Engineering data pipelines
Acquisition, conditioning, and governance of high-volume engineering data across instrumented assets and operations.
JEIDS · Open-access · Peer-reviewed · Published quarterly
JEIDS publishes scholarship at the intersection of engineering science, information systems, and computational analytics — with rigorous double-blind peer review and a methods-and-systems editorial process designed to give authors candid, timely decisions.
Acquisition, conditioning, and governance of high-volume engineering data across instrumented assets and operations.
Model-based representations, sensor fusion, and feedback loops that close the gap between physical assets and decision software.
Data-driven decision systems, predictive maintenance, and the operational integration of analytics into engineered workflows.
Methodological work on data architectures, schemas, and engineering-grade machine learning practice.
ISSN (Online): pending · CC BY 4.0 · OAI-PMH enabled · Editorial contact: [email protected]