over the past 6-12 months the co-authors of this post have been involved in setting up Germany's largest COVID-19 study called National Pandemic Cohort Network (NAPKON). NAPKON is a subproject of the Network University Medicine (NUM) which was financed with 150 Million Euro in 2020 by the Federal Ministry of Education and Research in the context of the emerging COVID-19 pandemic in Germany. NAPKON recruits COVID-19 positive patients in an unusually comprehensive data and biosample visit schedule. Over 1000 individuals across Germany are involved in various ways: local study sites, central coordination or expert groups for one of over 25 medical specialities.
We have been the primary developers of the project management IT infrastructure for NAPKON. By connecting multiple open-source software projects we created what we currently call a "Research Project Suite". It currently includes
- Group management
- with synchronization across all services
- with decentralized group management options
- with hierarchiycal dependencies
- Mailing lists
- Collaborative Cloud space
- Admin Interface for User Management
- Project Management tools (Tasks, Gantt charts etc)
- Coherent Header across services
Software used includes Keycloak, Nextcloud, OnlyOffice, Sympa, OpenProject, Discourse, Wordpress and many self developed scripts. It is thus similar to proprietary services such as Google Suite or Microsoft Teams but allows much more customization to our needs.
Our Research Project Suite has now been deployed for NAPKON and, ORCHESTRA (a large EU funded COVID-19 study) and is in a test phase for 2 other projects. A release under an open-source licence is planned soon and much work of the past weeks has been invested into making the software easy to deploy for outsiders.
As we are currently in the process of implementing software to poll users as requested by the project coordination we were considering ways to embed tools for improved institutional decision making into our software. We have brainstormed some ideas what we could implement:
- Implementation of prediction tools (e.g. by leveraging work of foretold.io)
- Implementation of Models for uncertainty (e.g. by leveraging more work of getguesstimate)
- Implementation of decision guidance tools (e.g. possibly with clearerthinking.org)
- Transparency by providing lists of all past polls
- Nudging people to make great polls by facilitating steelmanning arguments / Standard use of approval voting / transparency to the community / ... (e.g. by using an adapted Loomio)
It is obvious that all the proposed points above need careful investigation and adaptation to the typical workflows of the scientific community.
We are very interested in the thoughts of the Improving-Institutional-Decision-Making Community here in the forum regarding effective strategies to embed tools for better decision making into the very software that is used by a (scientific) community. Please help us to understand
- In what ways could we nudge people to make better decisions with our platform? What is low hanging fruit, what is the holy grail?
- What are well established best practices in the IIDM space that have been implemented elsewhere already?
- Is this worth the effort or shall we simply provide a project platform that works?
- What are important pitfalls we ought to be aware of?
Thank you very much in advance.