Modelling big data platforms as knowledge graphs: the data platform shaper

The rise of big data has introduced significant challenges in managing, storing, analyzing, and modeling data. These challenges require the integration of diverse storage and computing platforms. Consequently, incorporating new data sources and developing new data transformation methods is typically a slow and expensive process. Furthermore, these platforms often lack sufficient abstraction and are heavily reliant on particular technologies, which results in increased costs when adapting to new technological developments. This paper addresses these issues by presenting the Data Platform Shaper, an open tool for constructing and managing data platform catalogs as knowledge graphs. This system is built on top of the Agile Data Management Ontology (AGILE-DM), a novel ontology specifically designed for describing big data platforms. Our solution is characterized by flexibility, technological neutrality, and enhanced adaptability to changes and technological advancements.