Simple-ML: Towards a Framework for Semantic Data Analytics Workflows

TL;DR

Simple-ML is a framework that leverages semantic technologies to improve the configuration, robustness, and reusability of data analytics workflows, demonstrated through a mobility domain case study.

Contribution

It introduces semantic data models specifically designed for data analytics workflows, enabling more efficient and adaptable analytics processes.

Findings

Semantic data models support workflow robustness and reusability.

Framework applied successfully to a real-world mobility use case.

Enhances configuration efficiency of data analytics workflows.

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.