Scope of the call
Main goals of the call
Leveraging potential in the academic research data landscape: Dealing with data in research contexts is as important as it is challenging. In many cases, good data practices encounter missing processes, awareness and culture to be sustainable, viable and impactful. While there have been some substantial investments in digitalization and data infrastructures in the last years (e.g. by the science and research ministry or through calls of FFG), there are often the human resources missing to fully capitalize on these investments. Good ideas cannot be realized because money and attention is missing. Furthermore, most universities and research institutions have developed digitalization and data strategies which need to be implemented via concrete projects and undertakings.
This call, thus, also aims to support institutions in their strategic capacity. In this context, it is crucial that applications developed are not one-offs, but need to be maintained and developed beyond the project duration.
- Projects should engage with current needs of the promotion of good data practices in a defined context in the form of "executable applications" for data in research. "Applications" should be understood widely as, e.g., software prototypes, transferable use cases, modelling etc. "Executable" means that the applications developed should be easily integrated into code or software environments in due course (either in existing or future data environments or workflows).
- Projects should provide applications witch deliver useful services to research/ers, either by rendering existing data processes more efficient or by providing tools that allow for new approaches. The outcomes of the projects shall support data collection for research and its further use, however, should not be tied to a specific research project but be of wider relevance.
- Projects can take place in any scientific area, i.e., is not limited to computer science. However, the nature of the projects requires the integration of IT competences into the projects.
What is the purpose of the applications developed?
The purpose of the applications should be directed towards supporting research activities in broad sense. It may connect to other tasks such as teaching, administration or third mission, but the focus should be on the development of applications for research activities.
What should be the output of the project?
Rather code than text, training or talking: The output should be concrete applications in the form of use cases, best practices, data sandboxes etc. and should include code, models, application prototypes and alike. These applications - based on their code-like nature - should have the potential to be implemented in data environments/workflows relatively easy.
Activities that do not count as output..,
... and are thus not eligible within this call:
- Research activities that produce data.
- The preparation of existing data sets for secondary / further use by other researchers. However, concrete data sets might be used to develop applications useful to other user groups.
- The creation of a network as a sole output
- Training and education activities as the sole output
- The procurement and installation of hardware
- Purely text-based outputs such as strategy papers or guidelines.
Defining potential user group
Projects need to define potential user groups of the application developed. Projects should have benefits for wider user groups beyond the context of the project. These user groups can located in the own institution, across institutions as well as for scientific communities.
Sustainability and impact
Proposals need to define how the applications developed can be maintained and further developed beyond the lifespan of the project itself. Projects should also define how their project links to institutional data / digitalization strategies as well as (potentially) to inter-university activities.
Dissemination and exploitation strategies
Proposals should define in what ways their outputs should be shared, be it either open or in form of licensing (monetarization). Keep in mind that WWTF prefers open science / open data approaches according to the FAIR principles, however, monetarization strategies might be justified in the context of specific projects. Applicants need to present a plan how project's achievements can be made visible to serve as role model.