Data Sharing

This section of the knowledge database, is developed from the CARTRE data exchange platform, that provides methods for the exchange of data, knowledge and experience.  CARTRE, “Coordination of Automated Road Transport Deployment for Europe”, was a Support Action submitted for the call H2020-ART-2016-SingleStage-RTD. The data sharing section is built on former work done in the FOT-Net projects, but adjusted to new needs and requirements from automated pilots. It offers the automated driving and FOT communities a networking forum. It supports tests by offering training on the FESTA evaluation methodology and the Data Sharing Framework (

Data collected in FOT:s, NDS:s and automation pilots is complex and needs a structured approach for exchange to happen. The data sharing initiative in ARCADE merge the FOT-Net Data Sharing Framework and the Data Catalogue, including the three necessary elements of methodology, dissemination and storage and access. In addition the data anonymization part is highlighted since being an important subject in the GDPR era.
In 2020 the joint activities in L3Pilot project have concluded into the publishing of a common data format. The format is openly published (MIT license) on GitHub and will be promoted in the knowledge base. To read about the format click on the element below or visit the project home page:

On Feb 25th 2021 ARCADE project organized a workshop on data sharing. Between 70 to 80 participated in the morning webinar where interesting presentations on GDPR, Data for road safety partnership, edge computing, and data sharing principles in large European research projects were presented. In the afternoon, 50 experts shared knowledge and experiences in three breakout sessions covering important aspects of data sharing. All material, including presentations and proceedings, are available on 5th Joint Stakeholder Network on Data Sharing.

In July 2022 the Data Catalogue was massively updated now covering 20+ datasets on automated driving (many related to specific parts of ML training), and introduced sections on Data Catalogues, Federated data sharing and Data Marketplaces.

At the same time, a new column “Topics in data sharing” was published covering short articles on interesting topics in data sharing.  The aim is to continue this column in the FAME project.

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