Big data scientists are more effective when they work together and share data

Many of today’s most important environmental problems will be solved by scientists from different fields working together with policy makers and citizens to harness the power of big data.

Many of today’s most important environmental problems will be solved by scientists from different fields working together with policy makers and citizens to harness the power of big data.

September 12, 2018 - Author: Holly Whetstone

EAST LANSING, Mich. - Many of today’s most important environmental problems will be solved by scientists from different fields working together with policy makers and citizens to harness the power of big data. But, for hundreds of years, scientists have been trained to work individually and to use relatively small amounts of data. Luckily, that is changing, but not fast enough say Kendra Cheruvelil and Patricia Soranno, environmental science researchers at Michigan State University, in an article published today in BioScience.

Just like all of us, scientists work within a culture that determines how they interact, how and what they study, as well as the methods they use. But, using big data to solve environmental problems in big teams flies in the face of the scientific culture of the last several decades.

“Unfortunately, some scientists are still publishing articles about how big data scientists are ‘research parasites’ if they use other people’s data, are taking the easy path to science, or are doing science backwards – that they are using big data for ‘fishing expeditions,’” said Cheruvelil.

Just think about how scientists of the past, such as Albert Einstein and Marie Curie, are portrayed as lone geniuses toiling on problems in the laboratory or on a chalkboard all by themselves. Some prominent scientists think that this is still how science should be done, even though many problems are too big and complicated for one person to solve. But, changing the culture of how science gets done is very hard say Cheruvelil and Soranno.

Cheruvelil and Soranno propose a way to shift the culture of science. They suggest that by deliberately and incrementally using the practices from two relatively new scientific fields – open science and team science – big data scientists can do better research to solve environmental problems.

“Our big-data research on over 10,000 lakes in the U.S., with millions of observations, would not have been possible without open science, which includes free access to good quality data, such as from citizen science programs and natural resource agencies. But, it also took methods from team science that helped about 20 researchers from different fields work together to combine all of the data into a useable format,” said Soranno.

What can be done with big data for the environment? Big data will be critical to figure out some important problems facing the environment and society. For example, scientists need to figure out which animals and plants will be most threatened by climate change, where they may start disappearing, and how those local extinctions will affect the many important services these plants and animals provide to people. For example, bees pollinate important crops that feed the world and plants provide food, cloth and medicine – all of which are well adapted to particular climates that are quickly changing. We can’t study one plot or field to know how all of the land or fields in a country or on the globe are going to change. This is where big data comes in to help researchers know where the most change is happening.

Where does big data come from? Because scientists cannot be outside collecting information on the environment everywhere and all the time, they need help to gather important environmental information. New technology and helpful citizens are answering this call. Today, nonscientists and machines can be out collecting huge amounts of environmental information in new ways – including, pictures and video from cameras mounted on buildings, drones and even animals; buoys in lakes continuously monitoring water quality; and citizen volunteers collecting data on plants, animals and the environment.

But, scientists still need to pull all of this information together and make sense out of it. This is where team science comes in. Scientists now recognize that it is not easy to work together to do big data research and that they must spend time getting to know each other, learning how to communicate with each other and learning how to best work together. These are skills that people do not always associate with being a great scientist. But, that is changing and tomorrow’s science stars will be those who are team players, support each other and know how to work well together. They also will be willing to share their ideas and data, and to set aside the myth of the lone science genius to join others in the quest to solve society’s pressing environmental problems.

Fortunately, as Cheruvelil and Soranno point out, many scientists have been collaborating for decades and there are many great examples of science teams already doing this. In fact, Dan Gruner, a program director at the National Science Foundation, which funds Cheruvelil and Soranno’s research, points out that, “The scope of ecological research questions being asked is expanding rapidly, in large part thanks to collaborative science, participation of citizen scientists, and open access to big data sets provided by large-scale research networks, like the National Ecological Observatory Network. Open science and team science are enabling researchers to ask questions addressing major ecological challenges facing society at large – even continental – scales.”

Cheruvelil adds, “Luckily, younger scientists are pushing older ones to learn the technology and skills to practice open and team science to answer these sorts of questions. Now we just have to foster the culture of science for them to be successful!”

Tags: big data, msu agbioresearch


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