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DSVMs - Virtual Machines for Data Science

The rapid development of technology for data science applications frequently demands to test established or developing frameworks. Virtualization provides the infrastructure for efficient tracer bullet development.

This repository orginated from the BMWi funded project SePiA.Pro and has been used for automating the provisioning of Apache Flink on basis of OpenTOSCA [1,2].

[1] M. Falkenthal, U. Breitenbücher, M. Christ, Ch. Endres, A.W. Kempa-Liehr, F. Leymann, M. Zimmermann (2016): Towards Function and Data Shipping in Manufacturing Environments: How Cloud Technologies leverage the 4th Industrial Revolution. In: J. Barzen, R. Khalaf, F. Leymann, B. Mitschang (Editors): Proceedings of the 10th Advanced Summer School on Service Oriented Computing. IBM Research Report (RC25624), IBM Research Division: Almaden, p. 16-25

[2] M. Falkenthal, U. Breitenbücher, K. Képes, F. Leymann, M. Zimmermann, M. Christ, J. Neuffer, N. Braun, A.W. Kempa-Liehr (2016): OpenTOSCA for the 4th Industrial Revolution: Automating the Provisioning of Analytics Tools Based on Apache Flink. In: Proceedings of the 6th International Conference on the Internet of Things, IoT'16, ACM: New York, p. 179--180

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