What happens when you have two interdisciplinary fields that are changing what people think is possible? Fields that are expanding rapidly but on the surface seem completely unrelated? Where each field has more jobs and opportunities than people with the skills to fill them?
What if you integrated both fields to solve issues and problems that impact billions of people and the Earth itself?
That’s the question that scientists and researchers were asking themselves when computational tools became widely available and the problems we were facing as a species on the Earth became critical. Ecoinformatics started out in the scientific research community as a way to use databases and develop algorithms to test hypotheses concerning natural systems. However, today it has expanded to encompass so much more.
Today, Ecoinformatics is where clean technology and data science meet. It’s a field that’s become so broadly defined that it includes almost everything that concerns the Earth and the use of computational systems to model, monitor or change any natural system. That’s partly because both clean technology and data science are new fields that are expanding rapidly – faster than the people working in them can agree on what should be a part of the field and what shouldn’t.
Since we’ve become concerned about the environment, we’ve had different specialized fields to study each aspect of the Earth and our environment – environmental engineering, ecology, natural resource management, environmental science, sustainable systems, urban planning, sustainable material science and so on. But, it’s increasingly difficult to study these aspects in isolation – so, the term Clean Technology or Green Technology was invented to encompass all the aspects of the Earth as system and how human beings as a species can better live within the system. It includes everything from agriculture to water to sustainability to energy efficiency to biodiversity and ecosystem management.
Data Science, also known as Big Data, is another very new term for a basket of techniques and methods that have come from many different fields. The last few years have seen an explosion in the type and amount of data that is generated – so systems and methods have been created that allow us to handle these enormous volumes of data and extract insights from them to solve problems. The field includes traditional statistics as well as machine learning, sensors and robotics, data visualization and processing and managing large volumes of data.
Ecoinformatics lets us use the tools from data science to solve problems in clean technology. It’s a field that needs an understanding of how different systems in our environment work and an ability to create and use processes and methods to generate data about our environment and extract insights. It’s when we use sensors to monitor water levels and send a continuous stream of data to the cloud for processing. It’s when we use data from people’s Twitter streams and Facebook feeds to help figure out how to manage floods better. It’s when we develop algorithms based on natural systems like the lotus leaf to design water-resistant glass. It’s when we use maps to visualize the movement of traffic in a city and design better public transit.
This month we’re posting a series on how clean technology and data science work together, what’s driving the market in this sector and the kinds of careers that are being built everyday. Stay tuned to this space or subscribe to get the latest updates in your inbox.