Monthly Archives: August 2012

Crisis Mapping for Disaster Preparedness, Mitigation and Resilience

Crisis mapping for disaster preparedness is nothing new. In 2004, my colleague Suha Ulgen spearheaded an innovative project in Istanbul that combined public participation and mobile geospatial technologies for the purposes of disaster mitigation. Suha subsequently published an excellent overview of the project entitled “Public Participation Geographic Information Sharing Systems for Co-mmunity Based Urban Disaster Mitigation,” available in this edited book on Geo-Information for Disaster Management. I have referred to this project in count-less conversations since 2007  so it is high time I blog about it as well.

Suha’s project included a novel “Neighborhood Geographic Information Sharing System,” which “provided volunteers with skills and tools for identification of seismic risks and response assets in their neighborhoods. Field data collection volunteers used low-cost hand-held computers and data compiled was fed into a geospatial database accessible over the Internet. Interactive thematic maps enabled discussion of mitigation measures and action alternatives. This pilot evolved into a proposal for sustained implementation with local fire stations.” Below is a screenshot of the web-based system that enabled data entry and query.

There’s no reason why a similar approach could not be taken today, one that uses a dedicated smart phone app combined with integrated gamification and social networking features. The idea would be to make community mapping fun and rewarding; a way to foster a more active and connected community—which would in turn build more social capital. In the event of a disaster, this same smart phone app would allow users to simply “check in” to receive information on the nearest shelter areas (response assets) as well as danger zones such as overpasses, etc. This is why geo-fencing is so important for crisis mapping.

(Incidentally, Suha’s project also included a “School Commute Contingency Pilot” designed to track school-bus routes in Istanbul and thus “stimulate contingency planning for commute-time emergencies when 400,000 students travel an average of 45 minutes each way on 20,000 service buses. [GPS] data loggers were used to determine service bus routes displayed on printed maps high-lighting nearest schools along the route.” Suha proposed that “bus-drivers, parents and school managers be issued route maps with nearest schools that could serve as both meeting places and shelters”).

Fast forward to 2012 and the Humanitarian OpenStreetMap’s (HOT) novel project “Community Mapping for Exposure in Indonesia,” which resulted in the mapping of over 160,000 buildings and numerous village level maps in under ten months. The team also organized a university competition to create incentives for the mapping of urban areas. “The students were not only tasked to digitize buildings, but to also collect building information such building structure, wall type, roof type and the number of floors.” This contributed to the mapping and codification of some 30,000 buildings.

As Suha rightly noted almost 10 years ago, “for disaster mitigation measures to be effective they need to be developed in recognition of the local differences and adopted by the active participation of each community.” OSM’s work in Indonesia fully embodies the importance of mapping local differences and provides important insights on how to catalyze community participation. The buildup of social capital is another important outcome of these efforts. Social capital facilitates collective action and increases local capacity for self-organization, resulting in greater social resilience. In sum, these novel projects demonstrate that technologies used for crisis mapping can be used for disaster preparedness, mitigation and resilience.

Crowdsourcing Crisis Response Following Philippine Floods

Widespread and heavy rains resulting from Typhoon Haikui have flooded the Philippine capital Manila. Over 800,000 have been affected by the flooding and some 250,000 have been relocated to evacuation centers. Given the gravity of the situation, “some resourceful Filipinos put up an online spreadsheet where concerned citizens can list down places where help is most urgently needed” (1). Meanwhile, Google’s Crisis Response Team has launched this resource page  which includes links to News updates, Emergency contact information, Person Finder and this shelter map.

Filipinos volunteers are using an open (but not editable) Google Spreadsheet and crowdsourcing reports using this Google Form to collect urgent reports on needs. The spreadsheet (please click the screenshot below to enlarge) includes time of incident, location (physical address), a description of the alert (many include personal names and phone numbers) and the person it was reported by. Additional fields include status of the alert, the urgency of this alert and whether action has been taken. The latter is also color coded.

