Eyeo 2016 Recap

I attended the Eyeo Festival this week. It brings together "creative coders, data designers, artists, and attendees." I have been wanting to go for a couple of years as a way to pull myself in a different direction. It's easy to get into a rut, or at least into a routine that doesn't allow you to ponder other possibilities. This was a very different conference from others that I've attended. Here, I came away feeling creative and inspired. At others, I've walked away with learning to apply. It's not that one outcome is better than another---they each have a role.

I am looking forward to the videos from the festival being posted. In the meantime, here are some of the highlights.

Emergence
Nicky Case kicked things off. His focus was on emergence, a concept where the sum is different from the parts. I can't say that he shared anything new in terms of his ideas, but what I liked was seeing a young adult share his process of learning that there is a lot of grey area in the world. I worked with teenagers for nearly 20 years, and the black/white worldview was pretty normal. It takes time and experience to learn that there are lots of answers to any question. As a young 20-something, Case is showcasing the transition to a more experienced lens on the world.

The keynote by Paola Antonelli, which was the next evening, shared an even more advanced take on this theme with her views on quantum design: "ambiguous states, in the spaces ‘in between’—between digital and physical, high-tech and crafts, old and new, nature and artifice, developed and emerging world." Beauty is not just in the eye of the beholder, meaning is derived from the eye of the observer.

Transformation
A second theme was about the transformative nature of data. Paolo Ciuccarelli of Density Design spoke about the poetics of data visualization. He pointed to the need to design data experiences that "generate poesis within a space of wonder."

from http://www.densitydesign.org/research/brain-houses-three-interieurs-stories/

One of my favourite ideas that he shared was this concept of a panorama, like the one shown above. I love the idea of embedding the data within a larger context. I highly recommend having a look at the Raw tool for generating visualizations.

Moritz Stefaner gave a talk on his Data Cuisine project. One of the things I liked most about this project was the idea that the dimensions of food (ingredients, presentation, cooking method, etc.) can be used to represent dimensions of data. This leads to a very different sort of interactive experience.

Transformation also appeared in how artists used materials in different ways. Whether it was Anouk Wipprecht combining her love of couture and robots or Tania Candiani speaking about the intersection of combination, serendipity and translation, I was blown away by the creative thought processes that were shared.



This is not the sort of end product I get at education conferences---where sharing one's thinking is not considered good enough. At those conferences, there is an expectation of audience involvement and tangible takeaways. With Eyeo, the feeling that is created through the presentation is the goal. I can't talk about this conference in terms what I learned, but rather, how it made me feel. This brings me to the last major theme.

Instruments of Power
There was a strong focus on equity at this conference, from the range of speakers, to topics, to the code of conduct. Part of that is an understanding of privilege as it applies to how we collect, use, and represent data.

Marek Tuszynski from the Tactical Technology Collective shared their recent exhibition: The View from the White Room. (E.g. looking out from an Apple store.) The show looked at questions such as What does it mean to live in a quantified society? and What is the value of data privacy when it becomes something you can buy? Lots of powerful things to think about from this session---I had to get out and take a walk after it. Part of the exhibit included something called Big Mama, based on the quote from a government official justifying surveillance that he did it because "I love you all." and the perception that the contribution of data leads to a harmonious society. Take a deeper look at Unfit-bits, Me and My Shadow, Security in a Box, and Exposing the Invisible. It is not that these concepts are new or unknown, but it's their application within our personal and professional contexts that make them worth revisiting.

As much as we talk about the power data visualization has to reveal, we rarely talk about how it can also be used to hide. In the best talk I saw, Josh Begley shaped conversation around what the work is that data visualization does. In one example, he talked about the geography of incarceration. As part of that, he made the comment that "most photos today are taken by machines for other machines to see." Satellites, drones, and other tools capture far more images than anything humans post to Instagram, Flickr, or other sites. Josh works on projects that bridge what machines are doing with what we notice. Do we want to be as connected to our foreign policy as we are to our phones? Check out his work on the Dronestream App or Officer Involved Shootings as ways to explore how the things we don't represent are still powerful enough to evoke emotion.

There were other presentations, keynotes, and sessions that I attended. There were also some I didn't get to attend due to having to get to the airport...including one I was looking forward to the most by Lynn Cherny. However, I enjoyed exploring a bit of Minneapolis, getting to meet several data viz heroes in person, and being able to think about some very different concepts for awhile. This spring has been a real drag in terms of work demands. I am looking forward to working on some new projects that are being spurred by this recent boost to my sense of creativity.

What have you seen recently that inspires you?

Changing the Narrative

One presentation from the Tapestry Conference has kept me thinking long after the end of the event. It was a short story presented by Trina Chiasson, and explored the rise of the Data Selfie.



Trina talks about the importance of the user being able to see themselves within the data set. At minimum the data should support a personal goal or help solve a problem by revealing new insight. In this world, data become the jumping off point into a Choose Your Own Adventure style of story. I like this idea from the standpoint that part of audience engagement is a sense of personal relevance or connection with the data. 

One of the examples Chiasson gave was this interactive graphic from the New York Times that shows The Jobless Rate for People Like You.

There are tons of similar examples out on the interwebs---ones where if you fit the descriptors shown (male, female, white, black, Hispanic...), you get a chance to participate with the data and create that data selfie.

