Data Labs 2020 Virtual Research Experience for Undergraduates (REU)
This summer, the Ocean Data Labs team, in partnership with Rutgers RIOS, organized a virtual 8-week REU experience for 16 students across the country, including Alaska, Puerto Rico and Guam!. Find out more about the workshop, group projects and final research presentations below. You can also check out the article Eight weeks of intensive virtual learning on the OOI website and our cool REU Participant Map to see where everyone is from.
Final Presentations and Posters
Virtual Symposium, July 30 and 31, 3pm EDT
Presentation Schedule
Student | Mentor |
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Bailey Armos (Data Labs) University of Washington What drives variability in nitrate concentration off the Oregon coast? |
Ed Dever Oregon State University |
Paulina Cadena (Data Labs) California State University – Monterey Bay Teaching Oceanography with Comics |
Mikelle Nuwer and Cheryl Greengrove University of Washington |
Margot Chisolm (Data Labs) Middlebury College Seasonality of SAR Clades in a Temperate, Estuarine Environment |
Liz Harvey University of New Hampshire |
Kendra Devereux (Data Labs) The College of Wooster Estimating groundwater recharge rates over the Contiguous United States |
Chris Russoniello West Virginia University |
Nikko Galanto (RIOS) University of Guam |
Oscar Schofield Rutgers University |
Patricia N. Vidal Geraldino (Data Labs) Universidad Ana G. Méndez Response and Recovery of Sea Surface Temperature Near Puerto Rico to Hurricanes Irma and Maria, September 2017 |
Rich Dixon Texas State University |
Alondra German (Data Labs) Napa Valley College Seasonal Variability of Phytoplankton Biomass on the Oregon Shelf |
Kristen Fogaren Oregon State University |
Trevor Greenwood (RIOS) Millikin University Venting Distribution Mapping of the ASHES Vent Field through ImageJ |
Karen Bemis Rutgers University |
Kenichi Hirose (RIOS) Stockton University Estimating Capture Efficiency of a Survey Dredge for Atlantic Sea Scallops |
Daphne Munroe Rutgers University |
Doreen Leavitt (Data Labs) University of Alaska Southeast |
Ari Friedlaender UC Santa Cruz |
Samikshya Poudel (RIOS) Hudson County Community College Impact of spawning time and depth on larval transport by the Gulf Stream |
Jessica Carriere-Garwood, Heidi Fuchs, and Robert Chant Rutgers University |
Andrea Selkow (Data Labs) Austin College Low Dissolved Oxygen off Washington and Oregon Coast Impacted by Upwelling in 2017 |
Tom Connolly Moss Landing Marine Lab |
Lydia Sgouros (Data Labs) Case Western Reserve University Vertical Zooplankton Distribution on Continental Slope off Oregon Coast |
Ed Dever Oregon State University |
Alison Thorson (RIOS) Sarah Lawrence College Ocean pCO2 Variability and Drivers at the US Atlantic Coastal Pioneer Array |
Rachel Eveleth Oberlin College |
Brianna Velasco (Data Labs) Humboldt State University Magnitude and Drivers of the Seasonal Cycle and Interannual Variability of pCO2 in the Washington Coast OOI Endurance Array |
Rachel Eveleth Oberlin College |
Kathryn Zic (RIOS) The Ohio State University |
(2-week participant) |
Introduction
There are a growing number of NSF sponsored research programs that collect high volumes of data, such as the Ocean Observing Initiative (OOI) and the Long-term Ecological Research Program (LTER). These geoscience programs are using advanced technologies, including cabled systems, autonomous gliders, and sophisticated buoy sensor systems, that provide sustained ocean measurements to study climate variability, ocean circulation, ecosystem dynamics, air-sea exchange, seafloor processes, and plate-scale geodynamics for the coming decades.
Building data literacy and critical thinking skills utilizing large observatory-based datasets are important for the next generation of scientists, but these skills can be very challenging for students to develop for many reasons, including a shift from familiar small-scale to unfamiliar larger-scale data analysis tools, from hands-on experiences to utilizing data collected by others where metadata is needed to gain context about observations, and from simple to complex lines of reasoning.
In this summer research experience, selected undergraduates will work virtually with faculty mentors across the country to build their capacity to work with large online and openly accessible data sets. The 8-week research experience will include a 2-week professional development program (co-facilitated with Rutgers RIOS) and a 6-week intensive research project under the guidance of a faculty mentor.
Goals
By the end of this experience, participants will:
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- Develop and apply their data analysis skills using Python notebooks to access, analyze, and present ocean data.
- Learn about the variety of ocean data collection methodologies and datasets available to oceanographers.
- Participate in a variety of professional development sessions, including scientific question development, science communication, the graduate school process, and Diversity, Inclusion, and Research Ethics.
- Have the opportunity to participate in Career and Graduate Student Panels.
- Develop, carry-out, and summarize a research experience using an online dataset, under the guidance of a faculty mentor. (8-week participants only)
2-Week Professional Development Workshop (June 8-19)
Workshop sessions will be held between 3pm and 6:30pm Eastern, with a 30-minute break.
Date | Topic, Objectives & Activities | Followup Activities |
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Monday June 8 | Session 1a: Introductions & Ice Breakers (Janice & Josh) Objective: Get to know your cohort, the organizers and maybe a little more about yourself. |
Schedule a “get to know you” session with your mentor, if you haven’t already. (8-week participants only) |
Session 1b: Program Overview (Josh & Janice) Objective: Share more details on the program timeline, goals and expectations for this experience, and specifics about this two-week workshop. |
Journal: Reflect on what skills you want to learn in this workshop and internship. | |
Tuesday June 9 | Session 2a: How to ask a testable question (Janice) Objective: Explore how to ask testable questions and work in small groups to use the Question Formulation Technique (QFT). |
Watch the Tools of Science video on Testable Questions.
