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.
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.
Welcome to Bloom! Our mission to bring you a new type of visual discovery experience is already underway. We’re building a series of bite-sized applications that bring the richness of game interactions and the design values of motion graphics to the depth and breadth of social network activity, locative tools, and streaming media services. These new ‘visual instruments’ will help you explore your digital life more fluidly and see patterns and rhythms in the online services you care about. And they’re coming to a tablet, media console, or modern web browser near you!
We’re excited to invite you in to our newly redesigned site at bloom.io, where we’ll be showcasing the first instances of the experiences we’re designing, starting with Fizz and Cartagram. What is important to realize about these, as with all of our coming applications, is that they are the foundations of a constant flow of ongoing iterative development, much like video game franchises. As a participant in the Bloom Network, you’ll be presented with an ever-changing, ever-increasing variety of views onto the world’s most popular web services like Facebook, Twitter, Gmail, youTube, Netflix, Dropbox, Instagram, and so forth. Some of these instruments will be lyrical, some playful, some analytic, many of them combinations of all three, but all will provide compelling and engaging handles on the information that matters to you most, each one evolving and improving over time, building on your understanding of its performance. Starting later this year, you’ll find these instruments on iOS and Android devices, like tablets, phones, and media consoles in the home.
In order to make these experiences possible, many of which will use the latest in 3D graphics, simulation, and data modeling frameworks, we’ve brought together quite a team. I’m particularly excited to announce that we’ve most recently been joined by our new Creative Director, Robert Hodgin. For those not familiar with his work, please take a moment to browse his portfolio at roberthodgin.com or his blog at flight404.com, and you’ll quickly see why we’re so enthused to welcome him to the team.
His dynamic visuals have backed musicians performing on tour like Peter Gabriel and Aphex Twin, and he designed the popular Magnetosphere music visualizer in Apple’s iTunes. He is the foremost implementer of Cinder, a C++ graphics framework that underlies much of our work, and is engaged in constant investigations of emergent complexity in generative design, much like the rest of us here at Bloom.
We’re very excited about what lies ahead in the coming years. The ways in which people interact with computation are changing swiftly as we move into more casual relationships with our digital services on tablets, big screens, and across social networks. We believe we have some compelling answers about how digital experiences will evolve into these new contexts. Please, follow along with us and explore these playful, dynamic instruments of discovery together.