It is worthwhile for research funding to stimulate collaboration with third parties without the participants or their roles being part of a fixed plan in advance. The experiences gained are unique – and they are indispensable if we are to move forward with the dissemination of open data and open science practices. This paper will derive this from our own experiences – experiences that we at the Open Science Lab have gained in numerous third-party funded projects over the past years.
How and why should one try to raise third-party funding to finance one’s own research ideas? – There is a traditional notion that the “excellence” of a research project can be measured by its (mis)success in attracting external funding, analogous to its success in publishing in renowned journals. We repeatedly encounter opinions on the topic of third-party funding that are positive or critical of this established notion. 
The funding agencies, on the other hand, would prefer to turn the discussion in another direction: Instead of continuing to work on the traditional idea, which is now often and justifiably doubted, they now want their funding programmes to be measured, for example, by how they contribute to sustainable development  – indirectly, for example, because the type of funding encourages the research process or research results to be widely shared with the digital public (open science), or to allow participation throughout the entire research process (citizen science).
And this is where we feel directly addressed. We want to share here an observation we have gained in various funded information science research, development and participation projects of the Open Science Lab (OSL) at TIB.
We observe a quality of funding programmes that is currently (to our knowledge) hardly considered systematically. Some funding programmes allow, or even encourage, working together with third parties – with the particularity that at the beginning of the funding it is not yet clear who this will be or what roles will be taken on. Let’s call it, with the help of well-sounding buzzwords: Agile project collaboration based on publicly shared data and methods.
Particularly relevant in the context of our two main topics, Open Research Information and Open Cultural Heritage: these can be collaborations that are based on the new cooperation partners venturing a step outside, e.g. making digitised material available to the public for the first time, or bringing their own knowledge into the form of open digital knowledge resources.
- Coding da Vinci is an example of project funding with such effects. In our Lower Saxony 2020 implementation, 37 Lower Saxony cultural and scientific institutions – such as museums – took the step outside as part of our cultural data hackathon. For many of them it was their first Open Data experience ever – and for all of them it was an inspiring, confidence-building experience of working with creatives and developers. In addition, the threshold for the cultural institutions to raise their own third-party funds was removed. This hurdle alone can be considerable, especially because the (in itself banal, but at least learnable) craft of acquiring third-party funding is fraught with some sometimes complicating assessments and opinions, see above.
- In a cooperation between the Open Science Lab and the Academy for Public Health in 2019, funded by the Federal Ministry of Health, an open method was used that had already been practised and refined in many book projects at the OSL over many years: a “book sprint”. Together with the Academy and a network of experts, a whole series of textbooks was produced for the first time in a “marathon”. We observed a transfer that surprised everyone involved. After only three iterations of the sprints, the academy had learned the method and was able to carry it out independently. (Cf. Lambert Heller’s statement in the OER podcast with Dr. Ute Teichert, from minute 22, in German) However, this did not lead to the Open Science Lab becoming “redundant”, but, on the contrary, inspired joint plans for better infrastructures and new use cases for the open method Book Sprint.
When discussing openness (without having had corresponding experiences of our own), we always encounter vague fears about deficits:
- Can a cooperation be valuable if it is “only” based on data or methods that are freely available to everyone anyway?
- Are there even professionals who reliably deal with such open data and methods?
- Can loss of control and imponderables associated with the release of formerly “own” knowledge, own data or methods be compensated at all by other possible advantages?
With collaboration on the basis of freely accessible data and methods, we regularly have our own experiences that have made such fears seem to disappear by themselves. Here we see again and again that typical reservations can in principle be addressed by argument, e.g. by talking about the relevant experiences of third parties on the basis of concrete facts and data. This can always be useful as a supplement. However, to put it figuratively, talking about swimming technique falls far short of stepping into the (non-swimmer) pool, and it becomes apparent that the actual learning to swim takes place outside, in open waters.
But we would go one step further and question the strict clocking through of projects with meticulously planned deliverables etc.. Because through the omission of planning made in advance,
- new ideas fit better into a project, depending on the current circumstances.
- While applications for third-party funding and other projects that are planned long in advance come “from above”, the often loose, limited cooperation opens up greater participation “from below”. Cooperations can become grassroots projects, so to speak.
- Furthermore, greater openness is possible for potential project collaborators who do not normally submit research proposals, from smaller institutions to Citizen Science.
- All of the above points, the easier introduction of new ideas, as well as the stronger participation of new actors in the project, are mutually beneficial.
We hope that project funders will provide more incentives in this direction. Instead of letting funders pursue a project goal alone, they should be encouraged to put part of their project budget into open, not pre-fixed collaborations – and to systematically contribute to the emergence of such collaborations through timely and sustained opening, both of data and of their own methods and plans.
We ask ourselves:
- Which application scenarios with open data and open methods should be promoted to support agile collaboration and taking on new roles and responsibilities?
- What frameworks or incentives can help?
- What studies do we need to better understand how organisations and individuals learn and adopt new open skills and roles?
 Binswanger M. (2014) Excellence by Nonsense: The Competition for Publications in Modern Science. In: Bartling S., Friesike S. (eds) Opening Science. Springer, Cham. https://doi.org/10.1007/978-3-319-00026-8_3
 Mayer, K. and Schuch, K. (2019): Fostering the Sustainable Development Goals in Horizon 2020. Report for the Austrian Federal Ministry of Education, Science and Research. Vienna, February 2019. https://doi.org/10.22163/fteval.2019.416