Tag Archives: Visualization

Doctor Snow’s Health Map Propaganda

Doctor John Snow’s cholera map of 1854 is often heralded as an example of how mapping can illuminate powerful insights on otherwise hidden patterns. Not so, writes Mark Monmonier in his excellent book on “Spying with Maps” which I just reviewed here.

cholera-snow-map

Mark writes the following on John Snow’s famous map:

“If disease mapping has a poster child, it’s John Snow (1813-1858), the London anesthesiologist credited with discovering the water borne transmission of cholera. [...] Snow is best known for his 1854 map showing victims’ homes clustered around Soho’s infamous Broad Street Pump, which he identified as a source of contaminated water. According to epidemiological lore, the good doctor tried unsuccessfully to convince public officials to close down the pump.”

“Undaunted, he too matters in his own hands, removed the pump’s handle, and demonstrated the correctness of his theory when new cases plummeted. Truth be told, the epidemic had already run its course. What’s more, Snow made his famous dot map several months later, for a revised edition of his book on cholera transmission. Even so, his pin map continues to embellish discussions of GIS and disease.”

“Medical geographers, GIS experts, and some epidemiologists perpetuate the Snow myth because it promotes disease mapping as a discovery tool and enhances the stature of their own disciplines. But a careful examination of Snow’s writings indicates that he understood cholera’s mode of transmission well before he made the map.”

“Although Snow was a thoughtful observer, neither his map nor those of his rivals were of any value in generating insightful hypotheses. Snow’s famous cholera map was pure propaganda—and copycat propaganda at that—but proved eminently useful later in the century, when public officials needed convincing arguments to isolate drinking water from sewage.”

Although Mark is rightfully critical of Dr. John Snow’s legendary map, the last sentence above is quite insightful. The map, while unhelpful in knowledge discovery of cholera’s source, did become “eminently useful” to influence public health policy.

Patrick Philippe Meier

Doctor Snow’s Health Map Propaganda

Doctor John Snow’s cholera map of 1854 is often heralded as an example of how mapping can illuminate powerful insights on otherwise hidden patterns. Not so, writes Mark Monmonier in his excellent book on “Spying with Maps” which I just reviewed here.

cholera-snow-map

Mark writes the following on John Snow’s famous map:

“If disease mapping has a poster child, it’s John Snow (1813-1858), the London anesthesiologist credited with discovering the water borne transmission of cholera. [...] Snow is best known for his 1854 map showing victims’ homes clustered around Soho’s infamous Broad Street Pump, which he identified as a source of contaminated water. According to epidemiological lore, the good doctor tried unsuccessfully to convince public officials to close down the pump.”

“Undaunted, he too matters in his own hands, removed the pump’s handle, and demonstrated the correctness of his theory when new cases plummeted. Truth be told, the epidemic had already run its course. What’s more, Snow made his famous dot map several months later, for a revised edition of his book on cholera transmission. Even so, his pin map continues to embellish discussions of GIS and disease.”

“Medical geographers, GIS experts, and some epidemiologists perpetuate the Snow myth because it promotes disease mapping as a discovery tool and enhances the stature of their own disciplines. But a careful examination of Snow’s writings indicates that he understood cholera’s mode of transmission well before he made the map.”

“Although Snow was a thoughtful observer, neither his map nor those of his rivals were of any value in generating insightful hypotheses. Snow’s famous cholera map was pure propaganda—and copycat propaganda at that—but proved eminently useful later in the century, when public officials needed convincing arguments to isolate drinking water from sewage.”

Although Mark is rightfully critical of Dr. John Snow’s legendary map, the last sentence above is quite insightful. The map, while unhelpful in knowledge discovery of cholera’s source, did become “eminently useful” to influence public health policy.

Patrick Philippe Meier

Spying with Maps

Mark Monmonier has written yet another excellent book on maps. I relished and reviewed his earlier book on “How To Lie with Maps” and enjoyed this one even more on “Spying with Maps.” I include below some short excerpts that I found particularly neat and interesting.

