Data Viz for Long-term Ecological Research and Curricula

Project Summary

Devri Adams (Environmental Science), Annie Lott (Statistics), and Camila Vargas Restrepo (Visual Media Studies, Psychology) spent ten weeks creating interactive and exploratory visualizations of ecological data. They worked with over sixty years of data collected at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire.

Themes and Categories
Energy & Environment
Data+
Year
2017

Project Results: The team created a "data stories" website aimed at high school students and undergraduates in introductory ecology courses, with the goal of teaching canonical lessons using tangible data. They also used R Shiny to create an open-source exploratory dashboard which will allow researchers to examine data at various time scales, and to generate and test novel hypotheses.

Partially funded by the Cary Institute of Ecosystem Studies.

Faculty Lead: Emily Bernhardt

Project Managers: Richard Marinos, Matt Ross, Gene Likens

Download the Executive Summary

Related People

Related Projects

Getting Granular on Social Determinants of Health

Social and environmental contexts are increasingly recognized as factors that impact health outcomes of patients. This team will have the opportunity to collaborate directly with clinicians and medical data in a real-world setting. They will examine the association between social determinants with risk prediction for hospital admissions, and to assess whether social determinants bias that risk in a systematic way. Applied methods will include machine learning, risk prediction, and assessment of bias. This Data+ project is sponsored by the Forge, Duke's center for actionable data science.

Project Leads: Shelly Rusincovitch, Ricardo Henao, Azalea Kim

Project Manager: Austin Talbot

Investigating oil and gas production in the United Kingdom

Producing oil and gas in the North Sea, off the coast of the United Kingdom, requires a lease to extract resources from beneath the ocean floor and companies bid for those rights. This team will consult with professionals at ExxonMobil to understand why these leases are acquired and who benefits. This requires historical data on bid history to investigate what leads to an increase in the number of (a) leases acquired and (b) companies participating in auctions. The goal of this team is to create a well-structured dataset based on company bid history from the U.K. Oil and Gas Authority; data which will come from many different file structures and formats (tabular, pdf, etc.). The team will curate these data to create a single, tabular database of U.K. bid history and work programs.

On the Shelf: exploring oil and gas production in the Gulf of Mexico

Producing oil and gas in the Gulf of Mexico requires rights to extract these resources from beneath the ocean floor and companies bid into the market for those rights. The top bids are sometimes significantly larger than the next highest bids, but it’s not always clear why this differential exists and some companies seemingly overbid by large margins. This team will consult with professionals at ExxonMobil to curate and analyze historical bid data from the Bureau of Ocean Energy Management that contains information on company bid history, infrastructure, wells, and seismic survey data as well as data from the companies themselves and geopolitical events. The stretch goal of the team will be to see if they can uncover the rationale behind historic bidding patterns. What do the highest bidders know that other bidders do not (if anything)? What characteristics might incentivize overbidding to minimize the risk of losing the right to produce (i.e. ambiguity aversion)?