This data visualization from Kiva's 2011 Annual Report is worth taking a look at for the way that it takes a significant amount of data and designs the presentation so you can quickly see the patterns.

Even if the music isn't your thing, the idea that a platform was developed to facilitate the exchange of resources between people - money from lenders, updates, stories and a sense of purpose from borrowers (small business partners, really) - is valuable and worth contemplating further for all aspects of organizational strategy. I don't see these structures as nice extras, they are the heart of a new way of cooperating though they have yet to find their way into the psyche of most organizations.

Data Visualization - Minimum Wage in Europe

This is a dataset available on Google via Public Data Explorer and represents how minimum wages have changed in Europe since 1999. There are other very interesting datasets and with various governments around the world opening up public data, this is an important research space to watch and explore for stories.

Dynamic Particles form Network

Seeing information in motion powerful because we get a sense of the relational dimensions of data. Each piece  of data can be examined but we can't understand the patterns and possible implications until we see the wider context and the dynamics of that context. Though the following video wasn't devised to simulate network formation, I couldn't help but see the deep connection to how various agents/people in motion form networks over time that are patterned but not neatly.


In this program, variables can be changed and the program re-run. The crossing point in this came with my recent reading of Greg Spencer's paper "Creative economies of scale: an agent-based model of creativity and agglomeration" which features modelling of the dynamics of location, knowledge generation, and innovation. When the ideas in that paper are considered alongside Alvin's art/visualization/programming work, the possibilities are intriguing. Here's what Alvin says about his project:

Form finding particle field may generate a variety of forms through simple behavioural interactions. The interactions are dependant on variables such as displacement, proximity and density.

With some adjustment of variables, we can see how people, rather than particles, might form communities of practice, social gatherings, business connections, and other identifiable social patterns. Simulation does not equal an understanding of what actually exists, how it has changed or, most importantly, how it may change in the future. But if we set aside the predictive grail, modelling and simulations can help us gain understanding about how multiple variables interact over time. That can be useful indeed and the visualizations produced are powerful educational tools. They are also fantastic in translating specialized knowledge and complexity into a form that a whole range of people can understand and appreciated.



Depth Of Field (DoF) w/o Blur from Alvin C. on Vimeo.

Data Visualization - "See" Stanford Ph.D. Topic Relationships

There is little question that data visualization is becoming an increasingly powerful tool as more and more people are able to access the explosion of software options and use that software to view their data. This data visualization project from Stanford is particularly interesting. It allows you to click on a discipline and then see how that discipline relates to other disciplines based on Ph.D. dissertations written at Stanford 1993-2008. 

You can click here to see it live. Having seen how it works, the next thing is to ask what it means. What does the visualization tell us? What new information is created by the various combinations of existing information that was loaded into the software? 

You will see that certain disciplines have had more dissertations written within them than others. Some are more isolated than others. Education and sociology have an interesting (though not surprising) connection and if you look at economics, you'll see interesting approaches from disciplines in different parts of the circle. The gray shadowing gives a sense of what the overall representation is before you start clicking. If you move the slider to the far left and then use your arrow keys, you can see what happens year-to-year within whatever discipline you've selected. Another interesting one is that ethics scarcely moves the medicine/biology groupings at all.

If you took all universities and all disciplines over time, you would have a clear sense of where the intellectual investments have been made over time. Overlay funding, grants, publishing, commercialization and other data sources and a very intriguing dynamic of higher education would be created. 

Visualize Language Acquisition - See Social Interaction

This Deb Roy TEDtalk is a stunning example of directions that data visualization might go - even complex data like thousands of hours of video and audio. Linking that to the study of people (language acquisition in this case) demonstrates how it might be used in person-to-person interactions but also within wide populations as well (the Obama speech that is analyzed).

What doesn't this kind of analysis tell us? What gets left out? What are the hazards?

Invisible Cities: Seeing Beyond the Buildings

This is a very interesting project that adds a clear visual element to the idea that we need to map our cities using more than the traditional statistical data (that is also very important). We need to see the weave of the city, what can't be gained by looking at buildings. Ethnography approaches could really be enhanced by this tool.


I am extremely keen to learn about this kind of approach for Hamilton, ON. 


Invisible Cities from Christian Marc Schmidt on Vimeo.