• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.279-301
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• 2023

The data-driven research environment is rapidly changing. Accordingly, domestic university libraries are also preparing to establish and operate research data management services to support university researchers. This study was designed to propose a research data management service to support researchers in science and technology specialized university libraries. In order to propose the service, 11 universities specializing in science and technology were selected from overseas and domestic universities and their research data management services were analyzed. Key categories were derived from analysis results, research data management, electronic research notebooks, and RDM training. In particular, the 'research data management' category included DMP, data collection, data management, data preservation, data sharing and publishing, data reuse, infrastructure and tools. And it consists of RDM guides and policies. The results of this study will be helpful in introducing and operating research data management services in science and technology specialized university libraries.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.73-84
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• 2019

Machine learning as a service, the so-called MLaaS, has recently attracted much attention in almost all industries and research groups. The main reason for this is that you do not need network servers, storage, or even data scientists, except for the data itself, to build a productive service model. However, machine learning is often very difficult for most developers, especially in traditional science due to the lack of well-structured big data for scientific data. For experiment or application researchers, the results of an experiment are rarely shared with other researchers, so creating big data in specific research areas is also a big challenge. In this paper, we introduce the KISTI-ML platform, a community-based rapid AI model development for scientific data. It is a place where machine learning beginners use their own data to automatically generate code by providing a user-friendly online development environment. Users can share datasets and their Jupyter interactive notebooks among authorized community members, including know-how such as data preprocessing to extract features, hidden network design, and other engineering techniques.

• Journal of Korean Elementary Science Education
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• v.23 no.1
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• pp.50-60
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• 2004

The purpose of this study was to define teachers' learning motivation strategies and students' responses by analyzing science classes and interviews. The subjects were first grade and sixth grade teachers and students of an elementary school. The analysis tools are based on Keller's ARCS theory. The differences of teachers' motivation strategies were analyzed by grades and teachers' and students' backgrounds. The interviewers were composed of three teachers and three students of first grade, and three teachers and three students of sixth grade. The data were collected by recording of the classes using tape recorders, video cameras, and notebooks written by researchers. The results are as follows. First, teachers had their own styles of teaching strategies in their classes. Especially teachers' teaching backgrounds affected on the teachers' instructional strategies. The teachers who had long teaching experiences of lower grade students used to show a lot of attention strategies. While the teachers with long teaching experiences of higher grade students used to show few learning motivation strategies. Especially, sixth grade teachers used to show fewer confidence strategies than first grade teachers. Second, all of the teachers used to show few satisfaction strategies commonly in all the classes observed. Third, the students' recognition of the motivation strategies were not different according to their conceptions or activities of the classes. Commonly first grade students focused on the attention strategies, while sixth grade students focused on negative motivation strategies. Fourth, the teachers who believed that students need detail guidance and control recognized the needs of satisfaction strategies by students' autonomous activities after observing video tapes of other teachers' classes.