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Event report | Publication

Workshop on Manufacturing Data Spaces, summary of the results

Report on the main conclusions arising from the workshop on what role standards play with regard to data sharing.

The well-attended workshop presented exemplary data spaces that make use of GAIA-X concepts, described experiences, learnings and outcomes. Different speakers outlined essential building blocks like the 4 pillars technical solution, value creation, governance and licencing. They also addressed unified approaches like Asset Administration Shell and Digital Twins, and again and again data sovereignty. The speakers presented from a provider perspective as well as from practical, applied use cases. The aim was to advance the debate on how infrastructure initiatives such as GAIA-X can help scale embryonic operational data spaces to enable the rapid deployment of Manufacturing Data Spaces for Europe (start small – grow fast approach).

Presenting ongoing initiatives should show what is worthwhile for consideration as a starting point for the development of an industrial data space. We don't favour a top-down governance, but by keeping all the relevant stakeholders in a continuous exchange, we help to further develop commonalities. Use cases are a good way to start a conversation and develop ideas for a business ecosystem with the common goal of business value creation across multiple parties. The funding from Digital Europe wants to go a step further by supporting the roll out operationally and scaling it up as best practice examples. Speakers supported that it is important to do it on a European scale.

We see many initiatives that want to make data spaces happen and the workshop was also about how they may integrate. The idea is, that GAIA could built a kind of common ground. The presentations confirmed that this can indeed be an enabler, it was mentioned in most of the presentations. But, we need more exchange of information on the legal aspects and value sharing. The formation of data spaces have to be driven by the respective domain. The presentations demonstrated, that we're all working towards collaboration, but we are not yet there, at least we're walking along the same path. It is important to experiment more with data sharing to develop business propositions, to involve even more the user perspective, and SMEs as drivers of innovation. However, it was also said that it is important to think about cross domain aspects.

AI Test and Experimentation Facilities for Manufacturing, which are also funded through DIGITAL, were presented as an upcoming initiative that can also become important for the Manufacturing Data Spaces. It would be important to understand whether the SMEs would be interested to use the TEFs even if they don’t receive financial incentive to do so (they would receive the service for free). The responsible unit is looking forward to receiving answers to the following questions:

1)                     Would the TEFs be sufficiently attractive under these conditions?

2)                     Will the big companies be willing to use the TEFs in paying for it?

3)                     An important question is how to design the testing scenarios to be impactful and what to measure and how to measure it (e.g. what would be acceptable by a user as KPI?)

Unit A.1 will be happy to receive your answers, please speak to M. Baldyga (contact details in his slides).

In the coming months we will concentrate on how we can support matchmaking and how we can progress the deployment of business perspectives. The next webinar is planned for July.

On May 28th the Study on Industry Agreements will organize a workshop (by invitation only) on Policy recommendations for industry agreements in current and future digital value chains and their impact on European competitiveness

The presentations gathered different perspectives, from users and providers, and from SMEs.

Recording of the event


MDS-WS_2021-05-10_02_EC presentation - collaboration MDS-other initiatives
MDS-WS_2021-05-10_06_Smart Supply Network Manufacturing Data Spaces
MDS-WS_2021-05-10_09_AI TEFs for manufacturing