scholarly journals Contribuições para a gestão de dados científicos: análise comparativa entre modelos de ciclo de vida dos dados | Contributions to the management of scientific data: comparative analysis among life cycle models

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Débora Gomes de Araújo ◽  
Marco Antonio Almeida Llarena ◽  
Sandra De Alburqueque Siebra ◽  
Guilherme Ataíde Dias
Keyword(s):  
Information Technology ◽  
Life Cycle ◽  
Comparative Analysis ◽  
Scientific Data ◽  
Life Cycles ◽  
Single Step ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Digital Curation ◽  
Data Life Cycle

RESUMO O objetivo foi analisar as intersecções entre os elementos dos modelos de ciclos de vida dos dados das iniciativas do DCC, DataONE e o CVD-CI. Trata-se de uma pesquisa descritiva, qualitativa e bibliográfica. Verificou-se que há correspondências entre etapas (nem sempre de um para um) dos ciclos de vida dos dados analisados. Foi possível constatar que o CVD-CI condensa várias atividades em uma única etapa, o que pode dificultar a sua aplicabilidade. De uma maneira geral, os modelos propostos ainda carecem de maior detalhamento para poderem ser aplicados diretamente por pesquisadores/curadores.Palavras-chave: Ciclo de Vida dos Dados; Curadoria Digital; Dados científicos; Tecnologia da Informação.ABSTRACT The objective was to analyze the intersections among the data life cycle model elements of the DCC, DataONE and CVD-CI initiatives. It is a descriptive, qualitative and bibliographical research. It was verified that there are correspondences between stages (not always one-to-one) of the analyzed data life cycles. It was possible to verify that the CVD-CI condenses several activities in a single step, which can hinder its applicability. In general, the proposed models still need to be further detailed so that they can be directly applied by researchers/curators.Keywords: Data Life Cycle; Digital Curation; Scientific Data; Information Technology.

A hotel life cycle model based on bootstrap DEA efficiency

2015 ◽  
Vol 27 (5) ◽  
pp. 918-937 ◽  
Author(s):  
Pengzhen Yin ◽  
Henry Tsai ◽  
Jie Wu
Keyword(s):  
Life Cycle ◽  
Life Cycles ◽  
Initial Growth ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Content Type ◽  
Average Efficiency ◽  
Dea Model ◽  
Bootstrap Dea ◽  
Objective Indicators

Purpose – This study aims to propose a hotel life cycle model and applies this model to examine the development of international tourist hotels (ITHs) in Taipei. Design/methodology/approach – In this study, a two-stage approach is proposed to examine the life cycles of 20 ITHs in Taipei. First, we evaluate the overall and departmental efficiencies by using a two-layer bootstrap data envelopment analysis (DEA) model. Second, we divide the phases of the hotel life cycle by incorporating two objective indicators, namely, the average efficiency change rate (AECR) and the annual average efficiency (AE). Findings – The results show not only that the efficiency scores derived from the bootstrap DEA model could help assess the performance of individual ITHs but also that the resulting AECR and AE could help to objectively classify the development of the hotels under study into the following phases: initial, growth, maturity and recession and regeneration phases. Practical implications – The method proposed in, and the results obtained from, this study can provide the stakeholders of the ITHs in Taipei with an alternative to the existing subjective enterprise life cycle (ELC) model for identifying these ITHs’ stages of development using quantitative and objective criteria. Originality/value – Existing hotel management research rarely focuses on hotel life cycle analysis, likely due to the adoption of subjective criteria by the conventional ELC model, which limits the practical application of the research. To improve on the conventional ELC model, our proposed quantitative approach involves dividing the hotel life cycle by employing two objective indicators and then empirically presenting the results.

scholarly journals Virtual Reality: A Simple Substitute or New Niche?

