Validity Issues of Digital Trace Data for Platform as a Service: A Network Science Perspective

Aydın, Mehmet N.; Kariniauskaite, Dzordana; Perdahci, N. Ziya

doi:10.1007/978-3-319-77703-0_65

“…Metadata aPaaS provides visual tools to customize data models, application logic, workflow, and user interface. The underlying metadata model for this aPaaS is essential to this research as it provides us a metamodel [9] to reflect on network models of digital trace data to be discussed later on.…”

Section: Demonstration Of Network Analytics On Apaasmentioning

confidence: 99%

“…This research focuses on PaaS which acts as a bridge between IaaS and SaaSit is the runtime environment, the middleware of the cloud service architecture [6]. Metadata Application PaaS (aPaaS) is a particular type of PaaS, which provides cloud-based integrated development environment with a metamodel [9]. Simply this type (metadata aPaaS) embrace the very idea of model-driven software development [7] that employs a number of essential principles such as abstraction, model transformation and refinement, reusability [8].…”

Section: Introductionmentioning

confidence: 99%

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Metadata Action Network Model for Cloud Based Development Environment

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Cloud-based software development solutions (entitled as Platformas-a-Service, Low-Code platforms) have been promoted as a game changing paradigm backed by model-driven architecture and supported by various cloudbased services. With the engagement of a sheer number of platform users (experienced, novel, or citizen developers) these platforms generate invaluable data and that can be considered as user metadata actions. As cloud-based development solutions provide novice users with a new development experience (performing data actions that altogether leads to a successful software app), users often times face with uncertainty about development performance; how good or complete is app development? Thus, the issue addressed in this research is how to measure user performance by using digital trace data generated on the cloud platform from a Network Science perspective. This research proposes a novel approach to leveraging digital trace data on Platform-as-a-Service (PaaS) from a Network Science perspective. The proposed approach considers the importance of digital trace data as metadata actions on PaaS and introduces a network model (so-called Metadata Action Network), which is claimed to be the result of reconstruction of events of developer's actions. We show suitability of the proposed approach to better understanding of real-world digital trace data on PaaS solution and elaborate basic performance analytics on a PaaS solution with research and practical implications.

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When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned.

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Perdahçı

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When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned.

show abstract

Validity Issues of Digital Trace Data for Platform as a Service: A Network Science Perspective

Cited by 3 publications

References 12 publications

Metadata Action Network Model for Cloud Based Development Environment

Metadata Action Network Model for Cloud Based Development Environment

Big Data Analytics and Models

Big Data Analytics and Models

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