OD24B:
Feast After the Famine: Discoveries Based on Big Data Posters


Session ID#: 28725

Session Description:
The quantity and variety of data and data science tools available to oceanographers, ecologists, and marine scientists continue to increase at exponential rates, revolutionizing hypothesis testing and enabling new discoveries.  How can new data and combinations of data from different sources be used to address significant, longstanding questions across the marine sciences? What insights can be gleaned by applying data science methods and tools to existing data sources?  This session welcomes submissions that highlight data science in the ocean sciences; these could include insights gained from technology (Argo floats, gliders, satellites, ocean observatories, flow cytometry, acoustics, etc.), methods (machine learning, statistical modeling, computer vision, image analysis, data management, visualization, etc.) or techniques (genomics, transcriptomics, proteomics, metabolomics, velocimetry, high resolution modeling, etc.) .  We also encourage submissions related to education including designing data science courses and improving reproducibility of results
Primary Chair:  Allison Smith-Mislan, University of Washington, School of Oceanography, Seattle, WA, United States
Co-chairs:  Julia Stewart Lowndes1, Sophie Clayton2 and James R Collins2, (1)Openscapes, San Francisco, United States(2)University of Washington, School of Oceanography, Seattle, WA, United States
Moderators:  Allison Smith-Mislan1, James R Collins1 and Sophie Clayton2, (1)University of Washington, School of Oceanography, Seattle, WA, United States(2)University of Washington, eScience Institute, Seattle, WA, United States
Student Paper Review Liaison:  Allison Smith-Mislan, University of Washington, School of Oceanography, Seattle, WA, United States
Index Terms:

1926 Geospatial [INFORMATICS]
4259 Ocean acoustics [OCEANOGRAPHY: GENERAL]
4815 Ecosystems, structure, dynamics, and modeling [OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL]
4855 Phytoplankton [OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL]
Cross-Topics:
  • IS - Ocean Observatories, Instrumentation and Sensing Technologies
  • PO - Physical Oceanography: Other

Abstracts Submitted to this Session:

Implementing unsupervised machine learning algorithms in the Spatial Temporal Oceanographic Query System (STOQS) (309482)
Rachel Kahn1, Mike McCann1 and Danelle E Cline2, (1)Monterey Bay Aquarium Research Institute, Moss Landing, CA, United States, (2)Monterey Bay Aquarium Research Institute, Moss Landing, United States
Ecological Marine Units as a Framework for Collaborative Data Science and Knowledge Discovery (309871)
Dawn J Wright, ESRI, Redlands, CA, United States, Roger G Sayre, U.S Geological Survey, Land Change Science Program, Reston, United States, Sean Breyer, Esri, Living Atlas of the World, Redlands, United States, Kevin A Butler, Environmental Systems Research Institute, Redlands, CA, United States, Keith VanGraafeiland, Environmental Systems Research Institute, Redlands, United States, Mark J. Costello, Faculty of Biosicences and Aquaculture, Bodo, Norway, Kathy Goodin, NatureServe, Science Division, Marine Program, Arlington, VA, United States, Maria Kavanaugh, Woods Hole Oceanographic Institution, Woods Hole, MA, United States, Noel Cressie, Jet Propulsion Laboratory, Pasadena, CA, United States, Zeenatul Basher, U.S Geological Survey, Washington, DC, United States, Peter T Harris, GRID-Arendal, Arendal, Norway and John M Guinotte, U.S. Fish and Wildlife Service, Ecological Services, Mountain Prairie Region 6, Lakewood, United States
Detecting Community Shifts in Phytoplankton Populations Using Statistical Learning (Invited) (321167)
Corinne Jones1, Sophie Clayton2,3, E. Virginia Armbrust4 and Zaid Harchaoui1,3, (1)University of Washington, Statistics, Seattle, WA, United States, (2)University of Washington, School of Oceanography, Seattle, WA, United States, (3)University of Washington, eScience Institute, Seattle, WA, United States, (4)University of Washington, School of Oceanography, Seattle, United States
Spatial Reconstruction of Ocean Audio Data (326428)
Grady Kestler1, Shahrokh Yadegari1, Robert P Dziak2 and Adrienne Copeland3, (1)University of California San Diego, La Jolla, CA, United States, (2)NOAA Pacific Marine Environmental Laboratory, Seattle, WA, United States, (3)NOAA Office of Ocean Exploration and Research, Silver Spring, United States

See more of: Ocean Data Management