NL AIC presents two reference guides for responsible data sharing for AI applications

Published on: 12 April 2023

The Netherlands AI Coalition is aiming to put the Netherlands in a front-runner position in terms of both knowledge of AI and its applications for well-being and welfare. To achieve this, it is crucial to make data widely available so that AI algorithms can be better fed with correct information.

Accelerating AI implementation

The Data Sharing working group is committed to creating a flourishing data environment in the Netherlands that will make numerous new and improved AI applications possible and accelerate the implementation of AI. The data should be made available or accessible in a controlled and responsible way. One way of achieving this goal of reliable data sharing for AI is joining the European data strategy for data spaces. This ensures that a Dutch approach is also well-embedded internationally and that an open and equitable data-sharing environment is created, where data from governmental authorities, the commercial sector and the public at large can be used safely by AI developments in the general interest and for boosting the earnings capacity of businesses.

Active support of AI implementation

To help achieve these aims, the NL AIC described the umbrella approach for the development of AI data spaces in 2021, in ‘Towards a Federation of Interoperable (AI) Data Spaces’. Two main aspects were introduced there: how to design individual AI data spaces, and how to connect them together so that data can be shared reliably not just within e.g. sector-specific and applied AI data spaces but also between sector-specific data spaces. TNO has produced an additional reference guidebook on behalf of NL AIC for each of those aspects. These reference guides contain practical explanations for parties and organisations about getting started with the development of data spaces for AI applications. These reference guidebooks were presented during the Dutch AI Ccongress on 12 April.

Who are the new guidebooks for?

Both reference guidebooks aim to actively help organisations tackle the challenges of data sharing for AI applications by offering a reference framework with common building blocks for efficient and tailored development of AI data spaces. The ‘Reference guide for intra-AI data space interoperability’ focuses on the guidelines and building blocks for individual AI data spaces (e.g. sector-specific and applied ones), whereas the ‘Reference guide for inter-AI data space interoperability’ focuses on the guidelines and building blocks for connecting data spaces together. Together, they describe how reliable data sharing can be designed within AI data spaces and between them.

International approach

Data sharing for AI transcends sectors and country borders. With the developments as described in the two publications, the Data Sharing working group is helping both Dutch and European initiatives. Within the Netherlands, the ‘Centre of Excellence for Data Sharing and Cloud’ (CoE DSC) will take over the follow-up work about data sharing for AI. This centre is a joint follow-up initiative by the Data Sharing Coalition, the NL AIC’s Data Sharing working group and the Dutch Gaia-X hub. These results will be further promoted in Europe, for example in the International Data Spaces Association, Gaia-X and the Data Spaces Support Centre.

More information?

If you’re interested in more information about data sharing, go to the working group’s web page for more manuals and tools or contact Pepijn Groen.

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