Picture 1

“Mapping, it turns out, can reveal quite a bit about what we do and who we are. I say mapping, rather than maps, because cartography is not limited to static maps printed on paper or displayed on computer screens. In the new cartographies of surveillance, the maps one looks at are less important than the spatial data systems that store and integrate facts about where we live and work. Location is a powerful key for relating disparate databanks and unearthing information [...].”

Big Brother is doing most of the watching, at least for now, but corporations, local governments, and other Little Brothers are quickly getting involved.”

“Much depends, of course, on who’s in charge, us or them, and on who ‘them’ is. A police state could exploit geographic technology to round up dissidents—imagine the Nazi SS with a GeoSurveillance Corps. By contrast, a capitalist marketer can exploit locational data by making a cleverly tailored pitch at a time and place when you’re most receptive. Control is control whether it’s blatant or subtle.”

Corrona Satellites

“Spy satellites became a top priority during the Cold War, and Congress generously supported remote sensing. [...] analysts with security clearances pored over images from the CIA’s top-secret Corona satellites at the agency’s clandestine National Reconnaissance Office (NRO).” By 1967, “a massive research and development effort had refined the [resolution] down to an impressive 1.5 meters (5 ft.).” Today’s “intelligence satellites have even sharper eyes: various estimates suggest that pictures from Corona’s most advanced successors have a resolution of roughly 3 inches.”

“Because image intelligence focuses on detecting change, 1-meter satellite imagery is often more informative [then people realize]. A new railway spur or clearing, for instance, could signify a new missile site or weapons factory. And a suspicious accumulation of vehicles might presage an imminent attack. As John Pike observes, ‘if a picture is worth 1,000 words, two pictures are worth 10,000 words.'”

“Washington strongly discourages the sale of high-resolution satellite imagery of Israel, and during the 2001 Middle Eastern campaign, the government thwarted enemy media hopes by buying exclusive rights to Ikonos imagery of Afghanistan.”

I really appreciated Mark’s take on the panopticon. His points below are largely ignored by the mainstream literature on the subject and go a long way to explaining just why satellite imagery has not (yet?) acted a strong deterrent against genocide and crimes against humanity. For more on this, please see this post on geospatial technologies for genocide prevention.

Panopticon

Panopticon

“Although the [panopticon] metaphor seems largely appropriate, I am not convinced  that the similarity between Bentham’s model prison and video surveillance tells us anything that’s not obvious about the watcher’s power over the watched. My hunch is that the prison’s walls and bars as well as the isolation of inmates in individual cells exert far greater control over prisoners’ lives than a ready ability to spy on their actions. [...] What’s relevant [...] is the power of surveillance to intimidate someone already under the watcher’s control, like a prisoner (who can be beaten), an employee (who can be fired), or a motorist who runs red lights (and could be fined or lose his or her license.”

I had come across ShotSpotter a while back but rediscovered the tool in Mark’s book. What is neat is that ShotSpotter combines audio and mapping in a way that may also be applicable to crisis mapping.

Shotspotter

Shotspotter

“[...] police in several California cities rely on ShotSpotter, which its investors describe as an ‘automatic real-time gunshot locator and display system’ [...] a clever marriage of seismic analysis and acoustic filtering. [...] Like an earthquake, a gunshot generates a sharply defined circular pulse, which expands outward at constant speed. [...] ShotSpotter’s microphones detect the wave at slightly different times depending on their distance from the shooter’s location [which the computer can use] to triangulate a location in either two or three dimension. [...] The process pinpoints gunshots within 15 yards [...].”

Patrick Philippe Meier

Information Visualization: Using Vision to Think

I just finished paging through “Readings in Information Visualization: Using Vision to Think” and came across some interesting tidbits. I’ve shared these below in the form of short excerpts.

Information Visualization

“To understand something is called “seeing” it. We try to make our ideas ‘clear,’ to bring them into ‘focus,’ to ‘arrange’ our thoughts. The ubiquity of visual metaphors in describing cognitive processes hints at a nexus of relationships between what we see and what we think.”

“The purpose of visualization is insight, not pictures.”

