VREs are excellent environments to collaborate on research topics, to share data, methods and knowledge in projects at one affiliation as well as across national and continental boundaries. Quite a few mature solutions have evolved over the last 15 years and the usability of existing solutions has increased majorly. Two major trends can be observed regarding usability: one is the mostly black-box approach that allows beginners in a field to use complex scientific methods without having to become acquainted with complex research infrastructures but to be enabled to focus on research questions. The second trend are dashboards such as Jupyter that allow researchers to work with their own scripts and ease the connection to complex research infrastructures and portability. Both approaches might be supported by Artificial Intelligence (AI) or Virtual Reality (VR). FAIRness of VREs can address open sharing and trust challenges. The objective of this meeting is to discuss whether FAIRness of VREs is sufficient to increase trust in VREs while fostering critical thinking. 

Collaborative session notes: https://docs.google.com/document/d/1iZ3IFN9gzKriPCBSzY11wIuQff6rhx_biOlKvbZt9GE/edit?usp=sharing

0-10 min – Introduction to IG and FAIR4VRE working group (Sandra Gesing)
 

10-40 min – Panel – Why Trust and Critical Thinking in VREs is complementary (Moderator: Sandra Gesing, Panelist: Andreas Rauber, Zhiming Zhao)
Novel technologies such as AI and VR open exciting new opportunities to analyze and simulate data. While FAIRness of VREs can help to increase trust in the methods used, openly shared methods and data are often so complex that it is difficult to know whether results can be trusted. The panel will go into detail for the aspects of trust and critical thinking for VREs and their implications for the use of VREs.

40-90 min – Group discussion and preparing for new working group (Moderator: Kheeran Dharmawardena)

• Is FAIRness of VREs the basis for trusting results in VREs? Or does this apply for a subset of VREs?

• Which  knowledge acquisition and transfer skills  will we no longer need to teach/learn because machines will take care of it for us, and what will we need to learn instead?

• What are measures to improve trust in computational methods used in VREs?

• How to avoid “blind trust” in simulations – for example, created via AI and VR – for VREs?

This session is aimed at anyone who is or has been involved in using, developing or maintaining any form of online collaborative environment or their individual components.

In preparation for this meeting, attendees could refer to the notes from the previous sessions from past RDA Plenary meetings that focused more on understanding the commonalities and differences of the different VRE/SG/VL platforms from the different global regions and collaboration tools. Attendees could think about the challenges they face using and developing VREs especially under consideration of the aspects trust, security and privacy when incorporating novel technologies such as AI and VR.