Broadening Ontologization Design: Embracing Data Pipeline Strategies
This work addresses the design of ontologization processes for researchers and practitioners in data engineering and ontology development, but it is incremental as it builds on existing concepts without introducing a fundamentally new paradigm.
The paper argues that the design space for ontologization is broader than current practices, proposing data pipeline strategies and an evolutionary context to reframe it as a strategic tool for leveraging digitalization opportunities, based on examples from decades of work with the bCLEARer methodology.
Our aim in this paper is to outline how the design space for the ontologization process is broader than current practice would suggest. We point out that engineering processes as well as products need to be designed and identify some components of the design. We investigate the possibility of designing a range of radically new practices implemented as data pipelines, providing examples of the new practices from our work over the last three decades with an outlier methodology, bCLEARer. We also suggest that setting an evolutionary context for ontologization helps one to better understand the nature of these new practices and provides the conceptual scaffolding that shapes fertile processes. Where this evolutionary perspective positions digitalization (the evolutionary emergence of computing technologies) as the latest step in a long evolutionary trail of information transitions. This reframes ontologization as a strategic tool for leveraging the emerging opportunities offered by digitalization.