I had some fruitful conversations with colleagues at the UN this week and learned about an interesting initiative called the MDG Monitor. The platform is being developed in collaboration with the Parsons Institute for Information Mapping (PIIM).
Introduction
The purpose of the MDG Monitor is to provide a dynamic and interactive mapping platform to visualize complex data and systems relevant to the Millennium Development Goals (MDGs). The team is particularly interested in having the MDG Monitor facilitate the visualization of linkages, connections and relationships between the MDGs and underlying indicators: “We want to understand how complex systems work.”
The icons above represent the 8 development goals.
The MDG Monitor is thus designed to be a “one-stop-shop for information on progress towards the MDGs, globally and at the country level.” The platform is for “policymakers, development practitioners, journalists, students and others interested in learning about the Goals and tracking progress toward them.”
The platform is under development but I saw a series of compelling mock-ups and very much look forward to testing the user-interface when the tool becomes public. I was particularly pleased to learn about the team’s interest in visualizing both “high frequency” and “low frequency” data. The former being rapidly changing data versus the latter slow change data.
In addition, the platform will allow users to drill down below the country admin level and overlay multiple layers. As one colleague mentioned, “We want to provide policy makers with the equivalent of a magnifying glass.”
Network Analysis
Perhaps most impressive but challenging is the team’s interest in combining spatial analysis with social networking analysis (SNA). For example, visualizing data or projects based on their geographic relationships but also on their functional relationships. I worked on a similar project at the Santa Fe Institute (SFI) back in 2006, when colleagues and I developed an Agent Based Model (ABM) to simulate internal displacement of ethnic groups following a crisis.
Agent Based Model of Crisis Displacement
As the screenshot above depicts, we were interested in understanding how groups would move based on their geographical and ethnic or social ties. In any case, if the MDG Monitor team can combine the two types of dynamic maps, this will certainly be a notable advance in the field of crisis mapping.
iRevolutions 
Hi Patrick,
Great summary of the work being done to create dynamic analytic tools to monitor achievement of the MDG’s. In addition, thanks for your comments on how the integration of SNA maps and geo-spatial maps would be an advance in the field of crisis mapping.
I would like to add that this work evolved from a recognition of need for more sophisticated analytic tools for socio-cultural and political economic analyses in general….and crisis mapping thus falls under this larger umbrella of social science research.
Thus the work being done to construct dynamic visual analytic tools has broad implications for the future of governance mechanisms. What we are striving to do is create a tool that allows us to better understand the social dynamics and underlying relationships that emerge when we can actually SEE the patterns of “who is doing what where” that social action—and interactions—-create. Clearly this is vital so that we can better understand crises–ie. the implications of conflicts between ethnic groups, or the loss of sovereign lands, or the failure of crops.
However, these tools are also being designed to provide evidence and information in new ways so that we can have a more precise understanding of the “workings” of social relationships in general. This new deeper understanding of social dynamics can then be the basis of more realistic political/economic theories, appropriate governance mechanisms, and sustainable national/international policies in the 21st century global context.
Hi Jerri, many thanks for this additional information, very interesting work.