Vision—the potential for reorganizing scientific practices to support an open, inclusive, and engaging knowledge society.
Mission—how to design and implement a sustainable socio-technical system to support the vision.
The participants are experts from diverse fields and communities including:
Change management professionals.
How can future digital platform ecosystems be shaped in a sustainable way?
How can those ecosystems maximize the benefits for science? Particularly in the areas of:
– Good scientific practice.
– High-quality research.
– Reproducibility of results.
– Reuse of data.
– Acceleration and intensification of cooperation and communication.
How can those ecosystems maximize benefits for society, particularly in the areas of transparency, participation, and mission-oriented innovation?
How can an AI-centered, technology approach be used to encourage cultural support of new, inclusive forms of scientific practice?
How does AI become a risk or an enabler for research integrity?
How can we encourage and promote a broader and more mainstream understanding of informational sustainability?
How can we ensure that informational sustainability includes the long-term preservation of data and knowledge as well as key aspects of the U.N.’s Sustainable Development Goals?
How can we implement “sustainability-by-design” for e-infrastructures, particularly for lifecycle resources and energy consumption?
What are the most important paradigm shifts, incentives, and rewards to encourage cultural acceptance of open science?
A broad alliance of stakeholders is promoting the idea of reorganising our research landscape.
The Open Science movement has a lot of momentum in Europe, but various barriers and controversies caused by diverging interests are slowing things down.
The European Open Science Cloud (EOSC) and the Gaia-X project could establish a new data ecosystem at the intersection of science, economy, and society.
Such a data ecosystem and e-infrastructure will need to be carefully designed to tackle the structural problems of science and society.
Openness itself is not a sufficient end-state, as demonstrated in the FAIR principles (findability, accessibility, interoperability, reproducibility).
FAIR data is a necessary, but not a sufficient, condition for fundamental cultural change beyond the digital single market of Europe.
One of the visions for a European Public Sphere is to connect it to a value-based approach of digital sovereignty and Citizen Science. This can lead to reciprocal gains for science and society, although there are significant challenges.
All stakeholder groups must be included to drive a human-centric shift towards open, inclusive, and responsible research and innovation.
This type of social innovation requires collaboration between people and data and AI to develop knowledge tools.
A joint position paper from leading e-infrastructure stakeholders only addresses the EOSC and informational sustainability from a narrow perspective of funding and long-term preservation, despite other possible connections to sustainable development goals as part of Agenda 2030.
There is a gap that needs to be bridged between the Open Science Community and the growing conversation around digitalization and sustainability.
There also needs to be some myth-busting around the potential benefits and risks of AI, which is sometimes seen as a universal solution.
Instead, AI should be repositioned as needing a “reboot” towards an explainable, trustworthy, and ultimately sustainable socio-technical system.
The participants of the Roundtable agreed, that defining what "good" science is and which parts of it should be open/ accessible to the public is crucial in the discussion on reorganizing scientific practices.
Society, politics and companies will play an important role in this transformation, because an inclusive environment contains participation processes as well as sharing knowledge and data across disciplines and borders. Inclusiveness should always include diversity and equity and therefore involve all stakeholders without the conflict of some parties "owning" the scientific results because of funding. However, in this case, openness does not mean sharing everything and every part of the process. Science should be "as open as possible and as closed as necessary". High quality peer-review processes and suitable evaluation for different forms of science are needed before science communication should take place. The time-intensiveness need to be considered in creating this new framework of scientific practices and make "slow science" the standard instead of the current expectation of a high quantity of research in a short amount of time.
Among scientists, an increase in sharing data could contribute to the concept of "good" science, yet more data does not equal better science. That's why data sets need to be connected to their tools and methods to make sure the context is clear and hidden biases can be discovered more easily. Furthermore, the handling of data should play a crucial role in the education and create data ecosystems and data infrastructures managed by data stewards rather than AI. For this to become reality, data policies, strategies and governance on a EU level is essential. One question that emerged from this discussion is how to combine the scientific values of open science with societal values, such as data privacy and data protection?
A systemic change on a political and institutional level will be necessary to create the open, inclusive, and engaging knowledge society that individuals already dream of. The next steps in this process is to find a way to get to this defined goal.
Further results are currently being processed.