“The power of the unaided mind is highly overrated. Without external aids, memory, thought, and reasoning are all constrained. But human intelligence is highly flexible and adaptive, superb at inventing procedures and objects that overcome its own limits. The real powers come from devising external aids that enhance cognitive abilities. How have we increased memory, thought and reasoning? By the invention of external aids: It is these things that make us smart. An important class of external aids that make us smart are graphical inventions of all sorts.”

The progress of civilization can be read in the invention of visual artifacts, from writing to mathematics, to maps, to printing, to diagrams, to visual computing. [...] Information visualization is about [...] exploiting the dynamic, interactive, inexpensive medium of graphical computerse to devise new external aids enhancing cognitive abilities.”

“A few years ago the power of this new medium was applied to science, resulting in scientific visualization. Now it is possible to apply the medium more generally to business, to scholarship and to education.”

“It is sometimes said, ‘A picture is worth ten thousand words.’ [...] This quotation was simply made up [in 1921] by ad writer Frederick R. Barnard as an invented ‘Chinese proverb’ in a streetcar advertisement for Royal Baking Power. (The company assumed that consumers would be compelled to buy a product that had the weight of Chinese philosophy behind it). The ad writer wanted to make the point that pictures can attract attention faster than other media.”

“In 1985 [...] satellites were sending back large quantities of data, so visualization was useful as a method to accelerate its analysis and to enhance the identification of interesting phenomena.”

“Information visualization is particularly useful for monitoring large amounts of data in real time and under time pressure to make decision.”

Patrick Philippe Meier

Towards a “Theory” (or analogy) of Crisis Mapping?

The etymology of the word “theory” is particularly interesting. The word originates from the ancient Greek; theoros means “spectator,” from thea “a view” + horan “to see.” In 1638, theory was used to describe “an explanation based on observation and reasoning.” How fitting that the etymologies of “theory” resonate with the purpose of crisis mapping.

But is there a formal theory of crisis mapping per se?  There are little bits and pieces here and there, sprinkled across various disciplines, peer-reviewed journals and conference presentations. But I have yet to come across a “unified theory” of crisis mapping. This may be because the theory (or theories) are implicit and self-evident. Even so, there may be value in rendering the implicit—why we do crisis mapping—more visible.

Crises occur in time and space. Yet our study of crises (and conflict in particular) has generally focused on identifying trends over time rather than over space. Why? Because unlike the field of disaster management, we do not have seismographs scattered around the planet that  precisely pint point the source of escalating social tremors. This means that the bulk of our datasets describe conflict as an event happening in countries and years, not cities and days, let alone towns and hours.

This is starting to change thanks to several factors: political scientists are now painstakingly geo-referencing conflict data (example); natural language processing algorithms are increasingly able to extract time and place data from online media and user-generated content (example);  and innovative crowdsourcing platforms are producing new geo-referenced conflict datasets (example).

In other words, we have access to more disaggregated data, which allows us to study conflict dynamics at a more appropriate scale. By the way, this stands in contrast to the “goal of the modern state [which] is to reduce the chaotic, disorderly, constantly changing social reality beneath it to something more closely resembling the administrative grid of its observations” (1). Instead of Seeing Like a State, crisis mapping corrects the myopic grid to give us The View from Below.

Crises are patterns; by this I mean that crises are not random. Military or militia tactics are not random either. There is a method to the madnes—the fog of war not withstanding. Peace is also a pattern. Crisis mapping gives us the opportunity to detect peace and conflict patterns at a finer temporal and spatial resolution than previously possible; a resolution that more closely reflects reality at the human scale.

Why do scientists increasingly build more sophisticated microscopes? So they can get more micro-level data that might explain patterns at a macro-scale. (I wonder whether this means we’ll get to a point where we cannot reconcile quantum conflict mechanics with the general theory of conflict relativity). But I digress.

Compare analog televisions with today’s high-definition digital televisions. The latter is a closer reflection of reality. Or picture a crystal clear lake on a fine Spring day. You peer over the water and see the pattern of rocks on the bottom of the lake. You also see a perfect reflection of the leaves on the trees by the lake shore. If the wind picks up, however, or if rain begins to fall, the water drops cause ripples (“noise” in the data) that prevent us from seeing the same patterns as clearly. Crisis mapping calms the waters.

