Some parts of science are boring. Some are tedious. Some seem as though they will never end. It is these parts of science we tend to try to enlist the public in helping with.

You can, of course, listen for birds as part of the Breeding Bird Survey, count butterflies as part of the 4th of July butterfly counts, or set out cookie crumbs to collect urban ants for our School of Ants project. These endeavors are delightful ways to engage nature. They are also relatively easy ways to participate in science. But in collecting and contributing these bird and butterfly and ant data you are doing just a piece of the science. It’s an important piece but a piece nonetheless in the way that the word WHALE is part of the novel Moby Dick. You need the word WHALE, but Moby Dick is so much more than the word WHALE just as the science of studying birds is more than AMERICAN ROBIN. Wouldn’t it be incredible if, addition to helping with the accumulation of these nouns, the public could be part of the rest of science, the wild speculative part, the hypothesis testing part, the data exploration and all the rest? Yes, it would.

A challenge is that so many of the exciting moments in science come not from single observations but instead from context (That isn’t the only challenge, but one thing at a time). In Moby Dick, the great whale sees a different world from each of its enormous eyes. As scientists, the challenge is even more difficult. We see thousands of worlds with as many perspectives. We need to simultaneously keep track of both the details (one world) and the big picture (another). How then do we provide context when so much of modern science involves huge datasets about small things, datasets that can be hard for scientists themselves to manipulate and interpret? Visualization.

And so it is with incredible joy that we have embarked on a recent collaboration with Holly Bik and her team of programmers, artists and futurist gurus. Holly and team have developed a new online interface, Phinch (Phinch is to Darwin’s finches what Phat is to fat), in which one can visualize the sorts of data that are now very common in science, data on the genes or species present under different conditions, data like those we now have for 1000 homes across North America, data that we do not yet understand but which, once we release the data, you will be as poised to understand as are we to see both the small and the enormous at once.

Let me back up to explain the kind of data I am talking about. We worked with more than a thousand citizens who, roughly a year or two or more ago, swabbed four surfaces in their homes. On each of those swabs they collected an invisible zoo of living forms, animalcules including tiny worms, protists, bacteria, archaea and fungi as well as microscopic bits of plants. This is worse, of course, than listening for an American Robin in as much as at least when you listen to an American Robin you get to, well, listen to an American Robin. When you swab for microscopic species, you don’t see those species. “Seeing” them takes many steps in the laboratory, steps that break open the cells of those small beings, expose their genetic material, copy that material and then transcribe the secret code of that genetic material. The ultimate result, the boring, difficult, inscrutable result is an enormous datasheet on which we have a list of all of the places that were sampled and, for those places, the life forms whose DNA was found. It is exactly the same kind of result produced, for example, by a bird or butterfly or ant survey. What then?

Phinch, we hope, will provide a partial answer to “what then?” What then, is that in order for these data to become science, one needs to explore what determines which species live where. This is the exciting bit because it allows us to ask amazing things to which we, as of yet, are just beginning to learn answers. Do more kinds of microscopic species live in tropical houses than houses in Alaska? Do cats influence which species live in houses? Do dogs? Does it depend on climate in the first place? Are indoor species similar to those outdoors? These are all questions that are answerable given our data and now, with Phinch, anyone can answer them by exploring the data, anyone can answer them as well as or better than us. In fact, because our dataset from the inner and outer doorframes of 1000 homes includes more than 100,000 species, there are no fewer than 100,000 different phenomena to explore.

So how do you do it? First, we recommend you watch a video tutorial that Holly Bik prepared to walk you through how to use Phinch. Then, you’ll download the specially formatted datasets to your desktop – the files, one for bacteria and archaea and another for fungi, contain information about the species detected, locations in the home where we found the species and some data about the homes where we found those species. Next, go to hip-hop Phinch (be sure to open it in Google Chrome) and browse for the file you have downloaded. Once you have found it, upload it. Then the fun begins. You can begin to explore the data in its full fullness.

Right now, there is no user guide or recommended path for exploration. We want you to poke around, to see what is and is not obvious. Partake in the messy joy that is our science. With time we will make other data available as well, but already, if you are bold, you can explore the largest dataset on bacteria and fungi in houses ever to exist and, because we have only just begun to explore it too, you can see things we have not yet seen. If you do, please let us know.

Together, we can try to understand which species live where and why, so that we might ultimately understand how those species affect our health and well-being and how we might create environments in which we live among healthy species rather than just those that happen to show up. But not yet, our next step is just to begin to understand a microscopic world that is still invisible and yet, thanks to the Phinch team, much easier to see with both sides of your big brain, both the part that looks closely and the part that backs up to see the whole picture, the universe of life all around us, on every surface and yet still so, fundamentally, misunderstood.

Header image: Screenshot of ‘Bubble Chart’ visualization in Phinch.