TOWARDS A FRAMEWORK FOR ENGINEERING BIG DATA: AN AUTOMOTIVE SYSTEMS PERSPECTIVE
Editor: Marjanović D., Štorga M., Škec S., Bojčetić N., Pavković N.
Author: Byrne, Thomas James; Campean, Felician; Neagu, Daniel
Section: DESIGN INFORMATION AND KNOWLEDGE
DOI number: https://doi.org/10.21278/idc.2018.0490
Demand for more sophisticated models to meet big data expectations require significant data repository obligations, operating concurrently in higher-level applications. Current models provide only disjointed modelling paradigms. The proposed framework addresses the need for higher-level abstraction, using low-level logic in the form of axioms, from which higher-level functionality is logically derived. The framework facilitates definition and usage of subjective structures across the cyber-physical system domain, and is intended to converge the range of heterogeneous data-driven objects.