When we talk about data on this podcast, its mostly about training data and its properties that are relevant for the training machine learning models. But today we look at the bigger picture and the use of data in future data economies. How should the future use of data on a bigger scale look like? How can we make sure to build trustworthy and ethical data economy that follow our European Values?

Today on the show I am talking to Nina Popanton from the Data Intelligence Initiative (DIO) about its role as an enable of data collaborations. We talk about the challenges and the opportunities they see for companies, academia and the public sector when sharing data for specific use cases.

We discuss the motivation for stockholders to come together and share their data, and under which circumstances they are willing to do so.

In addition we are taking a step back and have a look the greater picture and the socioeconomic responsibility of a data sharing economy, driven by the "European Strategy for Data" and European projects like Gaia-X.

I know this episode diverges from our usual focus on AI and its methods, but I hope it will be an inspiration to you. Let's get started …

# References

Nina Popanton - https://www.linkedin.com/in/nina-popanton-4b1541179/

DIO - https://www.dataintelligence.at/

Gaia-X - https://www.gaia-x.eu/

GreenData Hub - https://www.greendatahub.at/