scholarly journals Do Required Minimum Distribution 401(K) Rules Matter, and for Whom? Insights from a Lifecycle Model

2021 ◽  
Author(s):  
Vanya Horneff ◽  
Raimond Maurer ◽  
Olivia S. Mitchell
Keyword(s):  
Lifecycle Model

scholarly journals Media Digitization and Preservation Initiative: A Case Study

2018 ◽  
Vol 13 (1) ◽  
pp. 91-113
Author(s):  
Devan Ray Donaldson ◽  
Allison McClanahan ◽  
Leif Christiansen ◽  
Laura Bell ◽  
Mikala Narlock ◽  
...  
Keyword(s):  
Large Scale ◽  
Qualitative Case Study ◽  
Future Research ◽  
Indiana University ◽  
Roles And Responsibilities ◽  
Case Study Analysis ◽  
Digital Curation ◽  
Lifecycle Model ◽  
Mass Digitization

Since its creation nearly a decade ago, the Digital Curation Centre (DCC) Curation Lifecycle Model has become the quintessential framework for understanding digital curation. Organizations and consortia around the world have used the DCC Curation Lifecycle Model as a tool to ensure that all the necessary stages of digital curation are undertaken, to define roles and responsibilities, and to build a framework of standards and technologies for digital curation. Yet, research on the application of the model to large-scale digitization projects as a way of understanding their efforts at digital curation is scant. This paper reports on findings of a qualitative case study analysis of Indiana University Bloomington’s multi-million-dollar Media Digitization and Preservation Initiative (MDPI), employing the DCC Curation Lifecycle Model as a lens for examining the scope and effectiveness of its digital curation efforts. Findings underscore the success of MDPI in performing digital curation by illustrating the ways it implements each of the model’s components. Implications for the application of the DCC Curation Lifecycle Model in understanding digital curation for mass digitization projects are discussed as well as directions for future research.

scholarly journals Methodology and Tools for Digital Twin Management—The FA3ST Approach

IoT ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 717-740
Author(s):  
Ljiljana Stojanovic ◽  
Thomas Usländer ◽  
Friedrich Volz ◽  
Christian Weißenbacher ◽  
Jens Müller ◽  
...  
Keyword(s):  
Decision Making ◽  
Industrial Applications ◽  
Industrie 4.0 ◽  
Conceptual Approach ◽  
Digital Twin ◽  
Digital Representations ◽  
Lifecycle Model ◽  
Digital Twins ◽  
International Data ◽  
Physical Assets

The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as well-defined software entities themselves that follow the whole lifecycle of their physical counterparts from the engineering, operation up to the discharge, and hence, have their own type description, identity, and lifecycle. This paper elaborates on this idea and argues the need for systematic DT engineering and management. After a conceptual description of DT, the paper proposes a DT lifecycle model and presents methodologies and tools for DT management, also in the context of Industrie 4.0 concepts, such as the asset administration shell (AAS), the international data spaces (IDS), and IEC standards (such as OPC UA and AML). As a tool example for the support of DT engineering and management, the Fraunhofer-advanced AAS tools for digital twins (FA3ST) are presented in more detail.

scholarly journals Decisions, Models, and Monitoring -- A Lifecycle Model for the Evolution of Service-Based Systems

2013 ◽  
Author(s):  
Christian Inzinger ◽  
Waldemar Hummer ◽  
Ioanna Lytra ◽  
Philipp Leitner ◽  
Huy Tran ◽  
...  
Keyword(s):  
Lifecycle Model

Lifecycles

2019 ◽  
pp. 1-32
Keyword(s):  
Large Scale ◽  
Software Systems ◽  
Software Products ◽  
Product Success ◽  
Product Features ◽  
Lifecycle Model ◽  
Software Product ◽  
Project Risks ◽  
Mission Critical ◽  
Common Understanding

This chapter discusses lifecycle model application for software development. It compares the benefits and shortcomings of different models. The authors argue that there is no universal lifecycle model. For agility, this chapter recommends combining prototyping with the other models. The authors suggest this to achieve a common understanding of the key product features and to reduce project risks. The lifecycle model choice determines project economics and time to market. The model also influences product quality and overall project success. However, product success essentially depends on human factors. The authors analyze the applicability of the lifecycle models to large-scale, mission-critical software systems. Finally, this chapter introduces a methodology. It includes a spiral-like lifecycle and a set of formal models and visual tools for software product development. This methodology helps to optimize the software product lifecycle. It fits large-scale, complex heterogeneous software products.

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