net available quantity for recharge is 133.58 MCM. For sustainable management of the ground water resources, recharge wells have been proposed in the higher order streams to augment the Raudatain aquifer in Kuwait. If the available quantity of precipitation can be successfully utilized, it will reduce considerable pressure on desalination, which is leading to increased salinity off the coast in Arabian Gulf.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.25-32
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• 2020

Data on patent and scientific paper is considered as a useful information source for analyzing technological information and has been widely utilized. Technology big data is analyzed in various ways to identify the latest technological trends and predict future promising technologies. Clustering is one of the ways to discover new features by creating groups from technology big data. Patent includes refined bibliographic information such as patent classification code whereas scientific paper does not have appropriate bibliographic information for clustering. This research proposes a new approach for clustering data of scientific paper by utilizing reference titles in each scientific paper. In this approach, the reference titles are considered as textual information because each reference consists of the title of the paper that represents the core content of the paper. We collected the scientific paper data, extracted the title of the reference, and conducted clustering by measuring the text-based similarity. The results from the proposed approach are compared with the results using existing methodologies that one is the approach utilizing textual information from titles and abstracts and the other one is a citation-based approach. The suggested approach in this paper shows statistically significant difference compared to the existing approaches and it shows better clustering performance. The proposed approach will be considered as a useful method for clustering scientific papers.