• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.3
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• pp.235-256
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• 2020

The purpose of this study is to define a method of building an integrated service to provide various science and technology knowledge infrastructures that are helpful in R&D activities, and to show the cases that are adapted the methodologies. Knowledge infrastructures scattered throughout the entire R&D cycle, such as generating/development of ideas, finding the R&D project, performing the project, and spreading results, are segmented in terms of services, functions, information, and data, and links and converges to provide the knowledge infrastructure that desired by users in one place. We define the integrated service classification, integration level model, integrated architecture, and integrated user authentication system in consideration of logical linkage and integration rather than physical integration of individual knowledge infrastructures. Also, we considered the extensibility as the reference model for building of similar integrated service.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.45-59
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• 2021

As software(SW) has been considered as a key driver of the fourth industrial revolution, significant R&D investment has been made by Korean government. Despite the attention and support by the government, systematic analysis on the SW R&D efficiency has not been fully addressed. In this study, the efficiency of SW national research and development projects was analyzed using Data Envelopment Analysis(DEA) techniques. Efficiency was measured from both static and dynamic perspectives based on 1,463 projects conducted by the National IT Industry Promotion Agency(NIPA) from 2008 to 2018. The static efficiency analysis identified the causes of inefficiency as scale and technology problems. As a result of dynamic efficiency analysis, we present a sector-specific response model using an efficiency-stability matrix. This study is meaningful in that efficiency analysis was conducted on the entire SW national R&D project, and static/dynamic efficiency analysis results are expected to be used as a guideline for planning SW national R&D project.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.266-287
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• 1997

The purpose of this paper is to purpose methods and procedures by which we can set up technology planning scheme essential for R'||'&'||'D(or technology) planning in public sector (governmental and government-sponsored institutions), and can develop and select "main R'||'&'||'D projects" which are crucial to R'||'&'||'D planning, were quite specifically discussed in case of I'||'&'||'T(Information '||'&'||' Telecommunications) sector, so that they may not remain theoretical but may be practically applicable to real R'||'&'||'D programs. In this paper, the concept of technology planning was defined as a procedure for establishing nominal planning to acquire technologies efficiently for a specific sector. More detailed definition optimal technology-acquisition strategy, i.e., analyzing technological development '||'&'||' environ-ment, establishing R'||'&'||'D objectives as promising technology opportunities, selecting main R'||'&'||'D projects, allocating resources and so on."The"main R'||'&'||'D projects by technology sectors and by planning phases and then deciding on priority. Scoring method was rsed in assessment phase. Summing up, this paper suggested technology planning scheme of methods and procedures for sorting out required technologies, developing and assessing public R'||'&'||'D projects, and finally selecting main R'||'&'||'D projects.

• Journal of Technology Innovation
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• v.14 no.2
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• pp.93-116
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• 2006

The purpose of this study is to contribute reference material that provides insight into innovative process management that increases R&D output in commercializing new products. A model of a process from research to commercialization with the cumulative profit and loss curve is put forward and hypotheses related to success and failure are developed at the stages up to product launch. Seventeen large projects that have resulted in successful product launches have been examined from the initial research stage to commercialization. Prefect duration, standardized cumulative R&D expenditures and research resource concentration are analyzed in terms of statistical method and patterns in cumulative profit and loss curves after product sales, as well as the reasons for and other aspects of success/failure are investigated and analyzed. Consequently, valuable information on future management tasks has been obtained such as: (1) project duration differs depending on market sectors, product types and presence/absence of materials research (2) cumulative profit and loss curves can be categorized into four patterns (3) reasons for failure can be divided into technological and market problem categories and (4) these factors have an impact on product sales.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.115-125
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• 2018

In order to examine the ways to improve the efficiency of R&D investment, this paper presents analysis on both quantitative and qualitative efficiency of R&D projects. As Korea's R&D investment has significantly increased in recent years, the efficiency of R&D investment has attracted attention. In this paper, a Data Envelopment Analysis(DEA) method is used to construct models for quantitative efficiency and qualitative efficiency analysis. Based on a cases of agricultural R&D projects of Korea, the efficiency of national R&D projects were analyzed and their quantitative and qualitative efficiencies are compared. As a result, statistically significant difference between quantitative and qualitative efficiency was found. Also, characteristics of Decision Making Units(DMUs) which can influence both quantitative and qualitative efficiency were identified. In particular, the stage of a R&D project has significant impact on R&D efficiency. This study suggests that in order to enhance R&D efficiency both quantitative and qualitative nature of outputs should be considered when measuring R&D efficiency.

• Journal of Information Management
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• v.43 no.3
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• pp.43-59
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• 2012

We established economic models for economic performance analysis in order to respond to changes in a rapidly changing environment. We tried to maximize business efficiency and performance of science and technology information management distribution project. The science and technology information management distribution project is significantly different from general R&D project. In this paper, it is meaningful to develop economic models to analyze economic outcomes for science and technology information management distribution project. We anticipate that these models will contribute greatly to economic performance analysis for science and technology information management distribution project.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.83-95
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• 2019

It is becoming more and more difficult to cope with new knowledge and technology required by society by the efforts of one person or organization according to the development of science and technology. As a method to overcome this, collaborative research is becoming important. This tendency is increasing in the government R&D projects as well, and the 'A' test research institute, which is the subject of this paper, is also increasing a collaborative research. The purpose of this study is to analyze the network characteristics among the participating researchers in the government R&D project conducted by the institution A, and to ascertain how the network characters of the researchers actually affect the financial performance of the team. The results of the analysis show that 'closeness centrality' and 'degree of centrality' contribute positively to the financial performance of the team. On the other hand, 'betweenness centrality' and 'eigenvector centrality' have a negative effect on the financial performance of the team because they are not directly related to financial performance.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.28-37
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• 2019

Various fields are being combined and developed for the development of the country and industry. The purpose of this study is to examine the effects of interdisciplinary research on the technology commercialization of researchers in the national R&D project. For the purpose of empirical analysis, major research and development have been reviewed. Major research and development projects conducted by government-funded research institution in which various technological fields are integrated in order to commercialize technology. The research data is based on the major R&D project data for railway/public transportation/logistics fields technology in 2015-17, and 149 project were selected for analysis. As a result, it was found that diversity of participants' experts had significant positive effect on technology commercialization when R&D expense, The number of research participants, The number of participating organizations, TRL before R&D were controlled. It is expected that the results of this study will be used meaningfully when the R&D program plan, analysing the academic convergence factor of research topic.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.12-24
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• 2022

This study attempted to investigate changes in collaboration structure for each stage of national Research and Development (R&D) in the artificial intelligence (AI) field through analysis of a co-author network for papers written under national R&D projects. For this, author information was extracted from national R&D outcomes in AI from 2014 to 2019. For such R&D outcomes, NTIS (National Science & Technology Information Service) information from the KISTI (Korea Institute of Science and Technology Information) was utilized. In research collaboration in AI, power function structure, in which research efforts are led by some influential researchers, is found. In other words, less than 30 percent is linked to the largest cluster, and a segmented network pattern in which small groups are primarily developed is observed. This means a large research group with high connectivity and a small group are connected with each other, and a sporadic link is found. However, the largest cluster grew larger and denser over time, which means that as research became more intensified, new researchers joined a mainstream network, expanding a scope of collaboration. Such research intensification has expanded the scale of a collaborative researcher group and increased the number of large studies. Instead of maintaining conventional collaborative relationships, in addition, the number of new researchers has risen, forming new relationships over time.