About Datascience.aero

Our team has led the field in data analytics in aviation for close to a decade. We decided to start the DataScience.aero blog in 2017 to share our thoughts on how AI could be developed and deployed safely in aviation.

Our blog is written by our teams at Innaxis.aero and DataBeacon.aero. We cover different maturity aspects of AI from fundamental research, applicability of algorithms and code development, to market issues, safety, regulation and practical aspects of AI practice in aviation.



How can we make sure safety is a key element in AI development?
How can AI systems be approved or certified? Are AI systems “black-boxes”?
What’s the role of Explainable AI?
Safety cases.



What are the technological ingredients of AI?
Data engineering, computing architectures, analytic techniques,
visualization and data protection.
MLOps practice.


Use Cases

Where do we see AI implemented in aviation?
What are the elements that contribute to a use case being successful?
Who is responsible for the user story in an AI use case
and how do we put together teams of domain experts and ML practitioners?


Green & Digital

Digitalization and AI will be the driver of the operationalization of green operational concepts that will boost the environmental performance of aviation


Who writes here?

DataScience.aero is written by Innaxis and DataBeacon.
Our teams are responsible for the content.
All content is original. We provide references whenever possible.