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What is Design Science

Encyclopedia of Data Science and Machine Learning
A emerging research methodology focusing on the creation of artifacts (methods, techniques, and tools) and the evaluation of their performance in the physical, social, and cultural environment. Like a software application, a process model can be considered as an artifact and created and evaluated by following design science methodology.
Published in Chapter:
Beyond Technology: An Integrative Process Model for Data Analytics
Chaojie Wang (The MITRE Corporation, USA)
Copyright: © 2023 |Pages: 15
DOI: 10.4018/978-1-7998-9220-5.ch067
Abstract
Data analytics is a key to unlock the untapped power of knowledge hidden in the trenches of big data in the age of information and intelligence. However, not all analytics efforts can achieve the desired outcomes and impacts. A successfully executed data analytics project relies on the application of an effective process model that facilitates multidisciplinary collaborations and balance technical efficiency with organizational effectiveness. This article introduces an integrated process model for data science and machine learning including its theoretical foundation and step-by-step descriptions and guidelines. The goal of this article is to provide concise, easy-to-follow guidance for data professionals and domain experts to apply this novel process model in their day-to-day collaborative and iterative analytics effort.
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More Results
Ontology Development Methodology for Virtual Reality-Based Training (VRT) in Ophthalmology Domain: Phaco Cataract Surgery Case Study
The design science paradigm concerns itself with the innovation of artifacts that can be a solution for an unsolved problem. This artefact can be as model, method, construct, or an instantiation.
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Fidelity and Play Model: Balancing Seriousness
Part of science that deals with phenomena and artifacts created by humanity.
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