• Journal of Digital Contents Society
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• v.19 no.1
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• pp.1-10
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• 2018

This study is to seek to find the importance of next digital marketing factors by using AHP method and analyze comparison between an advertising expert and a non-advertising expert. In results, the relative importance ranking is as follows; combination (0.26), transformation (0.259), optimization (0.243), and technology (0.238). The relative importance ranking of sub-factors is as follows: artificial intelligence and maching learning (0.086), big data (0.085), and contents curation (0.060). While the relative importance of combination and optimization for an advertising expert is higher than for non-advertising expert, the relative importance of transformation and technology for non-advertising is higher than for an advertising expert. This study provides managerial implication to build digital strategy based on these result.

• Informatization Policy
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• v.28 no.4
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• pp.3-18
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• 2021

The 'digital divide' is regarded as a latent dysfunction that impedes the intrinsic role of information to contribute to social equality. Therefore, it has drawn great attention inside and outside of academia. The growing interest in the digital divide has been driven by the realization that it can create a serious crisis that threatens a social system compounded by existing economic, social, and cultural inequality, rather than being limited to an uneven distribution of information. In this paper (1) studies on the digital divide published since 1970 are reviewed, (2) studies noteworthy of discussion are selected to assess their academic significance, and (3) the tasks and prospects of digital divide research are explored. Although meaningful achievements have been amassed through continuous interest and efforts of the academic community, two limitations are raised; the gap between pure research and policy research that hinders the working of synthetic imagination, and the intellectual lag falling behind a rapidly changing society. In addition, it is suggested that the operation, curation, and augmentation gaps would emerge as new agenda for digital divide research in the intelligent information age.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.3
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• pp.129-150
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• 2015

As the digital technologies and internet have advanced, data have centered in the process of meaningful scientific ramifications and policy making in a wide variety of fields. Data curator in charge of managing data plays a significant role in terms of improving the effectiveness and efficiency of data management and re-uses. The purpose of this study is to identify the core competencies for data curator. For achieving the purpose of this study, two sets of data were collected. First, a total of 255 job descriptions were collected from the web sites including ARL, Digital Curation Exchange, Code4lib, ASIS&T JobLine for the period of 2011-2014. Second, in-depth interviews with five data curators from four diverse organizations were collected. The two sets of data were analyzed into seven categories identified from the related studies. Findings of this study showed that core competencies for data curator were identified into four categories, communication skills, data management techniques, knowledge and strategies for data management, and instructions and service provisions for users. The implications of this study can be considered as integrated and professional curriculum developments for data curator with core competencies.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.98-103
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• 2023

As technology advanced dramatically in the late 20th century, a new era of science arrived. The emerging era of scientific discovery, variously described as e-Science, cyberscience, and the fourth paradigm, uses technologies required for computation, data curation, analysis, and visualization. The emergence of the fourth research paradigm will have such a huge impact that it will shake the foundations of science, and will also have a huge impact on the role of data-information infrastructure. In the digital age, the roles of data-information professionals are becoming more diverse. As eScience emerges as a sustainable and growing part of research, data-information professionals and centeres are exploring new roles to address the issues that arise from new forms of research. The functions that data-information professionals and centeres can fundamentally provide in the e-Science area are data curation, preservation, access, and metadata. Basically, it involves discovering and using available technical infrastructure and tools, finding relevant data, establishing a data management plan, and developing tools to support research. A further advanced service is archiving and curating relevant data for long-term preservation and integration of datasets and providing curating and data management services as part of a data management plan. Adaptation and change to the new information environment of the 21st century require strong and future-responsive leadership. There is a strong need to effectively respond to future challenges by exploring the role and function of data-information professionals in the future environment. Understanding what types of data-information professionals and skills will be needed in the future is essential to developing the talent that will lead the transformation. The new values and roles of data-information professionals and centers for 21st century researchers in STEAM are discussed.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.2
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• pp.191-220
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• 2018

Using Bloom's taxonomy model of thinking ability for learning (RBTT) and new ACRL information literacy framework (2016), this study demonstrates the meta-literacy competencies for library specialists and analyses current LIS curriculum of higher education. Some guidelines for reformation of LIS curriculum, emphasizing meta-literacy competencies which are required from Web3.0 information environment, are provided.

• Journal of Fashion Business
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• v.26 no.2
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• pp.28-47
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• 2022

Rapid development of information and communication technology is leading the digital transformation (hereinafter, DT) of various industries. At this point in rapid online transition, fashion manufacturers operating offline-oriented businesses have become highly interested in DT and artificial intelligence (hereinafter AI), which leads DT. The purpose of this study is to examine the development status and application case of AI-based digital technology developed for the fashion industry, and to examine the DT stage and AI application status of domestic fashion manufacturers. Hence, in-depth interviews were conducted with five domestic IT companies developing AI technology for the fashion industry and six domestic fashion manufacturers applying AI technology. After analyzing interviews, study results were as follows: The seven major AI technologies leading the DT of the fashion industry were fashion image recognition, trend analysis, prediction & visualization, automated fashion design generation, demand forecast & optimizing inventory, optimizing logistics, curation, and ad-tech. It was found that domestic fashion manufacturers were striving for innovative changes through DT although the DT stage varied from company to company. This study is of academic significance as it organized technologies specialized in fashion business by analyzing AI-based digitization element technologies that lead DT in the fashion industry. It is also expected to serve as basic study when DT and AI technology development are applied to the fashion field so that traditional domestic fashion manufacturers showing low growth can rise again.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.107-128
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• 2019

This study examines cases of digital humanities education programs at universities, university libraries and digital humanities centers in the United States. As a result of the research, it was analyzed that the university-centered education program operates in conjunction with other departments to take courses related to humanities and digital technology in general. The digital humanities education program is not operated as a full degree program, but most programs are operated as graduate certificate programs, and it is required to require a graduate degree in library and information science and humanities in advance. Most of the digital humanities centers run educational programs centered on faculty and postdoctoral researchers in universities in connection with universities and university libraries to support the humanities scholars. Lastly, the university's digital humanities education program is operated in the form of research support for students and researchers of all majors. In addition, the content of the educational program focused on the practice for digital projects rather than theory. Empowering digital literacy and supporting digital technology-based research has become a new role for university libraries, which requires libraries to play a central role in digital humanities education.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.154-162
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• 2019

Despite the development of information and communication technology, which has a great impact on society and culture, there is no platform that provides a systematic classification and state-of-the-art information retrieval system on the traditional culture. Therefore, this paper developed a traditional culture retrieval system capable of convergence services with systematic classification and retrieval based on automatically generate and visualize the 3D timeline. This system provides the function of collecting traditional culture contents, classifying and storing collected traditional culture contents, and automatically generating 3D digital timeline based on stored traditional culture contents. In addition, a system satisfaction questionnaire was developed to evaluate the usability of the system, and 19 students participated in verifying the system. As a result of the experiment, the satisfaction of the system showed that all items were 'satisfied' on average.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.51-58
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• 2013

Camera performance of smartphone recently has been developed as much as the digital camera. Interest in applications As a result, many people take pictures and the number of people who are interested in application according to photos has been steadily increasing. However, there are only synthesis programs which are arraying some photos, overlapping multiple images. The model proposed in this paper, base on the emotion that is extracted from the facial expressions by combining the background and applying effects filters. And it can be also utilized in various fields more than any other synthesis programs.

• Physical Therapy Korea
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• v.28 no.3
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• pp.177-185
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• 2021

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.