GA 5 Special Opportunity: 2 Day-Long Workshops on Data Science

GA 5 Conference Special Data Workshop on Vehicle Emissions Data

GA 5 Special Data Workshop on Ecological Forecasting and Native American Land and Water Resource Management

July 28, 2022 (Arrive on July 27 before the start of the GA5 Conference)

Sponsored by the NSF Award: III: Medium–Investigating Spatial-Temporal Informatics for Transportation Science (PI S. Shekhar) (NSF IIS 1901099) which seeks to build next-generation spatio-temporal informatics (STI) tools to analyze emerging vehicle big data such as on-board diagnostics data to further the understanding of real-world emissions and energy consumption. 

Geoscience Alliance Conference Attendees will be chosen to attend this special data workshop. Limited to 10 students.

Participants will use Google Maps to help develop and deliver a special GA Conference Workshop for the larger conference group that will take place during the conference. Participants will be looking at vehicle emissions and explore how the Google Maps Fuel-Efficient Route Options feature can support a clean environment.

Participants will have a chance to tour laboratories at the University of Minnesota and meet with faculty from the Computer Science Department. Learn about current research using Big Data sets from computers within vehicles and what it can tell us about fuel efficiency and creating more fuel efficient vehicles.

This workshop will be particularly useful for students in Computer Science, Engineering, GIS, Sustainability and other majors who are thinking about graduate programs in those fields or how they might use data science in their careers.

Schedule

Arrive at GA5 one day early on July 27. Housing is provided at UMN dorms. Food is also provided.

July 27, 6 p.m. Dinner with researchers from the Department of Computer Science and Transportation Studies

July 28, 9 am to 4 pm, workshop, lunch with faculty, and lab tours.

August 1, 2022 (Stay over Sunday July 31, a free day, and then workshop is on Monday)

Sponsored by the Ecological Forecasting Initiative (EFI). EFI is a grassroots consortium aimed at building and supporting an interdisciplinary community of practice around near-term (daily to decadal) ecological forecasts. Much of the imperative to focus on ecological forecasting comes from the need to respond to the multitude of environmental problems facing society and the aspiration that environmental decisions be made with the best available science in hand. In fields such as fisheries, wildlife, algal blooms, wildfire, and human disease, we often need to know how ecosystems, and the services they provide, are going to change in the future and how do humans affect those trajectories? Because all decision making is ultimately based on what will happen in the future, either under the status quo or different decision alternatives, environmental decision making ultimately depends on forecasts. Ecological forecasters try to make those forecasts, and their uncertainties, explicit. An important mission of the Ecological Forecasting Initiative is to support the next generation of environmental decision makers in developing the computational and data analysis skills needed to respond to environmental problems with a high level of technical expertise.

Participants will have hands-on experience in a computer lab trying out coding using R, finding important data sets and resources, and looking at some basic web resources for furthering your skillset.

This workshop will be particularly useful for students in Environmental Studies, Geoscience, or Sustainability (or other Earth-related fields) who have an interest in applying data analytics to research questions.

Schedule

Stay after GA5, leaving on August 2. Housing will be extended in UMN dorms, with breakfast provided.

July 31, 2022 – free day. Dinner with faculty and researchers will be arranged.

August 1, 2022: 9-4, Workshop, lunch with faculty, campus tours.

Participants’ housing will be extended in the dorms until August 2 departure and food will be provided.

%d bloggers like this: