We are pioneering a new language to understand our incredibly beautiful and complex world. A language that is forward-looking rather than retrospective, different from the words of historians and famed novelists. It is data science; and through it, we have the power to use insights from our past to build an unprecedented future. We need your help building that future. The National Data Science Bowl offers tremendous potential to modernize the way we understand and address a major challenges.
The first-ever National Data Science Bowl challenged participants to examine more than 100,000 underwater images. The data were available thanks to sophisticated image capture methods pioneered by Hatfield Marine Science Center and their research partners. Now they are faced with volumes of information that will take years to manually analyze—data collected over one day takes one year to manually analyze! The challenge for the data science community was developing an algorithm that would enable researchers to monitor ocean health at a speed and scale never before possible.
Like the smallest data point that can be the key to redefining an industry, plankton are key to Earth’s massively intricate ecosystems. A large and thriving plankton population is crucial. These organisms take 25% of CO2 released from burning fossil fuels every year. They also form the foundation for marine and terrestrial food chains. Because they are susceptible to small changes in temperature or water chemistry, plankton populations serve as an indicator for broader ocean health. A drop in plankton populations can be a predictor of devastating effects on our world.
More than 1,000 teams participated in the 2014/2015 National Data Science Bowl. They collectively submitted more than 15,000 solutions to the challenge. The algorithms they created are allowing rapid assessment of plankton population distributions and numbers, enabling the marine research community to monitor ocean health at an unprecedented speed and scale. These types of real-time insights have not been possible through manual identification and analysis and represent an important step forward in understanding as well as protecting the environment. The data science community benefited as well. Tutorials and sample code were used extensively for learning and skills development and insights from the competition helped advance the state of the art in computer vision and Deep Learning.
"We're excited to receive the winning algorithms from the National Data Science Bowl and to test and validate these proofs of concepts in our own labs. Our hope is that we will be able to expand upon this research and, eventually, make it an open source tool for the marine research community."
—Bob Cowen, Director Hatfield Marine Science Center
The top prize was awarded to Team Deep Sea, a team of deep learning specialists from Ghent University. They developed the most accurate classification algorithm, beating the current state of the art by more than 10%. Learn more about their algorithm, representing major advances for both the marine research and data science communities. The innovations don't stop there– Explore the other top-ranked entries from the 2014-2015 National Data Science Bowl.
Professor and Director of the Hatfield Marine Science Center at Oregon State University. Prior to OSU, he also held faculty positions at the University of Miami and SUNY Stonybrook. His research interests are focused on larval fish and the plankton communities upon which they depend. To better understand life on the time and space more...
Senior Research Associate and Co-developer of the In Situ Ichtyoplankton Imaging System. Even though his background is in fish biology, he has interests in new technologies and engineering used in the fields of biological and physical oceanography. His main contribution to the imaging system is the development of the more...
Postdoctoral Scholar at Oregon State University working with Drs. Bob Cowen and Su Sponaugle. Prior to moving to OSU, Kelly worked at the University of Southern Mississippi. She earned her PhD in marine science at the University of South Alabama and a Master's degree in fisheries and aquatic science from more...
PhD student using In Situ Ichtyoplankton Imaging System to study the ecology of jellyfish, larval fish, and other plankton in the ocean. She is interested in plankton community dynamics, specifically food-web interactions and the biophysical processes that cause fine-scale plankton aggregations. She hopes that this more...
Professor in the Department of Integrative Biology at Oregon State University. Inspired to pursue marine science while growing up in Thailand, Su has retained her love of tropical oceans by studying the processes associated with population replenishment of coral reef fishes. She is particularly interested in how young fish larvae grow and survive in the plankton and then find their more...
Bellamare, LLC, Hatfield Marine Science Center External Partner is involved with the design and manufacturing of the In Situ Ichtyoplankton Imaging System towed vehicles. He participates in the design of all systems of the instrument, using CAD modeling, drafting, and mechanical analysis more...
an independent federal agency that supports fundamental research and education across all fields of science and engineering. In fiscal year (FY) 2014, its budget is $7.2 billion. NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and other institutions. more...
Solving the previously impossible is not easy. You need a community to enable and empower your success. As a group we can share experiences, strategies, and information that will truly allow us to affect change at a global scale. The organizations that support the National Data Science Bowl form the underpinnings of that community.
We are searching for the next National Data Science Bowl challenge—a problem with the potential to change the world. We need you to share your ideas. If selected, the power of the entire data science community will be harnessed against it.
Submit your ideas to [email protected]. Include an overview of the problem, your contact information, a brief description of the data, and where it can be obtained.