Keeping with the lake analogy, the ripples form certain patterns. Conflict is also the result of ripples in the socio-political fabric. The question is how to dampen or absorb the ripples without causing unintended ripples elsewhere? What kinds of new patterns might we generate to “cancel out” conflict patterns and amplify peaceful patterns? Thinking about patterns and anti-patterns in time and space may be a useful way to describe a theory of crisis mapping.

Some patterns may be more visible or detectable at certain temporal-spatial scales or resolutions than at others. Crisis mapping allows us to vary this scale freely; to see the Nazsca Lines of conflict from another perspective and at different altitudes. In short, crisis mapping allow us to escape the linear, two-dimensional world of Euclidean political science to see patterns that otherwise remain hidden.

In theory then, adding spatial data should improve the accuracy and explanatory power of conflict models. This should provide us with better and more rapid ways detect the patterns behind conflict ripples before they become warring tsunamis. But we need more rigorous and data-driven studies that demonstrate this theory in practice.

This is one theory of crisis mapping. Problem is, I have many others! There’s more to crisis mapping than modeling. In theory, crisis mapping should also provide better decision support, for example. Also, crisis mapping should theoretically be more conducive to tactical early response, not to mention monitoring & evaluation. Why? I’ll ramble on about that some other day. In the meantime, I’d be grateful for feedback on the above.

Patrick Philippe Meier

Towards a “Theory” (or analogy) of Crisis Mapping?

The etymology of the word “theory” is particularly interesting. The word originates from the ancient Greek; theoros means “spectator,” from thea “a view” + horan “to see.” In 1638, theory was used to describe “an explanation based on observation and reasoning.” How fitting that the etymologies of “theory” resonate with the purpose of crisis mapping.

But is there a formal theory of crisis mapping per se?  There are little bits and pieces here and there, sprinkled across various disciplines, peer-reviewed journals and conference presentations. But I have yet to come across a “unified theory” of crisis mapping. This may be because the theory (or theories) are implicit and self-evident. Even so, there may be value in rendering the implicit—why we do crisis mapping—more visible.

Crises occur in time and space. Yet our study of crises (and conflict in particular) has generally focused on identifying trends over time rather than over space. Why? Because unlike the field of disaster management, we do not have seismographs scattered around the planet that  precisely pint point the source of escalating social tremors. This means that the bulk of our datasets describe conflict as an event happening in countries and years, not cities and days, let alone towns and hours.

This is starting to change thanks to several factors: political scientists are now painstakingly geo-referencing conflict data (example); natural language processing algorithms are increasingly able to extract time and place data from online media and user-generated content (example);  and innovative crowdsourcing platforms are producing new geo-referenced conflict datasets (example).

In other words, we have access to more disaggregated data, which allows us to study conflict dynamics at a more appropriate scale. By the way, this stands in contrast to the “goal of the modern state [which] is to reduce the chaotic, disorderly, constantly changing social reality beneath it to something more closely resembling the administrative grid of its observations” (1). Instead of Seeing Like a State, crisis mapping corrects the myopic grid to give us The View from Below.

Crises are patterns; by this I mean that crises are not random. Military or militia tactics are not random either. There is a method to the madnes—the fog of war not withstanding. Peace is also a pattern. Crisis mapping gives us the opportunity to detect peace and conflict patterns at a finer temporal and spatial resolution than previously possible; a resolution that more closely reflects reality at the human scale.

Why do scientists increasingly build more sophisticated microscopes? So they can get more micro-level data that might explain patterns at a macro-scale. (I wonder whether this means we’ll get to a point where we cannot reconcile quantum conflict mechanics with the general theory of conflict relativity). But I digress.

Compare analog televisions with today’s high-definition digital televisions. The latter is a closer reflection of reality. Or picture a crystal clear lake on a fine Spring day. You peer over the water and see the pattern of rocks on the bottom of the lake. You also see a perfect reflection of the leaves on the trees by the lake shore. If the wind picks up, however, or if rain begins to fall, the water drops cause ripples (“noise” in the data) that prevent us from seeing the same patterns as clearly. Crisis mapping calms the waters.

Keeping with the lake analogy, the ripples form certain patterns. Conflict is also the result of ripples in the socio-political fabric. The question is how to dampen or absorb the ripples without causing unintended ripples elsewhere? What kinds of new patterns might we generate to “cancel out” conflict patterns and amplify peaceful patterns? Thinking about patterns and anti-patterns in time and space may be a useful way to describe a theory of crisis mapping.

Some patterns may be more visible or detectable at certain temporal-spatial scales or resolutions than at others. Crisis mapping allows us to vary this scale freely; to see the Nazsca Lines of conflict from another perspective and at different altitudes. In short, crisis mapping allow us to escape the linear, two-dimensional world of Euclidean political science to see patterns that otherwise remain hidden.

In theory then, adding spatial data should improve the accuracy and explanatory power of conflict models. This should provide us with better and more rapid ways detect the patterns behind conflict ripples before they become warring tsunamis. But we need more rigorous and data-driven studies that demonstrate this theory in practice.

This is one theory of crisis mapping. Problem is, I have many others! There’s more to crisis mapping than modeling. In theory, crisis mapping should also provide better decision support, for example. Also, crisis mapping should theoretically be more conducive to tactical early response, not to mention monitoring & evaluation. Why? I’ll ramble on about that some other day. In the meantime, I’d be grateful for feedback on the above.

Patrick Philippe Meier

Proposing the Field of Crisis Mapping

There are no books on Crisis Mapping, no peer-reviewed journals, no undergraduate or graduate courses, no professional seminars. And yet, after co-directing the Harvard Humanitarian Initiative’s (HHI) Program on Crisis Mapping and Early Warning (CM&EW) for 2-years, I can confirm that an informal field and community of crisis mapping is veritably thriving.

The incredible interest around the first International Conference on Crisis Mapping (ICCM 2009) is further testament to this effect. Over 50 organizations are expected to participate and three leading donors have come together to generously support the formalization of Crisis Mapping as a field of study and practice. The conference is co-organized by myself at HHI and my colleague Professor Jen Ziemke at John Carroll University (JCU).

The findings from HHI’s 2-year program on Crisis Mapping were invaluable in developing a proposed research agenda for the field. This agenda serves the basis of ICCM 2009. I regularly refer to this research agenda when asked by colleagues: “What is crisis mapping?” Crisis Mapping is more than mapping crisis data. There are three key pillars that I have identified as being integral to crisis mapping.

1. Crisis Map Sourcing (CMS)
2. Crisis Mapping Analysis (CMA)
3. Crisis Mapping Response (CMR)

Each of these three pillars constitutes an important area of research for crisis mapping. I briefly describe what each of these constitutes below. Professor Ziemke and I are working together to further develop the crisis mapping taxonomy I crafted at HHI. If we are to begin formalizing the field, then the community may benefit from a common language. So we’re co-authoring a paper on the topic and look forward to sharing it in the near future.

Crisis Map Sourcing

How does one collect information in such a way that mapping can add value? There are four principal methodologies in crisis map sourcing: (1) Crisis Map Coding, (2) Participatory Crisis Mapping, (3) Mobile Crisis Mapping and (4) Automated Crisis Mapping. The common thread between the three is that they each look to extract event-data for crisis mapping purposes.

Crisis Map Coding (CMC) draws on hand-coding geo-referenced event-data like the project ACLED at the Peace Research Institute, Oslo (PRIO). This methodology is widely used by political scientists as evidenced by the peer-reviewed literature on the topic.  See also Jen Ziemke’s work on hand-coding conflict data on the Angolan civil war. While manually coding event data is certainly not a new approach, the focus on geo-referencing this data is relatively recent.

Participatory Crisis Mapping (PCM) is participatory mapping with a focus on crises. A good example is the UNDP’s Threat and Risk Mapping Analysis (TRMA) project in the Sudan, which uses focus groups to map local knowledge on threats and risks at the community level.

