The scientist Neil DeGrasse Tyson has a practiced ability to break down complex subjects for those not trained in scientific thinking or its specialized vocabulary. In an introduction to an online learning platform, Tyson says, “the trick to scientific breakthroughs is to know enough about a subject to think you're right, but not enough about a subject to know you’re wrong.” At the Open Environmental Data Project we are not aiming for a scientific breakthrough, but we are designing social and technical frameworks that will revolutionize the way we store, verify and use environmental data. Shannon and I have years of experience in the field known as “community science,” a process which equips non-professionals with the scientific method and new technological tools to investigate environmental problems. Our experience has provided us with enough perspective on the problems in the field, and therefore the ability to begin to see some of the solutions. However, like Tyson notes, we know we could be wrong about our assumptions around those solutions.

Our initial approach to this project is akin to the strategic innovation methods utilized by prize and challenge initiatives like Conservation X Labs. A prize or challenge in an open innovation method which incentivizes people from a variety of different types of organizations to try and solve for a grand complex problem the world is facing. The organization running the challenge awards money to the team that is able to solve the challenge. The first step in this method is to narrow down and clearly define the problem space that one wishes to spur innovations. For CXL their problem space was addressing declines in freshwater biodiversity and the strategic innovation process resulted in addressing the topic of Artisanal Gold Mining.  

This is where the Open Environmental Data Project will begin. We will define, refine and articulate the problem space: addressing barriers to realizing a diverse and meaningfully open environmental data ecosystem. After the problem space is clearly articulated, the next step is to outline the constraints or the barriers to a solution within that problem space. Once these are identified we can articulate our assumptions about those constraints and begin to design our solutions with clarity that we are solving for the right problem.

This approach is messier and more complicated than we can summarize in a single paragraph, but to illustrate let’s walk through a modern example. At this writing, the COVID-19 pandemic in the United States has caused millions of workers to lose their jobs. Processing unemployment benefits for millions of people is proving to be difficult because there aren’t enough claims examiners to process the claims. At this point, one might determine that the solution is to hire and train more staff for unemployment offices.

However, if we walk through this problem space, is it really the number of staffers that we need to solve for? The problem statement could be refined further to ask what are the duties of the staff? Could some of those duties be streamlined? If so, what are the constraints to streamlining them? Is it a technical problem such as interoperability capabilities, or an organizational one like the authority to process claims? Once one begins to look closer, things get messier and the proposed simple solution becomes more complex. The ideal goal is that once this strategic innovation process is complete the solution one realizes is more efficient, relevant and works for the greatest number of people.

At the heart of this process is the desire and commitment to ensure that our solutions will work for a variety of actors who create, need access to, and use environmental data for enforcement, regulation, policy, protection and scientific research.

As we define and refine the problem space we will share what we learn through our blog in the hope that other actors will see opportunities to partner with us and leverage our work. At the end of this process we will invite knowledgeable users to evaluate our proposed solutions.

During the spring and into the summer of 2020 we plan to interview lawyers, scientists, non-profit directors, engineers, journalists, philanthropists, technologists, community members, and local, state and national government employees.