“The spreadsheet can easily be referenced by any rescue group that can access the web, and is constantly updated by volunteers real-time” (2). This reminds me a lot of the Google Spreadsheets we used following the Haiti Earthquake of 2010. The Standby Volunteer Task Force (SBTF) continues to use Google Spreadsheets in similar aways but for the purposes of media monitoring and these are typically not made public. What is noteworthy about these important volunteer efforts in the Philippines is that the spreadsheet was made completely public in order to crowdsource the response.

As I’ve noted before, emergency management professionals cannot be every-where at the same time, but the crowd is always there. The tradeoff with the use of open data to crowdsource crisis response is obviously privacy and data protection. Volunteers may therefore want to let those filling out the Google Form know that any information they provide will or may be made public. I would also recommend that they create an “About Us” or “Who We Are” link to cultivate a sense of trust with the initiative. Finally, crowdsourcing offers-for-help may facilitate the “matchmaking” of needs and available resources.

I would give the same advice to volunteers who recently setup this Crowdmap of the floods. I would also suggest they set up their own Standby Volunteer Task Force (SBTF) in order to deploy again in the future. In the meantime, reports on flood levels can be submitted to the crisis map via webform, email and SMS.

Traditional vs. Crowdsourced Election Monitoring: Which Has More Impact?

Max Grömping makes a significant contribution to the theory and discourse of crowdsourced election monitoring in his excellent study: “Many Eyes of Any Kind? Comparing Traditional and Crowdsourced Monitoring and their Contribu-tion to Democracy” (PDF). This 25-page study is definitely a must-read for anyone interested in this topic. That said, Max paints a false argument when he writes: “It is believed that this new methodology almost magically improves the quality of elections [...].” Perhaps tellingly, he does not reveal who exactly believes in this false magic. Nor does he cite who subscribes to the view that  “[...] crowdsourced citizen reporting is expected to have significant added value for election observation—and by extension for democracy.”

My doctoral dissertation focused on the topic of crowdsourced election observa-tion in countries under repressive rule. At no point in my research or during interviews with activists did I come across this kind of superficial mindset or opinion. In fact, my comparative analysis of crowdsourced election observation showed that the impact of these initiatives was at best minimal vis-a-vis electoral accountability—particularly in the Sudan. That said, my conclusions do align with Max’s principle findings: “the added value of crowdsourcing lies mainly in the strengthening of civil society via a widened public sphere and the accumulation of social capital with less clear effects on vertical and horizontal accountability.”

This is huge! Traditional monitoring campaigns don’t strengthen civil society or the public sphere. Traditional monitoring teams are typically composed of inter-national observers and thus do not build social capital domestically. At times, traditional election monitoring programs may even lead to more violence, as this recent study revealed. But the point is not to polarize the debate. This is not an either/or argument but rather a both/and issue. Traditional and crowdsourced election observation efforts can absolutely complement each other precisely because they each have a different comparative advantage. Max concurs: “If the crowdsourced project is integrated with traditional monitoring from the very beginning and thus serves as an additional component within the established methodology of an Election Monitoring Organization, the effect on incentive structures of political parties and governments should be amplified. It would then include the best of both worlds: timeliness, visualization and wisdom of the crowd as well as a vetted methodology and legitimacy.”

Recall Jürgen Habermas and his treatise that “those who take on the tools of open expression become a public, and the presence of a synchronized public increasingly constrains un-democratic rulers while expanding the right of that public.” Why is this important? Because crowdsourced election observation projects can potentially bolster this public sphere and create local ownership. Furthermore, these efforts can help synchronize shared awareness, an important catalyzing factor of social movements, according to Habermas. Furthermore, my colleague Phil Howard has convincingly demonstrated that a large active online civil society is a key causal factor vis-a-vis political transitions towards more democratic rule. This is key because the use of crowdsourcing and crowd-mapping technologies often requires some technical training, which can expand the online civil society that Phil describes and render that society more active (as occurred in Egypt during the 2010 Parliamentary Elections—see  dissertation).

