Web 2.0 Expo Slides

Here are the slides and notes from my Web 2.0 Expo talk Data Visualization for Web Designers:

You can also download the PDF version. Both are exports from Keynote including extra notes and links that should cover most of the material from the session.

Upcoming Bloom appearances: Web 2.0 Expo SF and Geeky by Nature NYC

On Tuesday (March 29th) I’ll be speaking at in San Francisco at Web 2.0 Expo. My talk is Data Visualization for Web Designers: You Already Know How to Do This, here’s the overview:

Today’s web developer is armed with a powerful suite of tools optimized for writing network-aware, data-driven, interactive graphical applications. Modern web browsers provide a powerful flexible programming language (Javascript), an expressive and elaborate styling system (CSS) and two robust, battle tested document models (HTML and SVG). In the rare cases these aren’t enough, new technologies like WebGL and Canvas can fill the gaps and old standbys like Flash haven’t gone anywhere. You know how to do this!

In this session we’ll:

  • take a look at the best examples of interactive, web-based data visualization and talk about how they work and what they achieve (and where they fail)
  • explore the tools, techniques and resources out there for today’s web developers and designers working with graphical presentations of data (e.g. Processing JS, Protovis, D3, Google Maps, etc.)
  • look to the future of data visualization online and what features new technologies like WebGL will offer that we haven’t seen before

On Friday (April 1st) Bloom’s Robert Hodgin is speaking in New York at Geeky by Nature. His talk is Practice Makes Perfect, So What Are You Practicing?, here’s the overview:

Six years ago, I created my first programmed magnetic repulsion effect. In the years that followed, I continued to fine tune and explore the phenomenon of electrostatic fields and gravitational forces.

I used the necessary equations for these invisible forces to create audio visualizations, natural simulations, and artistic interpretations. Everything fell into place as things tend to do when you are dealing with specific formula in controlled situations.

Recently, however, my fascination with these invisible forces has started to work its way into my day to day. I can’t close my eyes to sleep without seeing charged particles spreading out in the blackness. I can’t walk down a crowded sidewalk without thinking about how repulsive forces lead to collision avoidance. I can’t look at flowering tree without considering the complex mathematics and infinite iterations it would take to create such intense beauty and variety.

In my presentation, I will discuss these forces at greater length and show some implementations and unexpected uses.

If you’re at either event (or both!) please don’t hesitate to say hi and ask us more about Bloom!

And then there was Cartagr.am

We’re all obsessed with recording not just the hard facts of the cities we live in, but also the soft ambiance of our experience within them.  At least that’s the implication we see from the mass acceptance of geo-social tools and the content you the user create with these tools.  We’ve tried to examine these shared experiences and how they define location with Cartagr.am — a map of collective experiences through Instagram photos.

Screenshot of the Cartagr.am map

As wonderful as these collected experiences are though, we’ve been limited in the tools we can use to explore this data of personal experience.  Too often the data arrives in a one-dimensional stream designed to help us catch up with what our friends are up to or as a snapshot of what’s happening precisely at that moment — but because they are so fragmented and linearly organized, none of them tell us much about the world as a whole. Even our favorite photo-sharing sites that support geo-coded photos — like Flickr and Instagram — are heavily biased towards a time-series oriented view of the data instead of geographic or otherwise experiential, exploratory views.  Because of this, we’re forced to rely on memory if we want to understand the trends and significance of a collection of images.

Compare this to the tools available to view the hard-facts of cities — crowd-sourced street and architectural information, and so forth — and you can being to see a the large gap between traditional visualization tools and personal and expressive data visualization tools. We are lucky here at Bloom Studios that Ben and Tom, two of our co-founders, have spent years refining the theory and practice of cities, geography, and mapping for hard facts.  As such, there’s a rich toolset for discussing and presenting data — and with Cartagr.am we’ve applied this technology stack to present you with the collective experience of Instagram users.

One of Bloom’s central theses is that the experiential and personal data can be transformed into an expressive format using the same tools we’ve become experts in using for traditional factual data.  So can we use visualization tools to provide a new insight into an already rich experience?  In our current social and experiential toolkits, location is an element of context to understand the photo.  What would happen if you inverted this relationship?  What would happen if you used the photo to provide a context for a given location?  That’s the question we’ve tried to examine with Cartagr.am.

Cartagr.am attempts to provide a glimpse into the collective experience of Instagr.am users.  We’ve initially created maps that present a collective view – focusing on what’s “interesting” within a given area.  Cartagr.am is actually a cartogram — it truly measures a variable over a geographical area.  In this case we’re using the notion of “interestingness” to define what defines an area.  Using this variable we select which photos to show in a larger size than others.  We’re not restricting ourselves to a completely linear model of interestingness and size, so that we can provide users with some larger, and recognizable, photos at any zoom level.

This, we hope, gives you a glimpse into the value of Cartagr.am and examining experience geographically in a broad way.  Over time we will expand this capability, allowing you to not just view all public data, but to also restrict it to your own views of geographical experiences and those of your friends (as defined by your social network participation), making it more personally relevant — your own social (or personal) map of what matters in the world.


Cartagr.am was written using ModestMap.js for the tile mapping and SimpleGeo for the location services and the labels are the Acetate labels from FortiusOne and Stamen.  We’ve extended this stack somewhat to support richer experiences than were available to us out of the box, but have tried to keep all of these extensions as general as possible.  Tile maps are certainly common experiences now, but we did this because we’re trying to explore the possibilities available to data visualizers if they can simply swap out the data source for another – would there be sweet spots of rich experiences made available if we encourages playing with the data sources?  The tile-generation itself was bespoke, and something we’ll look into generalizing further over time and as computation restrictions are relaxed somewhat.


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