2022 ◽  
pp. 28-40
Author(s):  
Victoria-Ann Verkerk
Keyword(s):  
Virtual Reality ◽  
Life Cycle ◽  
Comparative Analysis ◽  
Tourism Industry ◽  
System Model ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Negative Effects ◽  
Model Based

AbstractSince 2020, the tourism industry worldwide has been devastated as a result of the COVID-19 pandemic. Governments across the globe imposed strict national lockdowns in order to curb the spread of the pandemic, with negative effects on tourism. This forced many tourism companies and organizations to turn to virtual reality (VR) to survive. As a consequence, numerous tourism scholars began to question whether VR would replace conventional tourism after COVID-19. The study aims is to address this concern and to determine if VR will be a substitute for conventional tourism or whether it can be considered as a tourism niche. It is a conceptional study which adopts a comparative analysis of conventional tourism models and VR. It uses two popular conventional tourism models, namely N. Leiper’s (1979) tourism system model and R.W. Butler’s (1980) destination life-cycle model. Based on this analysis, this paper suggests that VR will never be a substitute for conventional tourism, but should rather be considered a future tourism niche.

The Life Cycle in Economic History

1983 ◽  
Vol 43 (1) ◽  
pp. 149-158 ◽  
Author(s):  
J. R. Kearl ◽  
Clayne L. Pope
Keyword(s):  
Life Cycle ◽  
Economic History ◽  
Life Cycles ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Cross Sectional ◽  
Income Ratio ◽  
History Of ◽  
Positive Effect ◽  
Foreign Birth

The life cycles of income and wealth form important traces of the economic history of households. Comparisons of cross-sectional estimates of the age-wealth profiles from 1774 to 1962 reveal little change in the basic pattern although crosssectional age-income or earnings profiles peak later in modern periods because of the increased investment in human capital.The wealth-income ratio appears to be declining. Multivariate regressions for Utah households show wealth-income patterns consistent with a life cycle model based on smoothing of consumption with little interaction between age and other determinants of economic position. Foreign birth has a positive effect on income while reducing wealth.

scholarly journals Developing a Knowledge Management System for Integrated Vehicle Health Management Using a Data Life Cycle Model

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexslis Maindze
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Management System ◽  
Health Management ◽  
Knowledge Management System ◽  
Quality Data ◽  
Life Cycle Model ◽  
Cycle Model ◽  
High Quality Data ◽  
Data Life Cycle

Data forms the foundation on which knowledge is created, captured, used and shared. The lack of an approach consistent with technological changes and needs can facilitate loss of knowledge and increased costs. Integrated Vehicle Health Management (IVHM) is characterized by prognostics and diagnostics which depend heavily on high quality data to perform data-driven, model-based and hybrid computational analysis of asset health. As a result, managing data and knowledge for Integrated Vehicle Health Management (IVHM) requires a data life cycle model that adopts the OSA-CBM data model and integrate with other approaches. This project will propose such a model and use it to support the development of an IVHM knowledge management system.

scholarly journals Блокчейн-технології в управлінні комунікаціями інфраструктурних проектів

2021 ◽  
pp. 169-181
Author(s):  
Дмитро Петрович Литвиненко ◽  
Ольга Володимирівна Малєєва ◽  
Аліна Володимирівна Єлізєва
Keyword(s):  
Life Cycle ◽  
Project Management ◽  
Comparative Analysis ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Communication Management ◽  
Advantages And Disadvantages ◽  
Blockchain Technology ◽  
Smart Contract ◽  
Infrastructure Project

The subject of research in the article is the processes and technologies of communication management of infrastructural projects. The possibilities of using blockchain technology in the field of project management are considered. The goal of work: improving the information security of infrastructure projects. The risks of stakeholder communications will be reduced by increasing the security of data access and reducing the time for their processing, which in turn will provide more flexible project management. The tasks of the work: to analyze the current state of development of blockchain technology and conduct a comparative analysis of technology and modern generally accepted management methods, give examples of implementation, determine the advantages of blockchain technology in modern conditions; analyze the benefits of using smart contracts in communication management, apply the smart contract life cycle model in an infrastructure project. Research methods: systems analysis, design approach, structural modeling, instrument Geth, programming language Solidity. The following results were obtained. The main directions of development and implementation of blockchain technology are characterized, examples of the use of blockchain technology in various industries are collected and analyzed, the main advantages and disadvantages of the technology are identified, a comparative analysis of blockchain technology and classical project management methods is carried out, the possibilities of using blockchain technology in the field of project management are described, the main the possibility of implementing reasonable contracts, the advantages and disadvantages of reasonable contracts are identified, the advantages and disadvantages of the instrument of reasonable contracts are analyzed in comparison with the traditional approach. The smart contract life cycle model presents the creation stages, installation to the blockchain contract managing, and contract completion. Provided an example of the smart contract used for the complex financial project, which reduced the risk of project failures. Conclusion. The scientific novelty of the obtained results is in the improvement of the project management life cycle model through the further development of the smart contract model. This allows to increase information security, reduce possible risks and guarantee the implementation of an infrastructure project through the use of blockchain technology in comparison with classical project management methods.

