Big data is all around us. The huge amounts of information collected by businesses, websites, Internet-connected devices, software and other sources can be used to gain valuable insights, inform decisions, and understand complex systems.
There are few systems more complex than our environment. A vast array of both living components like plants, animals and microbes and nonliving elements like air, water, soil, and energy work together to sustain life. The many complicated processes are too much for a single person to understand.
Big data, especially with the help of other technologies such as artificial intelligence, can help us to understand our environment in a way we couldn’t before. It’s already started to influence environmental science research through a number of projects.
The Global Lakes Ecological Observatory Network (GLEON)
GLEON collects data about lakes from around the world. It gathers sensor data from buoys in 80 lakes across 51 countries on six continents. It seeks to provide this data to researchers, educators, students, and the general public to promote study and understanding of lake environments.
Almost 200 papers, theses, and products have been attributed to GLEON. The organization’s data analyses have helped researchers better understand how lakes respond to extreme events, the role temperature plays in lake respiration and the effect of global climate change on lake temperature. Although such a huge project comes with its difficulties, GLEON is working to improve the infrastructure for sharing information.
The Environmental Quality Index (EQI)
The EQI is an Environmental Protection Agency (EPA) project that collects data on environmental, man-made and socio-demographic factors from a variety of sources. It uses that information to find correlations between environmental factors and public health issues. The EPA is currently working to develop a way to estimate the overall environmental quality of each county in the United States.
Among the environmental data collected is information on air quality, water quality, emissions and concentrations of pollutants. The EPA integrates data on public transportation, public housing, traffic safety, roads and business environments as well as economic conditions, crime rates and public health measures.
By analyzing this data, researchers could gain valuable insights on how environmental quality affects people’s health and overall quality of life. If areas of concern arise through the EQI, the EPA may direct more research to be done on those issues.
The Stream-Catchment Dataset
The StreamCat dataset developed by the EPA’s Office of Research and Development (ORD) collects data on both natural and man-made landscape features for 2.6 million streams and related catchments across the contiguous United States.
The data is used to create national maps of aquatic conditions. The information could be used to model and predict water quality. Researchers could potentially draw correlations between things like the construction of docks, which can leach harmful substances into the environment, and water quality. These findings could be used to inform policy development decisions and other kinds of relevant decisions.
The Web-Based Interspecies Correlation Estimation (Web-ICE)
Web-ICE is an Internet platform that integrates several datasets on the toxicity of chemicals to various species. It’s designed to be user-friendly, so investigators can use it to estimate the toxicity of a specified chemical to a certain species based on how that chemical affects other similar species. It can be used if data is not available on the reaction of the species in question to the specified chemical.
This knowledge could be crucial to understanding the risks of using a certain chemical on the area’s ecosystem and population and be used to inform development decisions.
The worlds of technology and environmental science are becoming increasingly interconnected. The more data we collect, the better we may be able to understand the environment we live in and how to better take care of it.