Usecases

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. Read this article for more info.

Homes, office- and public buildings get smarter every day, using sensors. Much of the generated data isn’t publicly available: it’s too private or commercially sensitive to share widely.
Anonymised data about building usage, empty soap dispensers, air-quality and presence of people would enable facility service providers and mobility planners to effectively manage crowds, cleaning buildings and public areas. AMdEX is working on sharing restricted sets of data, ensuring the privacy of building users.

Numerous sensors have been installed at the Marineterrein in Amsterdam, with a variety of owners (including the City of Amsterdam, research institutes, and others). The collected data wasn’t accessible to third parties, while businesses, artists, local authorities, journalists and residents have a need for it. In this case, the sensor data was made available to a variety of users under varying conditions and at various levels of detail. AMdEX supports both the data owner and individual user – for example a journalist – in sharing the data securely.

SURF and UvA are developing a Research Data Exchange (RDX) for researchers and industry to collaborate. One of the cases focus specifically on sharing data from pedagogical and educational research to assess government policy. Read the interview with AMdEX initiator Frans Oort (University of Amsterdam) explaining about the importance of the RDX usecase. This usecase 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.