• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.71-111
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• 2014

Metadata schemas are well recognized as one of the important technological components for archiving and preservation of digital resources. However, a single standard is not enough to cover the whole lifecycle for archiving and preserving digital resources. This means that we need to appropriately select metadata standards and combine them to develop metadata schemas to cover the whole lifecycle of resources (or records). Creating a unified framework to understand the features of metadata standards is necessary in order to improve metadata interoperability that covers the whole resource lifecycle. In this study, the author approached this issue from the task-centric view of metadata, proposing a Task model as a framework and analyzing the feature of archival metadata standards. The proposed model provides a new scheme to create metadata element mappings and to make metadata interoperable. From this study, the author found out that no single metadata standard can cover the whole lifecycle and also that an in-depth analysis of mappings between metadata standards in accordance with the lifecycle stages is required. The author also discovered that most metadata standards are primarily resource-centric and the different tasks in the resource lifecycle are not reflected in the design of metadata standard data models.

• Asian Journal of Innovation and Policy
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• v.9 no.3
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• pp.308-338
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• 2020

The entrepreneurial journey is not short of challenges, and about 90% + tech start-ups experience failure (Startup Genome, 2019). The magnitude of the challenges varies across the tech start-up lifecycle stages, namely emergence, stability, and growth. This opens the research question, do the profiles of a start-up and its co-founder impact start-up success or failure across its lifecycle stages? This study aims to understand and identify the profiles of tech start-ups and their co-founders. We gathered primary data from 151 start-ups (Status: 101 failed and 50 successful ones), and they are across different lifecycle stages and represent six major start-up hubs in India. The chi-square test on status and start-up's lifecycle stage indicates a noticeable correlation, and they are not independent. The Kruskal Wallis test was used to distinguish statistically significant profile attributes. The parameters distinguishing success and failure are identified, and the need to deliver customer experience is emphasized by the start-up profile attributes: Product/service, high-tech nature of a start-up, investor fund availed, co-founder experience, and employee count. The importance of entrepreneurial experience is ascertained with entrepreneur profile attributes: Entrepreneurial expertise, the number of prior and current start-ups, their willingness to start again in the event of failure, and age of co-founder, which is a proxy to learning and experience. This study has implications for entrepreneurs, investors, and policymakers.

• International Journal of CAD/CAM
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• v.11 no.1
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• pp.1-10
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• 2011

Product lifecycle management (PLM) is a new business strategy for enterprise's product R&D. A PLM system holds and maintaining the integrity of the product data produced throughout its entire lifecycle. There is, therefore, a need to build a safe and effective product data model to support PLM system. The paper proposes a domain-based product data model for PLM. The domain modeling method is introduced, including the domain concept and its defining standard along the product evolution process. The product data model in every domain is explained, and the mapping rules among these models are discussed. Mapped successively among these models, product data can be successfully realized the dynamic evolution and the historical traceability in PLM system.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.89-100
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• 2020

The smart factory is an important axis of the 4th industrial revolution. Smart factory is a system that induces the maximum efficiency and effectiveness of production using the IoT and intelligent sensing systems. The product lifecycle management technique is a method that can actively reflect the consumer's requirements in the smart factory and manage the entire process from the consumer to the post management. There have been many studies on product lifecycle management, but studies on how to organize product lifecycle management knowledge domains in preparation for the era of the 4th industrial revolution were insufficient. This study analyzed the opinions of a group of experts preparing for the 4th industrial revolution in terms of product lifecycle management. The impact of the 4th industrial revolution on the detailed knowledge areas of product lifecycle management was investigated. The changes in product lifecycle management were summarized using a qualitative data analysis technique for a group of experts. Based on the opinions of experts, the product lifecycle management, which consists of a total of 30 detailed knowledge areas, was prepared to supplement or prepare for the 4th industrial revolution. This study investigates changes in product lifecycle management in preparation for the 4th industrial revolution in the knowledge domain of the existing defined product life cycle management. In future research, it is necessary to redefine the knowledge domain of product life cycle management suitable for the era of the 4th industrial revolution and investigate the perception of experts. Considering the social culture and technological change factors of the 4th industrial revolution, the scope and scope of product life cycle management can be newly defined.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.52-64
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• 2019

