The aim of this guide is to actively support organisations through challenges of sharing data for AI applications. This guide focuses on the guidelines and building blocks to interconnect data spaces.
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- 26/04/2023
Reference guide for intra AI data space interoperability
The aim of this guide is to actively support organisations through challenges of sharing data for AI applications. In doing so, this guide focuses on the guidelines and building blocks for individual (sectoral, application-specific) AI data spaces.
- 02/11/2021
NL AIC Reference Guide: ‘Towards a federation of AI data spaces’
This document provides reference and guideline for developing AI data spaces, giving a rich set of methodologies, tools, processes and building blocks to support the challenges and requirements of AI.
- 12/12/2020
GAP analysis ‘From data sharing proofs-of-concept towards operationalization of the system architecture’
To gain insight into the opportunities and challenges for operationalisation and large-scale application of AI, the Data Sharing working group carried out a GAP analysis based on three use cases.
- 08/03/2020
Responsible data sharing in AI
Together with algorithms, data is the building block for AI applications, which must function properly and responsibly. The Data Sharing working group has released this report (in Dutch) to help realise AI-implementations.