Browsing by Author "Perdahci, Ziya N."

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Citation Count: 0
Metadata Action Network Model for Cloud Based Development Environment
(Springer international Publishing Ag, 2020) Aydin, Mehmet N.; Perdahci, Ziya N.; Safak, I; van Hillegersberg, J. (Jos)
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 cloud-based 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.
Citation Count: 4
Validity issues of digital trace date for platform as a service: A network science perspective
(Springer Verlag, 2018) Aydın, Mehmet Nafiz; Kariniasukaite, Dzordana; Perdahci, Ziya N.
Data validity becomes a prominent research area in the context of data science driven research in the past years. In this study, we consider an application development on a cloud computing platform as a promising research area to examine digital trace data belonging to records of development activity undertaken. Trace data display such characteristics as found data that is not especially produced for research, event-based, and longitudinal, i.e., occurring over a period of time. Having these characteristics underlies many validity issues. We employ two application development trace data to articulate validity issues along with an iterative 4-phase research cycle. We demonstrate that when working with digital trace data, data validity issues must be addressed; otherwise it can lead to awry results of the research.