A queue-poll extension and DataSHIELD: Standardised, monitored, indirect and secure access to sensitive data - Gründner, Julian; Prokosch, Hans-Ulrich; Schindler, Sebastian; Lenz, Stefan; Binder, Harald (Proceedings of the EFMI 2019 Special Topic Conference, 2019)
Analyzing data across hospitals and institutions without the data leaving the hospitals and adding institutions to a trusted network is an important part of privacy preserving data analysis. This work implements a queue-poll extension and integrates with DataSHIELD to allow for a standardized, monitored, indirect and secure access to data. The extension was created using the HTTP protocol and requests are not pushed into a participating institution but are sent to a server outside an institutional network. These requests are then pulled into the institution from within, executed and the response sent back to the outside server, which relays the request back to the request sender. We found that the requests were slower than a direct push request, but also that the integration of new institutions into the network was easily achieved. We propose that future work should focus on optimizing the monitoring and speed of the service. The service created here could reduce the barriers to entry for institutions to form an analysis network and can be used not only to drive analysis but also the sharing of resulting information and models.
CRIS-Team Scopus Importer:2019-05-09
Keywords: Data analysis network; Data governance; Distributed privacy preserving analysis; Machine-learning