Visualizing Community

Visualizing Community

A new project unfolding in Latin America links scientists, local communities, and development experts in an effort improve long-term access to clean water. The key to their work? "A-MANO," an innovative tool that draws upon local knowledge and participation to generate maps that are not only crowdsourced but also crowdvisualized.

To date at Visualizing, we’ve largely explored what one might call the expert-led model of visualization: data is gleaned from any one of a huge variety of sources, from peer-reviewed scientific reports to crowd-generated Twitter streams, from archives of global demographic statistics to the servers linked to a subterranean particle smasher.

Qualitative or quantitative, large or small, the data sets then go into the hands of a rarefied bunch – designers, coders, and programmers with the skills to transform information into its visible incarnation. Undoubtedly, this method can generate some stunning results, especially when, as the best information visualizers know, technical skill is layered with a deep understanding of human cognition, aesthetics, and the rapidly evolving social and technological infrastructures of human society.

But what if, instead of experts, those who generated the data in the first place could also help to generate the visualization? That is, what if data were not only crowdsourced, but also crowdvisualized? Today, we pivot to a team of researchers attempting just such an effort, with an innovative tool dubbed "A-MANO," for the Spanish "at hand."

Fotomapeo en Toninchincalaj, Guatemala. In this video, mapping participants identify houses. The image in the map includes an entire microwatershed and the numerous communities within it. These communities are labeled in the map legend (off-screen) and the microwatershed has been delineated with a thick yellow line. These map elements helped the participants orient themselves.

A-MANO is a community-based tool, now being piloted in Latin America, that relies on locals both as data sources and designers: working alongside technical specialists, community members contribute their intimate knowledge of the landscape and its resources to create high-fidelity visual representations of their physical environs. A-MANO was developed by researchers from the University of California, Davis in collaboration with "Proyecto Mi Cuenca" a partnership made up of several local and global NGOs working together under the auspices of the Global Water Initiative We recently caught up with Matthew Hamilton, a student in the International Agricultural Development Graduate Group at UC Davis, who has spent several months in El Salvador, Honduras, Guatemala, and Nicaragua working with local technical specialists to develop A-MANO and get it off - or perhaps more accurately, onto - the ground.

V: How do you typically describe A-MANO?

MH: In the technical lingo, A-MANO is a "map-based methodology for visualization, analysis, and communication of multidimensional data." But to give you a better sense of what it is, it’s easier for me to explain how it works: with A-MANO, stakeholders involved in community-based development projects help transform a high-resolution satellite image into a dynamic map of their physical environment. In sequential mapping sessions, local people and technical specialists collaborate to put their respective knowledge on the map. In so doing, the map becomes much more than a visual representation of the community. The benefits run in two directions: When development practitioners add to the map the technical data they have gathered, local people gain access to a valuable body of knowledge. What's more, this knowledge is recorded in an accessible format that they can use in their interactions with local governments and NGOs. Or this knowledge may help community organizations - such as a farmers' cooperative or reforestation committee - work more effectively. At the same time, when local people contribute their knowledge to the map, development practitioners gain access to a comprehensive and multi-layered body of data that they can use to better target their efforts.

The key is the use of a satellite photo as a base layer of the map. Because local people can literally see their community during the participatory mapping phase of A-MANO, they can quickly identify and accurately map features.

In sequential mapping sessions local people and technical specialists collaborate to put their respective knowledge on the map.

V: What kinds of information would community members be adding to the map? For instance, would they simply mark "River" on the map, or would they also describe how they use the river for things like food, water, and transportation?

MH: Community members primarily map physical features (such as water sources, and other natural resources) and land use / land cover characteristics (such as farmland, pasture, forested lands, and so on). Each point, line, and polygon that appears on the map then serves as a spatial reference point for a wealth of descriptive information, which we record on data forms and in notebooks, later to be digitized along with the physical map. That descriptive information might include all the soil conservation activities that community members are carrying out in each tract of agricultural land. Or it might provide a history of previous land uses in a site that has recently been reforested. Once documented on the map, this local environmental knowledge can be integrated with other sources of data, which is when things really get interesting.

