Smart & privacy conserving infrastructures

Explore and develop intelligent, privacy-conserving infrastructures for sharing and (re)using (sensor) data that are collected at agricultural enterprises and/or for food safety, to enable a smart and circular agriculture

One of the biggest challenges for data driven science is the accessibility and reusability of data that are collected for specific research purposes. These data contain often (sensitive) information from external parties, and are collected to answer specific research questions without clear specifications whether the data can be used for other purposes too like multidisciplinary research for the bigger societal issues. However, sharing of these (sensitive) data still is in its infancy. This project aims at exploring shared, domain overarching, and privacy-conserving infrastructures that enables safe, efficient, and controlled mechanisms to share or re-use these data.

Such infrastructures will stimulate activities to integrate these data within and outside WUR, and support scientific data-driven research where data ownership and privacy issues will be guaranteed. In this project we worked to this goal by organizing a thinkathon. This event highlighted valuable connections between the difference science domains, and stimulated the use of a shared infrastructure within WUR. In addition, we worked on specific usecases to share data between different science groups, as well as usecases that collect realtime data from farms, and connect these with other sources within our outside the farm. In this project, the Agrodatacube (WENR) is connected with Akkerweb (WPR) and the methane data lake (WLR), as well as with JoinData and RVO. Akkerweb (WPR_ connected to the methane data lake (WLR) and BIN (WECR). The methane datalake (WLR) alse searched for methods to combine datastreams within a farm real-time. WFSR connected to datasources outside WUR, using an infrastructure based on the Personal Health Train. In 2021, we set-up a framework to structure the lessons learned from these use cases. To do so, we used the nine building blocks identified by iShare as essential for sharing data. The uscases that have been or will be worked on within this project will be used to summarize the knowledge build within each building block. This will be continued in 2022.