scholarly journals Towards an Enhanced Data- and Knowledge Management Capability: A Data Life Cycle Model Proposition for Integrated Vehicle Health Management

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexslis Maindze ◽  
Zakwan Skaf ◽  
Ian Jennions
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Health Management ◽  
Process Models ◽  
Quality Data ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Data Life Cycle ◽  
Wide Range ◽  
The Creation

The creation, capturing, using and sharing of knowledge is based on data. The rate of data creation, collection, and elicitation through wide range experiments, simulations and measurements is rapidly increasing within Integrated Vehicle Health Management (IVHM). In addition, Knowledge Management (KM), data abstraction, analyses, storage and accessibility challenges persist, resulting in loss of knowledge and increased costs. This growth in the creation of research data, algorithms, technical papers, reports and logs, requires both a strategy and tool to address these challenges. A Data Life Cycle Model (DLCM) ensures the efficient and effective abstraction and management of both data and knowledge outputs. IVHM which depend heavily on high-quality data to perform data-driven, model-based and hybrid computational analysis of asset health. IVHM Centre does not yet have a systematic and coherent approach to its data management. The absence of a DLCM means that valuable knowledge might be lost or is difficult to find. Data visualization is fragmented and done on a project by project basis leading to increased costs. There is insufficient algorithm documentation and communication for easy transition between subsequent researchers and personnel. A systematic review of DLCMs, frameworks, standards and process models pertaining to data- and KM in the context of IVHM, found that there is no DLCM that is consistent with IVHM data and knowledge management requirements. Specifically, there is a need to develop a DLCM based on Open System Architecture for Condition-Based Maintenance framework.

Dynamics of Price Elasticity and Brand Life Cycles: An Empirical Study

1979 ◽  
Vol 16 (4) ◽  
pp. 439-452 ◽  
Author(s):  
Hermann Simon
Keyword(s):  
Life Cycle ◽  
Empirical Study ◽  
Price Elasticity ◽  
Life Cycles ◽  
Time Varying ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Carryover Effects ◽  
Strategic Pricing

A brand life cycle model is developed which incorporates carryover effects and obsolescence and allows for time-varying price responses. An empirical study of 35 brands in seven different markets shows typical changes in price elasticity over the brand life cycle. Important implications for strategic pricing and antitrust issues are indicated.

scholarly journals Revisiting the Data Lifecycle with Big Data Curation

2016 ◽  
Vol 10 (2) ◽  
pp. 176-192 ◽  
Author(s):  
Line Pouchard
Keyword(s):  
Big Data ◽  
Life Cycle ◽  
High Performance ◽  
Research Data ◽  
Data Curation ◽  
Complex Data ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Data Repositories ◽  
Data Life Cycle