V: How does this technique represent an improvement over the current "best practice" methods in environmental resource management?

MH: Collecting substantial quantities of locally verified data no longer requires technical specialists to spend days traversing the community with a GPS and a backpack full of interview forms. Instead they can collect they information they need through an effective and enjoyable exercise that allows them to engage with local people.

V: What was the original catalyst for A-MANO?

MH: We developed A-MANO to help gather information for evaluation of the Global Water Initiative in Central America. The Global Water Initiative has adopted a strategy of "Monitoring and Learning," in which early successes and lessons learned guide decision-making during subsequent phases of the project. For Monitoring and Learning to be successful, fairly comprehensive datasets must be collected regularly-and A-MANO has demonstrated its value in that regard.

From the beginning, we recognized that A-MANO could also serve as an effective tool for on-the-ground decision-making. Data collection is great, but A-MANO also really stands out as a visualization tool. Community-based natural resource management is complicated business, and maps represent a powerful way to quickly assess complex local situations. And the satellite photos are critical not just because they facilitate the collection of spatially accurate data, but because they represent a base layer of the map which is meaningful to local people. In the maps, these people can see their houses, their farms, their soccer field - and for that reason, the layers of natural resource management data above the photo become real in ways that data in a report or spreadsheet can never be. Because these data are meaningful to local people and technical specialists alike, they help both groups to better communicate and make decisions.

V: So far, has using A-MANO in Latin America led to any concrete results?

MH: As one example, in northeast El Salvador, representatives of two neighboring communities got together to participate in an A-MANO mapping exercise. While mapping both their communities, people realized that untreated wastewater from one community was likely contaminating a spring in the other community. That discovery was a direct result of the mapping exercise. Later, a group got together and came up with a plan for how to treat the wastewater.

V: Is A-MANO's utility limited to water resource management? If not, what kinds of scientific or humanitarian initiatives could benefit from participatory mapping?

MH: Not at all. A-MANO could be applied effectively in any other field in which highly accurate local-level spatial information could be used to improve decision-making. For example, we see a role for A-MANO in biodiversity protection, conservation of marine resources, disaster relief, rural nutrition assessment, and so on.

Fotomapeo en Escalon, El Salvador. In this video, community members use a map as a point of reference to describe their community to a government official. They also begin to envision how they might use the map as a tool to help improve social welfare and natural resource management in the future.

V: What are some of the challenges you’ve encountered in piloting community-based visualization? What are some of the early insights?

MH: A key challenge is explaining the value of A-MANO not just in terms of gathering and analyzing data - but also as a visualization tool. Visualization helps people learn, exchange knowledge, and ultimately make decisions. Local community members tend to immediately understand the value of A-MANO as a visualization tool, while technical specialists tend to be much more interested in analysis.

One of the most important insights we’ve gained so far is that the group of technical specialists (the NGO staff) facilitating A-MANO must participate as fully in the mapping exercises as do the local people. With the combination of technical data and local environmental knowledge, the map really comes alive, and leads people to see old problems in new ways.

V: How are you sharing some of these insights with others in the field? If people want to learn more about participatory mapping, for example, where can they go?

MH: Check out - we’ve posted technical documentation (including a number of step-by-step manuals), sample data forms, videos, and other related materials.

We’ve been communicating with a few organizations that have expressed interest in adapting A-MANO to their own work. Catholic Relief Services has just applied the methodology for watershed management efforts in Haiti. We’ve also been in touch with Mercy Corps about possibilities for using some variation of A-MANO for natural resource protection in Colombia. Sharing our own insights has been very rewarding for us. At the same time, we are certain that other organizations have been using similar tools and techniques–and we would very much like to compare notes and learn from others who have experience in applying a methodology similar to A-MANO.

In the end, A-MANO is really all about bringing people together - whether they be scientists, local peoples, development practitioners, or policymakers - to share and communicate knowledge using visual media. So in one respect, A-MANO may be a new way to do that, but at the same time, it’s practically the oldest idea in the world.

Add a Comment

Login or register to post comments