Journal: How does it relate to the QFT technique?
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Session 2b: The Wonderful World of Data (Daphne & Josh) Objective: Discover the array of ocean observation sensors and platforms, and the opportunities to conduct research using large oceanographic datasets. Understand the role of continuous datasets in providing context to discrete data. |
Practice using QFT and SMART techniques: Explore the NDBC web site and then generate 1-2 testable questions and identify the dataset(s) you could use to answer them. | |
Wednesday June 10 | Session 3a: Data Analysis I – Intro to Python & Accessing Data (Sage) Objective: Learn how to create python notebooks (in Google Colab) to develop your own data processing scripts and understand the value of this approach for reproducible research. Practice with some basic python scripts to load and plot meteorological data from NDBC. |
Continue to work with the example Python notebook and use the Slack channel for any questions. |
Session 3b: Science Communication Overview (Dr. Silke Severmann, Rutgers University) Objective: Review the various styles of science communication and reflect on best practices. |
Preview Career Panelists (link posted to Slack on Wednesday night). Rank your preferences and come up with 1-2 questions for each panelist you’d like to meet. | |
Thursday June 11 | Session 4a: Data Analysis II – Data Visualization Formats (Sage) Objective: Learn basic coding techniques to create data visualizations common in oceanography, including timeseries graphs, profile plots, scatterplots, TS diagrams, and transect plots. Discover how to adjust basic plot attributes, like lines, colors, markers, labels, titles, legends and subplots. Get an introduction to profiling ARGO and Glider datasets. |
Practice your skills using the Python notebooks and datasets, and use the Slack channel for any questions.
Submit Career Panelist survey by Midnight EDT Thursday. |
Session 4b: Group Project Starter Objective: Form small group project teams to explore data and begin to develop your own testable question. |
Begin working with your group on your research project. Plan how to tackle different tasks and when to have collaborative meetings. | |
Friday June 12 | Session 5a: Career Panel Session (Janine) Objective: Meet a panel of marine science professionals who have diverse backgrounds and careers, and participate in more in-depth discussions in a series of breakout rooms with each professional. |
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Session 5b: Data Analysis III – Analysis Techniques (Sage) Objective: Gain experience with some additional python data processing techniques, including basic statistics (mean, std, min, max, percentile), daily/monthly averaging (via resample), daily/annual variability (via groupby), anomaly calculation, correlation, and regression fitting. |
Continue group project work and prepare one slide for Monday highlighting your goal and progress. | |
Monday June 15 | Session 6a: Mid-Workshop Review Objective: Quick recap of where we are and where we’re going. |
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Session 6b: Work in groups with faculty supervision Objective: Organize your team around a testable question, dataset and analysis. Present your project plan to the entire group. |
Come up with a list of 5 questions about graduate school and the admissions process. | |
Tuesday June 16 | Session 7a: Getting into Grad School (Daphne) Objective: Discuss various aspects of the graduate school application process and how to identify the graduate program that best fits your goals. |
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Session 7b: Graduate Student Panel (Janine) Objective: Meet with a group of Rutgers marine science graduate students who have diverse backgrounds and research interests. Find out what it’s like to be a graduate student in this relaxed conversational setting. |
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Wednesday June 17 | Session 8a: Diversity, Equity and Inclusion (presented by the 2020 NSF Ocean Sciences REU) Objective: Participate in this discussion led by a mentor from the national Virtual REU program.
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Session 8b: How (not) to give an effective science presentation (Dr. Oscar Schofield, Rutgers University) Objective: Understand the best practices for delivering science presentations in this demonstration of what NOT to do. |
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Thursday June 18 | Session 9: Working session to finalize presentations and review slides with facilitators Objective: Finalize your data analysis and presentation. |
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Friday June 19 | Session 10a: Group Presentations Objective: Each group will have an opportunity to present their work.
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Session 10b: Program Wrap-up & Additional Resources (Josh & Janice) Objective: Celebration and review of resources available to help you explore your interest in marine science. |
6-Week Research Experience (June 22 – July 31)
Date | Topic, Objectives & Activities |
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June 22
3pm pm EDT |
The OOI Today: An introduction to its history and the science it supports Objective: Understand how the OOI is designed and what research questions it can support
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Quick-start to Accessing and Visualizing OOI Data using Python Objective: Explore Python as a tool to access OOI data
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June 29
3pm EDT |
Virtual Lab Group Meeting – Research Project Updates Share your research project plans and hear about what everyone else is planning to do.Prepare a powerpoint slide to share (feel free to use this template or design your own!) |
TBD | Additional Workshop Sessions Focusing on OOI Science, programming, additional data processing techniques, and research project development as needed. |
June 23 through July 24 |
Research Project Work
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July 30, 3pm EDT and July 31, 3pm EDT | Virtual Symposium
Celebrate your accomplishments! Final project presentations (5-minute pre-recorded highlight talks with 10-minute discussion); posters are available to preview in the Participant List. Click here for final schedule. |
Rutgers University Facilitators
- Janice McDonnell, Associate Professor and Data Labs PI
- Sage Lichtenwalner (@visualocean), Research Programmer and Data Labs Co-PI
- Christine Bean, Research Assistant and Data Labs Project Coordinator
- Josh Kohut, Professor & RIOS Co-PI
- Daphne Munroe, Associate Professor and & RIOS Co-PI
- Anthony Vastano, Lab Manager & RIOS Student Lead
- Janine Barr, Graduate Student and RIOS Assistant Lead