Quality Data Isn’t Enough: Why Communities Matter in Science
Description / Summary:
Scientific findings are often presented in isolation, driven by the need for efficiency and technical precision. Even when those most affected by the results are included in discussions, they are not always part of the scientific process itself. Yet the industries served by Microbial Insights are ultimately about people. Whether in environmental remediation, agriculture, corrosion, art restoration, or microbial source tracking, the science we perform has real impacts on communities around the world.
In this webinar, Dr. Sam Rosolina will look beyond the technical details to highlight the people behind the samples and why the quality of our science matters.
- In Accra, Ghana, a community with a globally recognized circular economy built around secondhand clothing is becoming overwhelmed by the growing volume of textile waste from the Global North. Community science is helping residents better understand and address the problem.
- In East Palestine, Ohio, residents affected by a train derailment carrying more than 350,000 L of hazardous materials had questions that science alone wasn’t answering. One community member’s observations led to important insights about groundwater connectivity and scientific communication.
- Farmers adopting rotational grazing want to understand how regenerative practices affect soil health compared to conventional, chemical-intensive methods. Microbial analyses revealed compelling patterns, but communicating those results proved just as important.
- A small nonprofit documenting every species within the nation’s most visited national park is using molecular tools to better understand microbial biodiversity. How can these data inspire public appreciation and conservation?
No matter the industry, every sample represents someone’s question, livelihood, or future. Recognizing the people behind the science reminds us that communication, accessibility, and collaboration are just as essential as the instruments that generate the data.