The problem? There is very little empirical research on crowdsourced election observation projects let alone assessments of their impact. Then again, these efforts at crowdsourcing are only a few years old and many do’ers in this space are still learning how to be more effective through trial and error. Incidentally, it is worth noting that there has also been very little empirical analysis on the impact of traditional monitoring efforts: “Further quantitative testing of the outlined mechanisms is definitely necessary to establish a convincing argument that election monitoring has positive effects on democracy.”

In the second half of his important study, Max does an excellent job articulating the advantages and disadvantages of crowdsourced election observation. For example, he observes that many crowdsourced initiatives appear to be spon-taneous rather than planned. Therein lies part of the problem. As demonstrated in my dissertation, spontaneous crowdsourced election observation projects are highly unlikely to strengthen civil society let alone build any kind of social capital. Furthermore, in order to solicit a maximum number of citizen-generated election reports, a considerable amount of upfront effort on election awareness raising and education needs to take place in addition to partnership outreach not to mention a highly effective media strategy.

All of this requires deliberate, calculated planning and preparation (key to an effective civil society), which explains why Egyptian activists were relatively more successful in their crowdsourced election observation efforts compared to their counterparts in the Sudan (see dissertation). This is why I’m particularly skeptical of Max’s language on the “spontaneous mechanism of protection against electoral fraud or other abuses.” That said, he does emphasize that “all this is of course contingent on citizens being informed about the project and also the project’s relevance in the eyes of the media.”

I don’t think that being informed is enough, however. An effective campaign not only seeks to inform but to catalyze behavior change, no small task. Still Max is right to point out that a crowdsourced election observation project can “encou-rage citizens to actively engage with this information, to either dispute it, confirm it, or at least register its existence.” To this end, recall that political change is a two-step process, with the second—social step—being where political opinions are formed (Katz and Lazarsfeld 1955). “This is the step in which the Internet in general, and social media in particular, can make a difference” (Shirky 2010). In sum, Max argues that “the public sphere widens because this engagement, which takes place in the context of the local all over the country, is now taken to a wider audience by the means of mapping and real-time reporting.” And so, “even if crowdsourced reports are not acted upon, the very engagement of citizens in the endeavor to directly make their voices heard and hold their leaders accountable widens the public sphere considerably.”

Crowdsourcing efforts are fraught with important and very real challenges, as is already well known. Reliability of crowdsourced information, risk of hate speech spread via uncontrolled reports, limited evidence of impact, concerns over security and privacy of citizen reporters, etc. That said, it is important to note that this “field” is evolving and many in this space are actively looking for solutions to these challenges. During the 2010 Parliamentary Elections in Egypt, the U-Shahid project was able to verify over 90% of the crowdsourced reports. The “field” of information forensics is becoming more sophisticated and variants to crowdsourcing such as bounded crowdsourcing and crowdseeding are not only being proposed but actually implemented.

The concern over unconfirmed reports going viral has little to do with crowd-sourcing. Moreover, the vast majority of crowdsourced election observation initiatives I have studied moderate all content before publication. Concerns over security and privacy are issues not limited to crowdsourced election observation and speak to a broader challenge. There are already several key initiatives underway in the humanitarian and crisis mapping community to address these important challenges. And lest we forget, there are few empirical studies that demonstrate the impact of traditional monitoring efforts in the first place.

In conclusion, traditional monitors are sometimes barred from observing an election. In the past, there have been few to no alternatives to this predicament. Today, crowdsourced efforts are sure to swell up. Furthermore, in the event that traditional monitors conclude that an election was stolen, there’s little they can do to catalyze a local social movement to place pressure on the thieves. This is where crowdsourced election observation efforts could have an important contribution. To quote Max: “instead of being fearful of the ‘uncontrollable crowd’ and criticizing the drawbacks of crowdsourcing, [...] governments would be well-advised to embrace new social media. Citizens [...] will use new techno-logies and new channels for information-sharing anyway, whether endorsed by their governments or not. So, governments might as well engage with ICTs and crowdsourcing proactively.”

Big thanks to Max for this very valuable contribution to the discourse and to my colleague Tiago Peixoto for flagging this important study.