Mobile Crisis Mapping (MCM) seeks to leverage mobile technologies for crisis mapping. This includes the use of mobile phones, geospatial technologies and unmanned areal vehicles (UAVs). Ushahidi, AAAS and ITHACA are all good examples of mobile crisis mapping in action. These different technologies enable us to experiment with new methodologies such as the crowdsourcing of crisis information, automated change detection using satellite imagery and real-time mashups with UAVs. More information on MCM is available here.

Automated Crisis Mapping (ACM) looks at natural language processing and computational linguistics to extract event-data. While this field of study is not new, it has been progressing rapidly over the years as evidenced by Crimson Hexagon’s work on sentiment extraction and the European Media Monitor’s (EMM) clustering algorithms. What is new in this area is the focus on automated mapping like GDACS and the use  semantic web parsing like BioCaster.

Crisis Mapping Analysis

How does one analyze crisis mapping data to identify patterns over space and time? There are three principle approaches in crisis mapping analysis: (1) Crisis Mapping Visualization, (2) Crisis Mapping Analytics and (3) Crisis Map Modeling. Note that there is a pressing need to enable more collaboration in the analytical process. Platforms that facilitate collaborative analytics are far and few between. In addition, there is a shift towards mobile crisis mapping analysis. That is, leveraging mobile technologies to carry out analysis such as Folksomaps and Cartagen.

Crisis Mapping Visualization (CMV) seeks to visualize data in such a way that patterns are identifiable through visual analysis, i.e., using the human eye. For example, patterns may be discernible at one spatial and/or temporal scale, but not at another. Or patterns may not appear using 2D visualization but instead using 3D, like GeoTime. Varying the speed of data animation over time may also shed light on certain patterns. More on visualization here and here.

Crisis Mapping Analytics (CMA) is GIS analysis applied to crisis data. This approach draws on applied geo-statistics and spatial econometrics to identify crisis patterns otherwise hidden to the human eye. This includes Exploratory Spatial Data Analysis (ESDA). A good example of crisis mapping analytics is HunchLab and other crime mapping analysis platforms like GeoSurveillance.

Crisis Map Modeling (CMM) combines GIS analysis with agent-based modeling. See this example published in Science. While the conclusions of the article are suspect, the general approach highlights the purpose of crisis map modeling. The point is to use empirical data to simulate different scenarios using agent-based models. My colleague Nils Wiedmann is doing some of the most interesting work in this area.

Crisis Mapping Response

Like early warning, there is little point in doing crisis mapping if it is not connected to strategic and/or operational response. There are three principle components of crisis mapping response: (1) Crisis Map Dissemination, (2) Crisis Map Decision Support, and (3) Crisis Map Monitoring and Evaluation.

Crisis Map Dissemination (CMD) seeks to disseminate maps and/or share information provided by maps. Maps can be shared in hard copy format, such as with Walking Papers. They can also be shared electronically and the underlying data synchronized using Mesh4X. Another approach is crowdfeeding, where indicator alerts are subscribed to via email or SMS.

Crisis Map Decision Support (CMDS) leverages decision-support tools specifically for crisis mapping response. This approach entails the use of interactive mapping platforms that users can employ to query crisis data. There is thus a strong link with crisis mapping analysis since the decision process is informed by the patterns identified using crisis mapping analytics. In other words, the point is to identify patterns so we can amplify, mitigate or change them. It is vital that crisis map decision support platforms have well designed user interfaces.

Crisis Map Monitoring and Evaluation (CMME) combines crisis mapping with monitoring and evaluation (M&E) to produce basemaps (baselines mapped in space and time). This approach seeks to identify project impact or lack thereof by comparing basemaps with new data being collected throughout the project cycle. More information on this approach is available here.

I’d be grateful for feedback on this proposed taxonomy.

Patrick Philippe Meier

Crisis Mapping for Monitoring & Evaluation

I was pleasantly surprised when local government ministry representatives in the Sudan (specifically Kassala) directly requested training on how to use the UNDP’s Threat and Risk Mapping Analysis (TRMA) platforms to monitor and evaluate their own programs.

