How to get funding for software Projects

Part A: Where and how to get funding?

There are some guides about funding of open source software projects:
- https://opensource.guide/getting-paid/#finding-funding-for-your-project
- https://github.com/nayafia/lemonade-stand

They can give a general overview for open source funding. They might have value for existing projects that need continous funding as these projects by demonstrating their use (Letters of support, Download/usage statistics, citation count etc), have a better chance of convincing external funders of the value they generate (even if only for the academic community). For funding requests supporting existing projects it might also help to detail what will be improved, what features will be added, and how the maintenance benefits the quality of the project.
However, in general it seems easier to obtain funding for new projects, since it seems that 'novel' ideas tend to be of greater interest for public funders.

Here, we will list several existing options for funds for software projects in (but not exclusively) academic settings:
For quantum projects, https://unitary.fund is a source of small (4000€) grants, that might be easily accessible.
For visibility and project improvements, Google Summer of Code and tweag open source fellowship offer a great way to get interested students, or with tweag even more professional coders into the project, test their potential (e.g. for a later masters/PhD) and get new contributors for a project. However, the support is for a rather short time (12 weeks).
In Germany, the DFG sometimes puts out calls for research software (e.g. 2016 call for sustainable research software development or 2019 call for quality management in research software)

Part B: How can we get more funding for scientific software?

Overall, we got the impression, that many software projects are funded by being hidden within larger grant proposals. While this works to get some funding, it leads to an undesired invisibility of research software development, which makes it difficult to get funding for projects. On the other hand decision makers seem to be aware, that software is necessary, and there are even calls which explicitly ask for details on what software funding there will be. As such, it seems important to get grant-writers to stop the practice of hiding or obfuscating software development in their grants but to explicictly list them in the requirements and/or goals of the grant.
To achieve this it would also be important to convince PIs that proper funding for research software development is important, and present the advantages of having permanent research software engineers.
Those include (but are not limited to):

• A RSE stays, and thus the knowledge about the code remains in house for future reference
• A RSE has a higher incentive to produce higher quality code, that stays useable even if they leave the institution
• Code development can be sped up if a RSE serves multiple groups by not having to replicate the same code multiple times (in contrast to individual PhDs/PostDocs who only code for "themselves")

A further argument, which needs some more work could be the time saved by employing RSEs. This would require a survey of PIs on how much tiem they, or their group spend on code development, and an estimate of how much time could be saved by employing specialists for some of the tasks. This data would also be important for higher level decision makers in order to show the value of RSEs in research. To this end, it would be good to obtain more and clearer statistics to demonstrate use and visbility as mentioned above. For some languages, download statistics can easily be obtained by package managers (e.g. conda/pip for python):

• Pip Download badge for git
• Conda download badge for git

We would need to check to what extend these are available for other languages. Another important thing to remember is to make citing software easy by putting it into code (e.g. a cite function), into the documentation, and in general make it easily findable (since often a lack of easy citability will lead to fewer citations). And in the end, citations are an important way to prove impact for future funding.

---

• What funding sources are available to software projects?

  • For the improvement of existing projects

    • Google summer of code, at least for students (both graduate and undergraduate)
      • Student projects can also lead to more visibility and additional contributors
    • tweag open source fellowship: https://boards.greenhouse.io/tweag/jobs/4638654002

  • For new projects

  • Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): 2016 call for sustainable research software development

  • 2019 call for quality management in research software

    Seems easier to get funding to make new software than maintaining older ones

• How did you get funding for your software project?

• Getting funding for a software project by embedding it into larger proposals.

  • How to best go about getting funding for software into a larger grant proposal?
    • Do write it in explicitly as software development. Not data analysis, or some other obfuscation.
  • Which calls are more likely to support these kind of mixed science/software approaches.
    • Potentially many, decision makers seem to be aware, it's more the PI's that need to put it in and not hide it.

Part B: How can we get more funding for scientific software?

• Who makes the decisions for public or industry funding of software projects, and could be approached to lobby for more funding?

• What arguments are there for funding open source/academic software projects?

• What arguments are there against public funding of software projects? (In order to be able to address those arguments)

• How to get the software funding into the light.

  • Get researchers to actually write software development into the proposals
  • Don't say "data analysis", write we develop software for the purpose

• How do we convince PIs that proper funding is necessary, when there is "free labor" from BSc/MSc students (and to some extent "existing" PhDs and postdocs)?

  • RSEs stays and has long-term perspective
    • PI might say: there will be new students when the old ones quit
    • But it takes a long time to redo it. +1
  • Quality of produced software

• Are there ways to quantify/measure how much time/funding is wasted on re-writing and re-learning old code? We might need this to convince PIs, stakeholders, funding agencies, …+1+1

  • Get Feedback from users (Letters of supports, proper citations).
  • Download/User counters
    • Pip Download badge for git
    • Conda download badge for git

• Write citation information into documentation to make it easier to cite.

  • We have a .cite() method
    ​​​​​​​​qutip.cite()
    

• Examples showcasing the use of the library (Sphinx gallery): https://pennylane.ai/qml/demos_research.html

• How do you justify "more funding" for an existing project.

  • Try to find non-served use-cases
  • Try to find improvements that can be done

• Clarify between Maintenance and New Development

• How does the time lag in the metrics play role for the "more funding"?