In August Openscapes held an advisory meeting, made possible with support from Mozilla. This event remotely convened a wide spectrum of biomedical open data science leaders to discuss how Openscapes could meet biomedical community needs. Openscapes’ roots are in environmental science but there has been increasing interest in becoming involved from the biomedical communities as well. This event started the conversation on topics we should consider to serve and strengthen biomedical and other communities more broadly. We have learned a tremendous amount from Mozilla Open Leaders and followed their best practices, including a stated code of conduct and multiple channels for participation, to create an inclusive space where everyone felt empowered to learn, share and ask questions.
Goal 1: Get to know each other through sharing leadership experiences
Due to COVID, the event was down-sized to a 2-hour call, so this asynchronous pre-work enabled us to reduce the synchronous time together. An exciting group of advisors (full list below) did “prework” before the meeting to get a sense of Openscapes’ vision, program, and momentum. This minimized spending in-person time on background in favor of hearing more from every participant.
The pre-work included everyone preparing a 5 minute statement where they shared with the group 1) an introduction to the person their work, their communities, their vision; 2) something they think/do/use/know that has improved their work, leadership, or impact that would benefit this group (could be process, technology, a cautionary tale…) and 3) what is the hardest part of your work. (The idea for that last question came from Kirstie Whitaker during a conversation at MozFest 2019).
Folks shared really interesting stories and perspectives building from their work. They lead trainings for researchers as well as for leadership, and build and support learning communities like Life Science Trainers, BioData Club, H3ABioNet, ASBCB, Community of Bioinformatics Software Developers, LIBD rstats club, Mozilla Open Leaders, and E2M2: Ecological and Epidemiological Modeling in Madagascar. From their statements we discussed further as a full group, asking questions, finding synergies, and developing a better understanding of some of the different approaches and efforts going on in this space.
Goal 3: how to improve Openscapes going forward
As break-out groups we focused on specific questions for Openscapes: What gaps or opportunities do you see for Openscapes? What could make Openscapes better suited for biomed communities? What existing needs do you see as unfilled in your biomed communities?
We talked about time as a big issue; how to help folks prioritize Openscapes/open data science with their other responsibilities? Advice here was to focus on the value exchange: illustrate how it’s worth the time spent, and be clear what they’ll be getting out of it. This means being very cognisant of the cost/labor involved in participation being very explicit of offering incentives and rewards. Encouraging people to make community activities and learning part of their job instead of something extra. With storytelling, focus on what the journey could look like for research teams: Your lab is doing A, B, C, this is what the journey to D, E, F looks like. On the other hand, you don’t want people to overcommit. So in addition to the value exchange, perhaps there is a lightweight version of Openscapes that could have different levels of lessons, messaging, intensity, etc.
We also discussed that identifying and naming explicit roles can be very effective – both at events but also within research teams.
Programmatically, we need to focus on what makes Openscapes unique, and communicating that it has staying power. People love to spin up new stuff but is this initiative going to stick around?
Next steps
It was so valuable to have the opportunity to learn from this group. There is a lot more to reflect on but one of the biggest take-homes for me was around communicating the vision and the services Openscapes provides, and how it fits in and complements other existing efforts. And also thinking about the value exchanges for participants. Engaging in open data science is not only about time and effort – which are substantial – but also about changing the way we’ve been working for our whole careers. Both time and change are hard, so how can we really focus on meeting scientists where they are and providing them with what they need.
Advisory Group
Abby Cabunoc Mayes (Twitter, web)
Leo Collado-Torres (Twitter,web)
Julie Lowndes (Twitter, web) (host)