Launching a Library of Crisis Hashtags on Twitter

I recently posted the following question on the CrisisMappers list-serve: “Does anyone know whether a list of crisis hashtags exists?”

There are several reasons why such a hashtag list would be of added value to the CrisisMappers community and beyond. First, an analysis of Twitter hashtags used during crises over the past few years could be quite insightful; interesting new patterns may be evolving. Second, the resulting analysis could be used as a guide to find (and create) new hashtags when future crises unfold. Third, a library of hashtags would make it easier to collect historical datasets of crisis information shared on Twitter for the purposes of analysis & social computing research. To be sure, without this data, developing more sophisticated machine learning platforms like the Twitter Dashboard for the Humanitarian Cluster System would be serious challenge indeed.

After posting my question on CrisisMappers and Twitter, it was clear that no such library existed. So my colleague Sara Farmer launched a Google Spreadsheet to crowdsource an initial list. Since I was working on a similar list, I’ve created a combined spreadsheet which is available and editable here. Please do add any other crisis hashtags you may know about so we can make this the most comprehensive and up-to-date resource available to everyone. Thank you!

Whilst doing this research, I came across two potentially interesting and helpful hashtag websites: Hashonomy.com and Hashtags.org.

Crowdsourcing a Crisis Map of the Beijing Floods: Volunteers vs Government

Flash floods in Beijing have killed over 70 people and forced the evacuation of more than 50,000 after destroying over 8,000 homes and causing $1.6 billion in damages. In total, some 1.5 million people have been affected by the floods after Beijing recorded the heaviest rainfall the city has seen in more than 60 years.

The heavy rains began on July 21. Within hours, users of the Guokr.com social network launched a campaign to create a live crisis map of the flood’s impact using Google Maps. According to TechPresident, “the result was not only more accurate than the government output—it was available almost a day earlier. According to People’s Daily Online, these crowd-sourced maps were widely circulated on Weibo [China's version of Twitter] the Monday and Tuesday after the flooding.” The crowdsourced, citizen-generated flood map of Beijing is available here and looks like this:

One advantage of working with Google is that the crisis map can also be viewed via Google Earth. That said, the government does block a number of Google services in China, which puts the regime at a handicap during disasters.

This is an excellent example of crowdsourced crisis mapping. My one recommen-dation to Chinese volunteers would be to crowdsource solutions in addition to problems. In other words, map offers of help and turn the crisis map into a local self-help map, i.e., a Match.com for citizen-based humanitarian response. In short, use the map as a platform for self-organization and crowdsource response by matching calls for help with corresponding offers of help. I would also recommend they create their own Standby Volunteer Task Force (SBTF) for crisis mapping to build social capital and repeat these efforts in future disasters.

Several days after Chinese volunteers first launched their crisis map, the Beijing Water Authority released its own map, which looks like a classic example of James Scott’s “Seeing Like a State.” The map is difficult to read and it is unclear whether the map is even a dynamic or interactive, or live for that matter. It appears static and cryptic. One wonders whether these adjectives also describe the government’s response.

Meanwhile, there is growing anger over the state’s botched response to the floods. According to People’s Daily, “Chinese netizens have criticised the munici-pal authority for failing to update the city’s run-down drainage system or to pre-warn residents about the impending disaster.” In other cities, Guangdong Mobile (the local division of China Mobile) sent out 30 million SMS about the storm in cooperation with the provincial government. “Mobile users in Shenzhen, Zhongshan, Zhuhai, Jiangmen, and Yunfu received reminders to be careful from the telecom company because those five cities were forecast to be most affected by the storm.”

All disasters are political. They test the government’s capacity. The latter’s inability to respond swiftly and effectively has repercussions on citizens’ perception of governance and statehood. The more digital volunteers engage in crisis mapping, the more they highlight the local capacity and agency of ordinary citizens to create shared awareness and help themselves—with or without the state. In doing so, volunteers build social capital, which facilitates future collective action both on and offline. If government officials are not worried about their own failures in disaster management, they should be. This failure will continue to have political consequences, in China and elsewhere.