For a long time, we've been chewing on the problems in Science. From smaller technical bugs to larger systemic issues like incentives and culture, it's very obvious now that scientists and citizens have to deal with a lot of obstacles.
A big part of our perspective comes our experience as scientists, but most of our frame of reference comes from what feels like an infinite number of in-real-life conversations with scientists from all walks of life over the last seven years. Some of these people include students, professors, administrators, communicators, teachers, policymakers, and more. Most of the time, there's a lot of overlap so we started jotting things down.
We've found ourselves constantly going back to this list. We first started it to help us organize and define the problem space. This list has helped us to sort and prioritize which problems we are focusing on, which ones are within the scope of being solvable, and how the problems interact with each other.
It's worth noting our bias that we most often come at it from the perspective of the scientist - the person doing the science. Science definitely isn't just producing new data or writing an article, it is also the act of consuming and reflecting on science created by yourself and others. It is also how the science is delivered, and the responsibility and care with which is it delivered. This is just something we remind ourselves of when fleshing out the list of Problems In Science™.
- Doing science by yourself can be slow
- Doing science by yourself can be lonely
- Scientists often do not own their own data or outputs
- Published scientific papers are often not open access
- Data and documentation are fragmented across many places causing unnecessary context switching and duplication of work
- Corporations profit off the free work of scientists by charging rent on knowledge
- Scientists cannot easily and cheaply self-publish
- Existing tools (e.g. Github, OneNote, Google Docs) are not designed for scientist collaboration
- There is no format for publishing web-first science content, and PDFs aren't ideal for distributing and searching through knowledge
- Most published science isn't (easily) reproducible
- There is no scientific code of conduct for bad behavior within the community
- Scientific knowledge should be a public good, not a commodity
This is definitely not a complete or finished list, but these are just a few things that come up frequently when talking to scientists.
We think these problems won't be solved technocratically; there is no single technical solution that will instantly make science not slow, or sustainably make all science content open access by default. We believe that these problems are solvable, but it will require broad scientist participation and big shifts in the cultural consensus of the values that drive science.
Where do we start? How do we use tools and wisdom we have today to build the tools to enable our behaviors to match our ideals. This is our best guess at values that we can use to address the list.
Joy: Focusing on making the the process of science enjoyable will encourage scientists to do more science. Perhaps it's also what originally drives a lot of people to get into science in the first place. Maybe making science fun will also encourage more people to become scientists.
Quality: Defining what quality means for each scientific community produces a common language for what verifies a meaningful result. When the citizens of science agree on a bar for quality, we build trust between all of the actors.
Openness: When existing knowledge is easy to search for scientists enjoy the work more, the quality of new work is improved, and the speed in which new knowledge is created hastens. Making published knowledge easy to access online and making unpublished knowledge easy to share influences the speed of value creation for the entire ecosystem.
We think of these three values as guides as we navigate through the problem space. We're not quite sure what the vehicle will look like, but this is what we'll use to guide our direction.
If we could start from scratch and reimagine an ideal version of Science that can take us farther, what dials and knobs could we reach for as we reimagine the machinery of science? There are many knobs, but these are the three knobs we like.
Participation: Who gets to participate in science and why? Instead of centralized gatekeepers on tolled-roads, what if our scientific networks and communities looked more like peer-to-peer, end-to-end connected commons? Let more people participate in all the phases of science: creation, consumption, and application.
Governance: Who gets to have a say in how science is managed and refereed? How do we keep the organizations and institutions in science accountable? Keep the power of management in the hands of the people who are actively engaged in doing and shepherding science. This governance responsibility is not a speculative good that can be purchased or traded.
Ownership: What is the upside of science and who gets to own it? Ownership of a thing usually looks like a corporation stock, but what if users in the community got to also collectively own the thing? What if scientists owned Elsevier or Wiley and received a part of the upside? By participating in and producing quality knowledge, the people doing the science increase the value of the resource, so give the proplr an opportunity to be owners of the resource.
By defining the problem space and questioning whether our foundations continue to serve science, we hope to find some sort of starting point towards how we can be better serve Science. This is just a snapshot of how we think, and we'll definitely come back to many of these ideas in future posts.
If these ideas resonate with you, please join the conversation!