Development roadmap

The development roadmap looks at what the initial focus points are for the experiment and what focus areas could be explored and further developed in the future.

Initial experiment focus

The initial experiment is entirely focused on learning as much as possible about operating a contributor funding process. This experiment has been created to explore the potential effectiveness of open source contributor funding. Several of the suggested approaches that emerged from the funding process analysis will be trialled in this experiment. Many of these suggestions are highlighted below. Experimenting with new approaches whilst keeping the costs as low as possible will help with maximising the cost efficiency for learning as much as possible about contributor funding. This experiment should help with generating a large amount of data that can be further analysed to make comparisons with other funding processes. The key components of this initial experiment include:

• Community prioritisation suggestions - A public priority suggestion board will help with experimenting with independent contribution systems which can help with making the funding process more dynamic and flexible to sudden changes. It will be insightful to see what priorities the community suggests and which priorities they upvote during the funding process. It will also be insightful to see how contributors respond to these suggestions. A separate process for handling priority suggestions means that preferences and opinions from the community will be captured at any stage during the funding process. A separate and ongoing priority process can help to enable the community to contribute in the way they want to and as often as they like.

• Contributor profiles - Contributors will share personal and professional information about themselves to be considered as a candidate. Over time this will help with learning about what information is really necessary for voters to make an informed decision about which contributors could generate the most impact.

• Contributor voter selection - Expressive approval voting can be experimented with during the contributor selection process. Voter feedback and the voting results data will help with learning about how easy it is to use this suggested voting system. Delegated idea selection is where contributors are selected and funded to then decide themselves which ideas they will execute. Some experiments might choose to experiment with this suggested decision approach, whilst other experiments might initially have the founding entities decide what contributors will work on.

• Contribution task board - A simple contribution task board is a good starting point for exploring how ideas can be planned and executed in a public space. It would be useful to experiment with a more complete idea based system in the future that enables contributors and community members to share draft ideas that can be improved over time with collaboration until they are ready for execution. For now a simple contribution task board will suffice for this experiment.

• Contribution attestations - Attestations should be useful for the contributions that are not digitally recorded. Contributors can make requests to other people to submit attestations about their own contribution efforts so that there is more evidence that the contributor actually made a certain contribution. This process will be useful for learning about what kind of attestations people make about other people's contributions and how these contributions could be more easily recorded and verified in the future.

• Contribution logs - Individual time based monthly contribution logs can be trialled in this experiment to see how easy this approach is for contributors and how effective it is for recording and verifying contribution efforts. Over time this will help with identifying what contribution efforts should be recorded and presented. This experiment can also help with seeing how easy it is to identify good or poor performers based on their contribution logs and how accurate or limiting this approach is for assessing overall performance. Both contribution logs and contributor peer review responses will help with creating a strong foundation for learning about measuring contributor impact. Measuring contributor impact could end up being one of the more reliable and effective ways to reward people for generating impact.

• Contributor peer reviews & feedback - A simple feedback process will help with documenting people's opinions and experiences with other contributors that they worked with. Community members and other teams may also want to give feedback to the contributors who were funded. This information should be highly insightful for learning about how contributors have collaborated with others during the funding process and what impact they generated overall. This feedback should help with revealing some of the overall sentiments about the funding process and how it performed. Responses that come out of these reviews and feedback should be insightful for thinking about how a contributor's impact could be measured.

Future development ideas

After the initial experiment is completed there will be a number of learnings that can be made by analysing the data that has been created and collected. These insights can help with guiding future experiments to continue learning about contributor funding. As effective approaches emerge the next step will be to start developing more complete solutions that incorporate the learnings from initial experiments. In a rough order of priority some of these potential areas of development could include:

• Contributor profiles - Identity solutions could help with making contributor profiles for storing and sharing personal and professional information about a contributor. Contributors would then be able to create their own identity profile which can showcase their contributions and involvement in each ecosystem.

• Contribution logs - Contribution logs can be increasingly automated over time to make it easier and quicker for contributors to record and showcase their contribution outputs. Tools and libraries that are already being developed in the industry could be directly integrated into a contributor funding process to improve how contribution logs are recorded.

• Voting systems - Voting systems can be developed or integrated into the funding process to replace the manual solution that is initially being used for the experiment. The initial experiments should help to identify any improvements that might be necessary before a voting system is properly developed.

• Contribution workflow - Tools that help with managing and voting on how contributors work on a daily basis and make decisions about who works on what and how an idea gets executed.

• Contributor peer review & feedback - Solutions that help with enabling contributors and community members to more easily review other contributors performance and provide feedback about their contributions or interactions they've had with them.

• Idea coordination & discussion - Systems that enable the community and contributors to better suggest, coordinate and discuss ideas that they could execute within the ecosystem.

• Idea selection - A voting solution that enables the community and contributors to share their opinions and preferences about which ideas they believe are the most promising to work on at that point in time. Solutions that will improve upon the initial task management solutions used in this suggested experiment will be those that can help to take an idea from the draft stages all the way through to the execution stage in a collaborative manner.

• Priority coordination & discussion - Systems that enable the community and contributors to better suggest and discuss the priorities they believe are the most important for the ecosystem to focus on.

• Priority selection - A voting solution that enables the community and contributors to share their opinions and preferences about which priorities they believe are the most important for the ecosystem. The main problem with using solutions such as Canny is that these priority suggestions would not be on chain in. the ecosystem. Participating users might not necessarily be community members so future solutions will be more directly connected to the accounts and users in the ecosystem.