The COVID-19 Future Operations Clearing Board is an interdisciplinary expert platform from the fields of science and the public sector. The aim of the Clearing Board, docked to the Federal Chancellery, is to exchange current information, data, and analyses that may be relevant for evidence-based strategic decisions on an interdisciplinary basis, as well as to bundle and expand findings to create a better foundation for overcoming the current corona crisis. Working groups exist in the areas of Health care, basic care, economy, and psychosocial issues. Participants contribute their expertise voluntarily to the COVID-19 Future Operations Clearing Board. 


Our experts from TU Wien Informatics assist with different research areas: Niki Popper was appointed to the advisory staff of the Coronavirus Task Force in the Ministry of Health. His model calculations were the basis for the Austrian government’s measures in the COVID 19 pandemic (see also COVID-19: Model Calculations by TU Wien Informatics Confirmed). Hannes Werthner was commissioned to draft a strategy paper on digitalization in Austria, taking into account factors such as the economic recovery and the dynamics of digitalization.

Andreas Rauber from the research unit Information and Software Engineering serves as the coordinator for the data management working group. Together with his team, he set up a high-security data infrastructure to allow better access to health data for research purposes.

Secure Data Infrastructure 

During the rise of the COVID-19 pandemic, the need for reliable, data-driven decisions was recognized right from the beginning. While national experts met in the COVID-19 Future Operations Clearing Board, it became evident that access to essential data was missing, since data owners could not share their data with experts, either due to privacy reasons or due to the massive risk involved in sharing commercially sensitive data. To break this deadlock, Andreas Rauber and his research team set up a high-security data infrastructure and respective processes to allow data owners to provide highly selective access (data visiting) to specific (fine-granular or aggregated, fingerprinted) subsets of data. The access applies to identified individuals for a limited time and will answer precisely defined questions accepted by the data owner. 

This infrastructure was set up and deployed within a timeframe of two weeks in order to support the work of the COVID-19 Future Operations Clearing Board. Rauber and his team could build on the experience gained by operating a very similar infrastructure in the health care sector for many years as part of the DEXHELPP project. As the new secure data infrastructure was set up in less than two weeks, it was kind of “handcrafted” and targeted the specific needs and local set-up. The availability of such infrastructure has met the interest of several parties who would like to provide such a data hosting/data visiting solution on their own. 

Open Data Portals

The project has been granted funding by the CoCreation Fund of the European Open Science Cloud to package and release these infrastructure components, and corresponding documentation to allow other parties to set-up and operate this infrastructure (or parts of it) in their environment, thus being able to maintain complete control over who can work with which pieces of their data within their server infrastructure, and without having to hand over data to external partners. 

Thus, the goal of this project is to clean up, document, and enhance this infrastructure to provide a fully documented, entirely open-source-based reference implementation of a secure data infrastructure (OSSDIP) supporting data visiting. This will empower institutions to establish a similar solution quickly. It will allow data not sharable via existing COVID-19 data portals to be used for analysis by enabling data owners to make their data visitable and usable in a fully controlled manner.

It is meant to complement existing Open Data portals and support access to sensitive and not openly sharable data. A fully open-source based solution consisting of pre-packaged scripts, components, and virtual machines will allow institutions to quickly set up a secure data infrastructure facilitating data visiting, thus providing a safe environment to enable researchers to work with sensitive data in the context of COVID-19 and beyond. 

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