Abstract
This publication will introduce the reference model AI2VIS4BigData for the application domains Big Data analysis, AI, and visualization. Without a reference model, developing a software system and other scientific and industrial activities in this topic field lack a common specification and a common basis for discussion and thus pose a high risk of inefficiency, reinventing the wheel and solving problems that have already been solved elsewhere. To prevent these disadvantages, this publication systematically derives the reference model AI2VIS4BigData with special focus on use cases where Big Data analysis, artificial intelligence (AI), and visualization mutually support each other: AI-powered algorithms empower data scientists to analyze Big Data and thereby exploit its full potential. Big Data enables AI specialists to comfortably design, validate, and deploy AI models. In addition, AI’s algorithms and methods offer the opportunity to make Big Data exploration more efficient for both, involved users and computing and storage resources. Visualization of data, algorithms, and processing steps improves comprehension and lowers entry barriers for all user stereotypes involved in these use cases.
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Reis, T., Bornschlegl, M.X., Hemmje, M.L. (2021). Toward a Reference Model for Artificial Intelligence Supporting Big Data Analysis. In: Stahlbock, R., Weiss, G.M., Abou-Nasr, M., Yang, CY., Arabnia, H.R., Deligiannidis, L. (eds) Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-71704-9_38
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