Usecases that will be tested in the AMdEX fieldlab

Aircraft maintenance data market

Predictive Maintenance is a highly competitive field in many industries. Machine learning allows the industry to transition from fixed to variable maintenance intervals of parts through prediction. Training data is required for this, preferably on all global flight conditions, from arctic to desert conditions. There is no company that collects all this kind of data with its flights. AMdEX provides the possibility to set up data markets for maintenance data in which companies can share this data with each other.

Smart mobility data market

The transition to a new generation of smart mobility solutions requires advanced systems that use data fusion and prediction algorithms in order to respond to and anticipate the current situation at public transport nodes. However, these types of algorithms require many current and historical data sources which often are not available. The AMdEX infrastructure support mobility datamarkets in which data from different sources can be made available and accessible.

Materials data market

Madaster and Dexes are jointly developing a datamarket – the ‘Omgevingsregister’ – containing data on the built enivornment. Think of bridges, benches & lamposts including locations and components. The ‘Omgevingsregister’ can make a substantial contribution to area development and accelerate the transition to a circular economy. For this to happen data from a.o. engineering firms, governments and contractors need to be made accessible. The AMdEX infrastructure will be beneficial to the development of trust amongst partners.

Research data market

SURF and UvA will develop a prototype research data market for researchers and industry to collaborate. One of the cases focus specifically on sharing data from pedagogical and educational research to assess government policy. Ultimately this will also apply to the resulting data publications in which the entire lifecycle of data processing by various groups / industries can be traced, thus ensuring transparency in Open Science.

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