Month: March 2013

data-analysis, data-mural, Uncategorized, workshops

Helping a Community Find Stories in Their Data

My Data Mural work has led me into a new area – actually helping community groups find the stories they want to tell in their raw data.  Until now, all my data therapy work has focused on how to present the data-driven stories more creatively.  This post shares some of the techniques I’m trying out.

Step 1: Speak like a normal person

I know, it should be obvious, but too often when entering the realm of data-anything, we fall back into using big words.  That doesn’t fly when working with community groups that don’t have a shared meaning for those words. I tried to figure out how to use regular words to talk about the types of stories that you can look for.  I came up with this set to start with:

typesofdatastories

  • comparison: you see two pieces of data that are really interesting when compared to each other
  • factoid: you see one fact that jumps out at you as particularly interesting or startling
  • connection: you see a connection between two pieces of info – you can’t say one causes another, but they’re interesting when put together
  • personal: you have a compelling story or picture that is about one person
  • change: you see one of your measures changing over time

I used regular words to describe the types of data stories in order to make the activity less intimidating to non-data people. Many people nodded their heads as I described these categories (especially at the second workshop where I spoke about them better!).  I was inspired by the Data Stories section of the Data Journalism Handbook.

Step 2: Try it out together first

To come up with a shared definition of what these types of stories meant, I showed a few data points from an amusing data set – the Somerville “Happiness Survey” (raw data).

happiness-data

We quickly tried to find stories of each type in this tiny data set.  Practicing all together on a tiny dataset can create a shared language for finding stories in data. In the breakouts that followed this activity, I could hear people using some of these words with each other to talk about the data they were looking at.

Step 3: Use less data

Usually data analysis starts with a giant set of documents.  This model doesn’t really work for a small community group made up of people that aren’t data nerds.  For our “story-finding” workshops we culled down the full data they gave us, producing a 4-page data handout for people.  Limiting the data helped the community group not be overwhelmed by the task of finding a story they wanted to tell. We definitely made some “editorial” decisions that limited the stories they could find, but we did this with the help of a smaller group of our community partners so it wasn’t arbitrary.

So how did it go?

We scaffolded the story-finding around the idea of telling a story in our “The data say____” format.  This gave us a common way to talk about the stories with each other.  Just as importantly, this forced each person to justify why they thought it was a compelling story to tell in mural form.

thedatasaySo did we build the group’s capacity for data analysis?  Our pre-post survey did NOT show a noticeable increase in people’s self-assessed ease of finding stories in data. Damn. But wait… the answer is probably more nuanced than that.  They did say they came away with more knowledge about the topic the data was about.  They also said one of the most interesting things they learned was “telling data stories”, and in each of these two pilots they came out with a data-driven story that they wanted to tell.

Is exposure to data story-finding  a sufficient outcome?  Am I trying to do too much capacity building all at once?  I’m still pondering how to do this better, so please suggest any tips!

Curious about these pilots?  You can read some more on my collaborator Emily’s Connection Lab blog:

Cross-posted to the MIT Center for Civic Media blog.

meta, presentation

The Case for Informal Visualization

Data visualization is all over the place. On the hype curve, we’re clearly up in the area of inflated expectations. If you listen to the reporting, you wouldn’t be blamed for thinking dataviz is going to bring world peace! I’m writing to beat the drum in favor of more informal presentations.  You can tell better data stories, and engage your audience more, by creating less formal data presentations.

Some Examples

What do I mean by “informal visualization”?  To start, toss out your computer, printer and graph paper. Pull our your crayons, big paper, tape, and your imagination.

From top-left, clockwise:

Another example is the Data Mural pilots I’ve been doing with artist, facilitator (and my wife) Emily Bhargava.  We’re leading groups through finding a story in their data, creating a collaborative visual design for a mural, and then painting it! (read more on my Data Therapy blog and Emily’s Connection Lab blog).

Stuff Academics Say

I work at a university, so I have to mention some of the research in this area.  First up – there is a great paper out of the City University of London, called “Sketchy Rendering for Information Visualization“.  Basically, they get a computer to draw graphs as if they had been drawn by hand.  My main takeaway was that their “sketchy” graphs engaged people more than the more “official” looking ones with straight lines.

Secondly, the Data Stories podcast had a recent episode called “Data Sculpture” in which they spoke with people investigating physical data presentations.  If you listen to it, be prepared for a lot of academic jargon – their audience is not the general public.  My main takeaway from the paper referenced (“Evaluating the Efficiency of Physical Visualizations“) was that when people physically touched the 3d objects representing the data they did a better job understanding the data.

It’s Arts & Crafts Time

Beyond these examples, and academic rationale, making informal visualizations is just flat out more fun.  As with most things, I think there is a cultural issue involved here.  Western culture has an inexplicable (to me) emphasis on professionalism and looking like an expert. When I’ve worked in Central America, South America, and India I’ve found the professions more welcoming to informal data presentations like those I show above.  Perhaps this was due to resource constraints, but it almost always led to better sessions.

Whie doing my master’s in the Lifelong Kindergarten group here at the MIT Media Lab, I fully joined the tribe that talks about how making physical things is the best way to communicate your ideas. This “constructionism” approach has feuled all my work since then, and I see this call for informal visualization as a way to bring it to the dataviz world.

So what does this mean in practice?  For me, I’ve taken to doing less on the projector and more on paper.  I encourage community groups I work with in Data Therapy sessions to partner with local artists and schools. I push businesses and organizations to thing about their audience and goals harder before jumping into making data presentation.  (PLUG: come to my “Fight the Bar Chart” meetup here in Boston to learn more about that)

If you want to look like a “sage on the stage”, by all means be as formal as you can.  However, if you want to engage your audience around a data story, try having some art and crafts time before your next data presentaton.

 Cross-posted to the MIT Civic for Civic Media Blog