Small words = big ideas

Explaining science is a tricky business. You have to use the right words to be accurate, and you have to assume that your audience may never have heard those words. Recently, I was invited by the nonprofit Science on Tap to talk about simplifying language for an audience at the Pub at Third Place in Seattle. I also will give a talk at the Seattle Aquarium on some of the same ideas.

Maybe you are a newcomer to the idea of the Up Goer language, created by Randall Munroe. But I’ve written about it before, and so you can get some background on that language and why scientists use it by reading an earlier post of mine about Hair-Having animals and a later discussion based on a talk at Town Hall.

What I’d like to share here are some links for exploration on your own of Up Goer, as well as other ways that people have used to try to simplify science communication.

Here is an especially wonderful comment from Chris Rowan’s article linked below:

“Some might not see this as anything more than a gimmick, and argue that the constraints you are forced to work under are too severe; that by replacing jargon with a dense thicket of ‘simple’ words, you are just replacing one sort of linguistic complexity with another.” But, as he says, that’s missing the point.  Rewriting in Up Goer can bring something “quite profound.”

Scientific American magazine article

Text editor to use upgoer yourself

Original cartoon about Saturn V rocket

Blog from Forum on Science Ethics and Policy that sponsors UW contest. This contains excerpts from some of the wonderful entries by contestants who described their research using Up Goer.

Different gizmo for simplifying text

Alternate text editor – By Theo Sanderson who created Upgoer5, Upgoer6

In Theo’s version Six, your text gets analyzed so that you can use more than the 1,000 most common words in English, but the words are sorted by color according to where they fall on the most-common to least-common continuum.

 

Read “The Forest Unseen”

The book, “The Forest Unseen,” is seductive and delightful. Every one of the short chapters takes you on a journey from an overview down to a microscopic and then sometimes genetic level of an organism. All of this is part of the author’s visits to a small section of a forest in the Southeastern United States.

These chapters take surprising turns, but seem crafted to keep the reader comfortable and close, even while taking us far inside a molecule or a historic evolutionary branch or the chemistry of photosynthesis. We are omnivores in this journey, sampling from a wide variety of delicious scientific flavors, while our guide remains true to his emotional and philosophical musings.
Biologist professor David Haskell teaches at the University of the South, but writes that he held his “scientist” way of looking at bay while he visited the same square-meter section of forest for a whole year. “This year, I have tried to put down scientific tools and to listen: to come to nature without a hypothesis, without a scheme for data extraction, without machines and probes.” He calls his square meter – the mandala.
Please enjoy my list of some favorite chapters and see whether this book crawls under your skin and makes a place for itself.
1. Samara
The spinning maple seed that seems to helicopter through the forest is a samara. Maple samaras “live in a little-known border country between the aerodynamics of fast, large objects like cars and airplanes and the aerodynamics of slow, miniscule objects, like motes of dust.”
2. Litter
While helping us understand the layer of detritus on the forest floor, he takes us beneath for a survey of the mysteries just below fallen leaves. “The rootlet is a smooth, creamy cable sprouting a maze of hairs that radiates out into the soil surface. Each of these hairs is a delicate extension of the root’s surface, a tentacle stretched out from a plant cell.”
3. Mosses
“I gaze through my hand lens and see water caught everywhere in the moss. In the angles between leaves and stems, water is caught in silver pools, trapped by surface tension. Droplets don’t flow: they clasp and climb. Moss seems to have erased gravity and conjured rising snakes of liquid. This is the world of the meniscus, the lip of water that pulls itself up the wall of a glass cup. And moss is all glass edge, an architecture that invites then traps water in its labyrinthine core.”
4. Medicine
Through the eyes of a man who has recently been given drugs for his heart, we get to see the forest plants as sources of aspirin and digitalis. But he also speculates on how certain plants developed their armories to protect them in tough times. “Ginseng, yam and mayapple are all small plants that overwinter as nutritious underground stems or roots. “ They are vulnerable to attack. Their defense is to soak themselves in chemicals that attack mammals. “By finding just the right dose, herbalists can turn the plants’ defensive arsenal into an impressive collection of stimulants, purgatives, blood thinners, hormones and other medicines.”
5. Moth
“A moth shuffles his tawny feet over my skin, tasting me with thousands of chemical detectors. Six tongues! Every step is a burst of sensation.” Later, we learn this moth is harvesting salt from the sweat of the author to give as a “gift” to a potential mate.
6. Underground bestiary
“In the end, it is not just the diversity of the bestiary that our size and dryness hides from us but the true nature of life’s physiology. We are bulky ornaments on life’s skin, riding the surface, only dimly aware of the microscopic multitudes that make up the rest of the body.”

The book was published in 2012, won many awards, and came to my attention through a post by Carl Zimmer on Twitter.

Photo of the author above by Buck Butler.

Shallow dive in Seattle big data projects

Seattle has a rich resource of both data-driven research projects and scientists who enjoy designing tools that mine data.

I was asked to talk about that big data heritage here in Seattle as part of a meeting of the Northwest Science Writers Association.

Consider this blog post a cheat sheet for those of you who did not take notes during my presentation or didn’t attend.

1. Big Data is defined as having volume, velocity and variety. If you put sensors on the ocean floor, as researchers are doing at the University of Washington, you will bring back real-time data by the server loads on temperature, salinity, and even on genetic sequences of the microorganisms there. The data will stream at high volume and velocity and with amazing variety. But finding insights from that fire hose of data is not so easy. There is a shortage of the data scientists who know the best way to parse the flood, according to Professor Ed Lazowska, who commented for my recent story.

Lazowska and a team have pioneered the eScience Institute on campus to nurture data science and provide a meeting place, a sort of water cooler, for the best conversations and exchanges among disciplines.

2. Most of us already understand the retail use of big data, because predictive models of our own buying behavior surround us. Apps that help you choose restaurants, airlines, music and other commodities are using models built on the buying habits of thousands of other consumers. The same desire for prediction is driving medical research now. Researchers in Seattle at the Institute for Systems Biology and Fred Hutchinson Cancer Research Center and Allen Institute for Brain Science are all using algorithms to try to understand vast amounts of data about human disease. One wonderful overview of this new way of seeing human disease was just published in Cell by Eric Topol in April.

Among the things Topol envisions in the very near future: “With the power of sequencing, it is anticipated that the molecular basis for most of the 7,000 known Mendelian diseases will be unraveled in the next few years.”

Many human diseases are a complicated mixture of vulnerabilities combined with environment and behavior. Knowing their molecular basis does not mean curing them is easy. But this level of understanding will create new opportunities.

One of the foremost Seattle scientists in genomics is Jay Shendure. You can read why NIH Director Francis Collins praises his newest ambition.

3. For my last comment on this quick overview about Seattle, I want to change the focus of the big data from sensors and molecules to the “big” pool of people that are increasingly seen as a resource for research itself. Patients are key players in new efforts to accelerate medical research by drawing in volunteer patients who free data about themselves. One of the pioneers of this approach is Sage Bionetworks, lead by Stephen Friend and John Wilbanks.  I wrote an earlier post about Friend, when the White House gave him an award. Recently, Forbes wrote about the way drawing on the public may bring faster cures.

Seattle sits at the center of many different strengths in using big data. We have leaders in a variety of sciences, including oceanography and proteomics, but we also have leaders in the creative destruction of the old models for disease discovery. As science journalists, I think you can mine many data projects for stories.

 Photo above is of poster session at the eScience Institute at the University of Washington.