June 20–25 | Virtual
Teaching science with big data
Teaching science with big data
June 20–25 | Virtual
This international meeting guides faculty on how to teach using web-based, free-access large data sets. How big is "big data"? Data that is so large, fast or complex that it's difficult or impossible to process using traditional methods.
Join us to learn these valuable teaching skills to prepare students for the future.
Sponsored by the ASBMB and the International Union of Biochemistry and Molecular Biology.
Registration and abstract submission opening soon.
Organizers
Preliminary schedule
Sessions offered at 10 a.m. and 10 p.m.
All times listed are U.S. Eastern Daylight Time (GMT-4)
Keynote
Investigating evolutionary relationships through cluster analysis using Juypter Notebook
Showing teachers how to analyze sequence sets using sequence analysis and visualization tools in order to help students to visualize connectivity between datasets.
Workshop: Facilitator introduction
Workshop: Practice a big data activity
Networking break
Spotlight talks selected from abstracts
Three 10 minute talks on best practices in teaching.
NOAA database resources
Faculty talk
Selected from abstracts from those who teach using big data.
Visualization of Top 8000’s protein dataset using RStudio
Apply different R visualization packages and display different design themes using R so that students can select type of visualization and use R to help them communicate an end result.
Workshop: Facilitator introduction
Workshop: Practice a big data activity
Networking break
Spotlight talks selected from abstracts
Three 10 minute talks on best practices in teaching.
NOAA database resources
Faculty talk
Selected from abstracts from those who teach using big data.
Pedagogy of working with climate big data using RStudio
Instructors will learn an approach they can use to guide students through working with large datasets that will increase their quantitative reasoning. We will compare climate data from different time periods to explore what is so different about current climate change.
Workshop: Facilitator introduction
Workshop: Practice a big data activity
Networking break
Spotlight talks selected from abstracts
Three 10 minute talks on best practices in teaching.
NOAA database resources
Faculty talk
Selected from abstracts from those who teach using big data.
Visualization of Top 8000’s protein dataset
Instructors will learn to load protein datasets into Jupyter Notebook, analyze them using Biopython and visualize the results.
Workshop: Facilitator introduction
Workshop: Practice a big data activity
Networking break
Spotlight talks selected from abstracts
Three 10 minute talks on best practices in teaching.
NOAA database resources
Faculty talk
Selected from abstracts from those who teach using big data.
Resources and implementation plans
Participants develop plans for implementation and find community of resources.
Workshop: National Oceanic and Atmospheric Administration (NOAA) environmental data and visualization resources
Workshop: Implementation plan development
Networking break
Workshop: Development plans report out
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Bios

Michael Lauer
Michael Lauer, M.D., is the deputy director for extramural research at the National Institutes of Health, where he serves as the principal scientific leader and advisor to the director of the NIH on all matters relating to the substance, quality and effectiveness of the NIH extramural research program and administration. He received education and training at Rensselaer Polytechnic Institute, Albany Medical College, Harvard Medical School, Harvard School of Public Health and the NHLBI’s Framingham Heart Study. He spent 14 years at Cleveland Clinic as professor of medicine, epidemiology, and biostatistics. During his tenure at the clinic, he led a federally funded internationally renowned clinical epidemiology program that applied big data from large-scale electronic health platforms to questions regarding the diagnosis and management of cardiovascular disease. From 2007 to 2015 he served as a division director at the National Heart, Lung and Blood Institute, where he promoted efforts to leverage big data infrastructure to enable high-efficiency population and clinical research, and efforts to adopt a research funding culture that reflected data-driven policy. He has received numerous awards including the NIH Equal Employment Opportunity Award of the Year and the Arthur S. Flemming Award for Exceptional Federal Service in recognition of his efforts to grow a culture of learning and accountability.

Alon Friedman
Alon Friedman, Ph.D., is an associate professor in the School of Information Science at the University of South Florida. He is an interdisciplinary researcher with a focus on visualization theory and the visualization of data. He uses different theoretical perspectives to organize data through a visualization lens. His current projects include Visual Peer Review and 'Peirce's sign theory as an open-source R package.’ His work has been published in the Journal of Information Visualization, Education and Information Technologies, and Technology, Pedagogy and Education. He has developed courses to teach open-source R and visual analytics to students across academic disciplines. Alon is an active member of the open R community member since 2010.

Wally Novak
Wally earned his Ph.D. in Chemistry and Chemical Biology from UCSF in the lab of Patsy Babbitt where he studied bioinformatics and enzymology. He went on to an NIH postdoctoral fellowship in structural biology at Brandeis University with Greg Petsko and Dagmar Ringe before landing at Wabash College. He holds the William J. and Wilma M. Haines Professorship in Chemistry and is currently serving as the Chair of the Division of Mathematics and Natural Sciences.

Catherine O'Reilly
Catherine O’Reilly is a professor at Illinois State University, where she teaches in the Department of Geography, Geology and the Environment. She has long been committed to providing undergraduate students with authentic experiences in science, both in the classroom and through research projects. She has been involved in Project EDDIE since its inception, and is currently leading one of grants that supports the project. Her research focuses on aquatic ecosystems, with an interest in human impacts and climate change. She has been involved in several large-scale collaborative projects through the Global Lake Ecological Observatory Network, as well as over a decade of research on Lake Tanganyika, East Africa. Her work has been reported in media such as the BBC, New York Times and National Geographic. Dr. O’Reilly has a B.A. from Carleton College and a Ph.D. from the University of Arizona. As part of the 2007 Intergovernmental Panel on Climate Change, Dr. O’Reilly shares the Nobel Peace Prize with Al Gore and 2000 other scientists.

Charlie Weiss
Charlie Weiss teaches chemistry and scientific computing at Augustana University in Sioux Falls, South Dakota. He earned his B.A. from Carleton College and Ph.D. from Northwestern University, and his areas of specialty have historically been catalysis and reaction mechanisms. In recent years, he has taken an interest in the processing, analysis, and visualization of experimental data using the Python programming language and Jupyter notebooks. In 2017, Charlie began teaching a scientific computing course aimed at providing chemistry students advanced data analysis skills and recently made his textbook for the course, Scientific Computing for Chemists, freely available on GitHub under a Creative Commons license. He has a particular interest in data visualization and digital graphics and is a proponent of using and teaching open source software and utilizing open educational resources.

Stephen Zepecki
Stephen Zepecki joined the National Oceanic and Atmospheric Administration in 2013 after serving as a certified secondary science educator in Connecticut and Washington, D.C., for ten years. NOAA collects 100k terabytes of remote sensing data each day, and it is Stephen’s job to sort and distribute data and resources to the public. Under NOAA’s Office of Education, Stephen supports outreach tasks by distributing environmental data and resources using NOAA’s Science On a Sphere and its Collaborative User’s Network. Stephen also designs and develops data visualizations through his shared position at NOAA’s Visualization Laboratory, which are then distributed among institutional partners. Stephen is an avid traveller, scuba diver, and reef aquarist.