But what if you don't see yourself reflected in those descriptors? If I'm Asian, for example, I have to be content with "all other races." Beyond that, there's a lot of nuance missing. Does it matter if I have one college degree or three? It all counts the same.

What I think might be more disconcerting is what happens if you do see yourself in the data and don't like what you see. Using the NYT site shown above, if I'm a black male, the jobless rate is double the national average...but there isn't anything I can do about being a black male. I can't change that narrative. So then what?

I realize were talking about an example involving adults, but I can't help but think of the K - 12 world I live in. What if I did build something like this to show the graduation rate for people like you? I have the data. I know the demographics of our students and graduation rates. Not a big thing to put it together. But in posting it, what am I saying to the parents of black child in third grade? Your kid has  a 50-50 shot of making it to graduation in our district. What are the options to create a different story for him or her? Will it change before your son or daughter reaches high school? After all, dropping out is a process, not an event. Is it already too late to try? I can't imagine anyone would tell a child to just give up in third grade because data reveal that they're not going to get a diploma. But what is the takeaway for a child, parents, community, or teacher who sees just that in the data?

Sometimes, these aren't data selfies. They're system selfies. If the jobless rate for black males is twice the national average, that says something about us as a society...not those individuals. Ditto for my imaginary graduation rate display. It seems to me there is greater power in supporting individuals become critical consumers of their own data. Perhaps, as Chiasson suggests, it's tracking health or working toward a personal goal. But when we connect it to something larger ("People who lost 10 pounds also ate three carrot sticks a day!"), it stops being personal and projects a Fate you might not feel you are able to escape. Can we develop ways to effectively share data and use trends for insight without disenfranchising the most vulnerable among us? How do we balance the rise of the data selfie with the need for systemic change?

Ethical Communications Using Data

Much of the data we collect as educators is subject to various federal, state, or local regulations about who can see the data and for what purposes. These ethical considerations most often apply to data points that connect with an individual or very small groups. Once aggregated, we tend to slide into our own version of ethics. We make decisions about how the data are presented and annotated. We choose the stories, the focus points, and even the audiences we share with. What are the questions we should be asking ourselves as we make these choices?

A recent forum on Responsible Data Use generated some categories and avenues of inquiry around this topic. I've read through the summary several times now, and with each glance through the list, I find new things that I'd like to discuss. Here are a few that catch my eye:

Communicating uncertainty

• How do we communicate uncertainty in data?
• In metadata?
• How do we represent gaps in the data?
• What if our knowledge of the uncertainty in the data is anecdotal?
• How can visuals show “no answer”?
• How can data visualization promote ambiguity?

Literacy

• How do we improve everyone’s data visualization literacy, as creators and as viewers?
• How do we educate people about the data they create?
• Which people most need data literacy?
• Can we provide interactive tools that let viewers adjust data visualizations in real time as a means of improving literacy?
• How can we support grassroots groups to create better data visualization?
• Is there a need for basic design principles and data viz 101 resources?
• How do we navigate a fear of numbers?

BAD data viz

• Is meaningless data visualization worth anything?
• What about when people make decisions based on bad data viz?
• If raw data is unrepresentative, will visualizations on it be bad?
• We should collect examples of unethical data visualization.

Audience

• How do we involve the audience?
• Who is the audience, and why?
• How do we create community ownership of a data viz?
• How do we allow a data viz to speak to multiple disparate audiences?

Some of these questions are easier to answer than others---we can think of a few ways to represent a lack of data. Others, like those in the "BAD data viz" group, are not so simple, but would be fun to kick around and see where we get. What would be your priorities in your workplace?

The summary with all of the categories and questions also has links to a variety of resources and notes connected with the forum. They are well worth exploring, if you have a few moments.

New Frontiers

I have probably shared this before, but this tweet from Hilary Mason is something I think a lot about:

https://twitter.com/hmason/status/488382950128754688

Within my own work, I continue to raise conversations about equity. How will students and teachers be empowered by the data we collect and review? How do we provide opportunity for marginalized voices to be heard? How do we elevate their needs and concerns?

I am starting to collect resources around both equity in data visualization. Here are a few that you might be interested in, too:

• The Harvard Graduate School of Design recently hosted a Black in Design Conference. There's a great Q & A available, where organizers Cara Michell and Courtney Sharpe provide background.
• I was also pointed toward two different articles about feminist data visualization. One explores what this type of data visualization would look like. The other takes a historical approach, reviewing work of women engaging in data viz in the nineteenth century. 
• Along this vein, I am starting to see more information shared about the intersection between digital humanities and data visualization. You might also be interested in following Shannon Mattern, Lauren Klein, and Paige Morgan for more ideas in this field.

In other news, I have been working on a little behind the scenes cleanup on this site. I've refreshed the information on the various pages, as well as the front page side bar. I also recently purged my Delicious site, deleting dead or irrelevant links and reorganizing the remaining ones. If you're searching for Excel info, research, tools, or anything else related to data viz (including equity), please head over to that site. There, you can sort links by a variety of tags.

I'm heading to the Tapestry Conference and Eyeo Festival this year. I am feeling the need to stretch and grow beyond the field of education. I do my best to connect with others in a digital space to learn about how they are using data, but I would like to do some in-person networking, as well. Will any other readers be at either of these events?