This research was aimed at studying the situation, problems, and requirements for digital collection lifecycle management of Thai theses and dissertations. The mixed research method used was composed of: (1) Study of the problem and situation in which the qualitative method was applied. The research site covered 10 higher education institutions where the Thailand Digital Collection (TDC) project is operated. The informants were key administrative officers of the TDC project of each institution. In-depth and structured interviews were conducted on an individual basis to obtain the most accurate answers. (2) Study of requirements based on the quantitative research method to survey the requirements for the digital collection management system for Thai theses and dissertations from 84 purposively-selected TDC project officers and 527 end users selected by accidental sampling, totaling 611 samples. Research findings are as follow: (1) The study of the situation and problems of digital collection lifecycle management shows that Thai higher institutions systematically manage their digital collection. The management lifecycle is consistent with the Guidance documents for lifecycle management of ETDs, which included seven steps: program planning, creation, submission, and ingestion, access and retrieval of digital objects, archiving and preservation, evaluation and assessment, interoperation (creation of institutional collaboration), and development of link data. (2) The study of requirements for digital collection management of Thai theses and dissertations shows five system requirements: acquisition and gathering, digitization, metadata standards, management of rights, and storage and retrieval, all of which are at M (mandatory) and D (desirable) levels.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.3
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• pp.103-131
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• 2012

This study aimed to identify the entire lifecycle of research projects in science and technology. Specifically, it attempted to reveal major research steps and research activities from the beginning to the end of R&D projects. It also investigated information needs, source use and problems scientists encounter in each research step. In-depth interviews with 24 Korean scientists in the fields of bio- and nano-science and technology revealed five major steps of lifecycle, namely idea formation, seeking funding, experiment and analysis, output disseminations, and evaluation. We further identified specific information behaviors and salient communication and research tools in each step.

• Computers and Concrete
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• v.20 no.5
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• pp.511-519
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• 2017

The reliability of reinforced concrete structures is frequently compromised by the deterioration caused by reinforcement corrosion. Evaluating the effect caused by reinforcement corrosion on structural behaviour of corrosion damaged concrete structures is essential for effective and reliable infrastructure management. In lifecycle management of corrosion affected reinforced concrete structures, it is difficult to correctly assess the lifecycle performance due to the uncertainties associated with structural resistance deterioration. This paper presents a stochastic deterioration modelling approach to evaluate the performance deterioration of corroded concrete structures during their service life. The flexural strength deterioration is analytically predicted on the basis of bond strength evolution caused by reinforcement corrosion, which is examined by the experimental and field data available. An assessment criterion is defined to evaluate the flexural strength deterioration for the time-dependent reliability analysis. The results from the worked examples show that the proposed approach is capable of evaluating the structural reliability of corrosion damaged concrete structures.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.234-245
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• 2012

This paper proposes a multi-level product modeling framework for long-term lifecycle products. The framework can help engineers to define product models and relate them to physical instances. The framework is defined in three levels; data, design model, modeling language. The data level represents real-world products, The model level describes design models of real-world products. The modeling language level defines concepts and relationships to describe product design models. The concepts and relationships in the modeling language level enable engineers to express the semantics of product models in an engineering-friendly way. The interactions between these three levels are explained to show how the framework can manage long-term lifecycle product information. A prototype system is provided for further understanding of the framework.

• Journal of the Korean Society for information Management
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• v.29 no.3
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• pp.99-122
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• 2012

This study analyzed scientists information behaviors when they engage in solving specific research problems in various situations throughout the entire scientific R&D lifecycle process. In-depth interviews with a total of 24 scientists were conducted in their research laboratories, the scientists' everyday workplace and the contexts of scientific research. The theoretical and methodological frameworks employed for this study were Dervin's Sense-making, Savolainen's Everyday Life Information Seeking, and Engestrom's Activity Theory. The findings of this study informed context-specific research and information behaviors of the scientists in the 14 sub stages of the five-stage of R&D lifecycle. Specifically, the study revealed the research objectives and related information behaviors (e.g., information needs, information seeking, information sources and channels, information barriers, etc.) to achieve the objectives at each sub-stage. The study results provided essential information to re-design the information services and strategies that accommodate the scientific R&D lifecycle.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2006.05a
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• pp.384-389
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• 2006