Abstract
In this paper we present the Simple-ML framework that we develop to support efficient configuration, robustness and reusability of data analytics workflows through the adoption of semantic technologies. We present semantic data models that lay the foundation for the framework development and discuss the data analytics workflows based on these models. Furthermore, we present an example instantiation of the Simple-ML data models for a real-world use case in the mobility domain.
Cite
CITATION STYLE
Gottschalk, S., Tempelmeier, N., Kniesel, G., Iosifidis, V., Fetahu, B., & Demidova, E. (2019). Simple-ML: Towards a Framework for Semantic Data Analytics Workflows. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11702 LNCS, pp. 359–366). Springer. https://doi.org/10.1007/978-3-030-33220-4_26
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