As science becomes more data-intensive and collaborative, researchers increasingly use larger and more complex data to answer research questions. The capacity of storage infrastructure, the increased sophistication and deployment of sensors, the ubiquitous availability of computer clusters, the development of new analysis techniques, and larger collaborations allow researchers to address grand societal challenges in a way that is unprecedented. In parallel, research data repositories have been built to host research data in response to the requirements of sponsors that research data be publicly available. Libraries are re-inventing themselves to respond to a growing demand to manage, store, curate and preserve the data produced in the course of publicly funded research. As librarians and data managers are developing the tools and knowledge they need to meet these new expectations, they inevitably encounter conversations around Big Data. This paper explores definitions of Big Data that have coalesced in the last decade around four commonly mentioned characteristics: volume, variety, velocity, and veracity. We highlight the issues associated with each characteristic, particularly their impact on data management and curation. We use the methodological framework of the data life cycle model, assessing two models developed in the context of Big Data projects and find them lacking. We propose a Big Data life cycle model that includes activities focused on Big Data and more closely integrates curation with the research life cycle. These activities include planning, acquiring, preparing, analyzing, preserving, and discovering, with describing the data and assuring quality being an integral part of each activity. We discuss the relationship between institutional data curation repositories and new long-term data resources associated with high performance computing centers, and reproducibility in computational science. We apply this model by mapping the four characteristics of Big Data outlined above to each of the activities in the model. This mapping produces a set of questions that practitioners should be asking in a Big Data project

Applying a Metadata Framework to Improve Data Quality

2005 ◽  
pp. 146-151
Author(s):  
Victoria Youngohc Yoon ◽  
Peter Aiken ◽  
Tor Guimaraes
Keyword(s):  
Life Cycle ◽  
Data Quality ◽  
Quality Engineering ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Imperfect Data ◽  
Information Resources Management ◽  
Business Operations ◽  
Data Life Cycle ◽  
A Company

The importance of a company-wide framework for managing data resources has been recognized (Gunter, 2001; Lee, 2003, 2004; Madnick, Wang & Xian, 2003, 2004; Sawhney, 2001; Shankaranarayan, Ziad & Wang, 2003). It is considered a major component of information resources management (Guimaraes, 1988). Many organizations are discovering that imperfect data in information systems negatively affect their business operations and can be extremely costly (Brown, 2001; Keizer, 2004). The expanded data life cycle model proposed here enables us to identify links between cycle phases and data quality engineering dimensions. Expanding the data life cycle model and the dimensions of data quality will enable organizations to more effectively implement the inter- as well as intra-system use of their data resources, as well as better coordinate the development and application of their data quality engineering methods.

scholarly journals FAITH Software Life Cycle Model for Forex Expert Advisors

2021 ◽  
Vol 9 (1) ◽  
pp. 1-12
Author(s):  
D.A Oyemade ◽  
D Allenotor
Keyword(s):  
Life Cycle ◽  
Software Development ◽  
Life Cycles ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Software Life Cycle ◽  
Investment Capital ◽  
Lot Sizes ◽  
Stop Loss ◽  
Very High

The emotional stress and uncertainties associated with foreign exchange (forex) trading due to the high risk of losing the investment capital has left most forex traders in a state of indecision on the best methodology to apply for achieving long term profit. The provision of lot sizes, leverages, take profits and stop losses in forex trading implies that very high profit can be made within a very short time with the same capital, but at the same time, very high losses can be incurred. On one hand, this provision often prompts a set of traders to become greedy by increasing their take profit levels, lot sizes and leverages, which in turn increases their probability of losing out. On the other hand, the provision creates doubts and induces the fear of losses in some other set of traders. Consequently, these set of conservative traders employ the use of relatively small lot sizes, low leverages and low values of take profit and high stop loss levels. This in turn often results in a devastating effect on the investment capital due to lost opportunities and resulting losses. The problem of losses in forex trading effort is compounded by the fact that many programmers and developers of forex expert advisors do not adopt a software life cycle, having learned only how to write codes to program the trading platform. Furthermore, software engineering professionals who understand the import of software development life cycles soon discover that conventional software life cycles are not capable of effectively handling the complexity of the forex market. This paper models the human characteristics of greed, fear and doubt as manifested by traders in forex trading using selected expert advisors’ properties. It proposes Facts, Analysis, Implementation, Testing and Hope (FAITH) software life cycle model for Forex trading profitability to tackle the problem of indecision in the development of forex expert advisors. The proposed model was implemented on a live trading platform for a period of three months and compared with doubt, fear and greed approach to trading. The results showed that while a level of greed can be profitable, FAITH software life cycle produced more profitable results and can be adopted for forex trading. Keywords: Software Development Life Cycle, Expert advisors, Forex Model, Losses, Profit

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