Introduction

The use of crisis mapping for monitoring and evaluation (M&E) had cropped up earlier this year in separate conversations with the Open Society Institute (OSI) and MercyCorps. The specific platform in mind was Ushahidi, and the two organizations were interested in exploring the possibility of using the platform to monitor the impact of their funding and/or projects.

As far as I know, however, little to no rigorous research has been done on the use of crisis mapping for M&E. The field of M&E is far more focused on change over time than over space. Clearly, however, post-conflict recovery programs are implemented in both time and space. Furthermore, any conflict sensitivity programming must necessarily take into account spatial factors.

CartaMetrix

The only reference to mapping for M&E that I was able to find online was one paragraph in relation to the Cartametrix 4D map player. Here’s the paragraph (which I have split into to ease legibility) and below a short video demo I created:

“The Cartametrix 4D map player is visually compelling and fun to use, but in terms of tracking results of development and relief programs, it can be much more than a communications/PR tool. Through analyzing impact and results across time and space, the 4D map player also serves as a good program management tool. The map administrator has the opportunity to set quarterly, annual, and life of project indicator targets based on program components, regions, etc.

Tracking increases in results via the 4D map players, gives a program manager a sense of the pace at which targets are being reached (or not). Filtering by types of activities also provides for a quick and easy way to visualize which types of activities are most effectively resulting in achievements toward indicator targets. Of course, depending on the success of the program, an organization may or may not want to make the map (or at least all facets of the map) public. Cartametrix understands this and is able to create internal program management map applications alongside the publicly available map that doesn’t necessarily present all of the available data and analysis tools.”

Mapping Baselines

I expect that it will only be a matter of time until the M&E field recognizes the added value of mapping. Indeed, why not use mapping as a contributing tools in the M&E process, particularly within the context of formative evaluation?

Clearly, mapping can be one contributing tool in the M&E process. To be sure, baseline data can be collected, time-stamped and mapped. Mobile phones further facilitate this spatially decentralized process of information collection. Once baseline data is collected, the organization would map the expected outcomes of the projects they’re rolling out and estimated impact date against this baseline data.

The organization would then implement local development and/or conflict management programs  in certain geographical areas and continue to monitor local tensions by regularly collecting geo-referenced data on the indicators that said projects are set to influence. Again, these trends would be compared to the initial baseline.

These program could then be mapped and data on local tensions animated over time and space. The dynamic mapping would provide an intuitive and compelling way to demonstrate impact (or the lack thereof) in certain geographical areas where the projects were rolled out as compared to other similar areas with no parallel projects. Furthermore, using spatial analysis for M&E could also be a way to carry out a gap analysis and to assess whether resources are being allocated efficiently in more complex environments.

Next Steps

One of my tasks at TRMA is to develop a short document on using crisis mapping for M&E so if anyone has any leads on applied research in this area, I would be much obliged.

Patrick Philippe Meier

Pictures: Community Mapping in Action

I find the pictures below inspiring. In many ways, the action of participatory mapping is where the real added value lies. The pictures are from TRMA and IFAD and IAPAD (Vietnam, Fiji and Kenya for the latter). They depict scenes from the Sudan, Botswana, Kenya, Vietnam, Indonesia, Fiji and the Philippines. What is striking, however, is the lack of women doing the actual mapping in these photographs.

Please send me additional pictures, I’d love to include them, especially of women focus groups and projects from South America. Kindly see my previous post for pictures of social maps.

Updated: Dear All, please accept my apologies, due to copyright issues I’ve had to take the pictures off my blog. I find this both sad and ironic; ironic because the pictures were about participatory activities and yet those who took the pictures (and who are passionate about community mapping) are in fact unwilling to share these inspirational moments with others. In any case, I’ve learned my lesson and be a lot more careful in the future.

Patrick Philippe Meier

MDG Monitor: Combining GIS and Network Analysis

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.”

G8-MDG-logosThe 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.

abmSFI

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.

Patrick Philippe Meier