At a time when consumer products are swimming in big data, we often struggle to get basic data on our oceans, wildlife, and public lands. Solutions are out there, but we need to translate and repurpose them to meet the needs of the people that manage, protect, and rely on our natural infrastructure.
What can be done?
The environmental sector needs better data collection, system design, and data analysis that works across institutional silos, answers real management questions, and engages the public in stewardship of our public resources. Data can point to solutions and facilitate conversations about where to work next, and why.
How the databranch is meeting the challenge:
The databranch seeks to make connections across the conservation and technology sectors to enable digital stewardship on a changing planet, by bringing high-quality design, computer science, and digital ingenuity to bear on conservation challenges and natural resource management. The databranch focuses on making it easier for managers, resource users, and the public to collect, analyze, and access essential data for smart decisions and long-term stewardship of our planet. The databranch offers three main services:
- Network building–The databranch seeks out, connects, and cultivates relationships among a wide array of professionals to expand the capacity of the natural resource management sector and catalyze new and innovative projects.
- Problem framing & design–Public agencies and user groups do not always have the capacity to assess their current data systems, conduct qualitative research to identify community needs, or explore a wide range of potential tools. The databranch can help with problem framing directly or by finding and matching you with experienced service designers and technical consultants.
- Project management–Once you’ve identified your project’s goals and scope, the databranch can help you fill out your team with researchers, designers, software engineers, and other skilled partners. The databranch also offers project management capacity to keep a project on track.
The databranch’s recent projects include:
- AI for fish in New England–A team of fisheries and machine learning experts co-created the N+1 fish, N+2 fish challenge where competitors developed algorithms to count, measure and identify fish species from video from fishing vessels. The open source results will help make it easier and faster to monitor fishing in New England, providing better data to sustain future fish populations.
- Improving U.S. Fisheries Data Systems–As part of a 2016 expert panel, the databranch helped develop recommendations to increase the accuracy, speed, and usability of U.S. fisheries data. The databranch supports ongoing projects to implement those recommendations.