Tag Archives: Preparedness

Zooniverse: The Answer to Big (Crisis) Data?

Both humanitarian and development organizations are completely unprepared to deal with the rise of “Big Crisis Data” & “Big Development Data.” But many still hope that Big Data is but an illusion. Not so, as I’ve already blogged here, here and here. This explains why I’m on a quest to tame the Big Data Beast. Enter Zooniverse. I’ve been a huge fan of Zooniverse for as long as I can remember, and certainly long before I first mentioned them in this post from two years ago. Zooniverse is a citizen science platform that evolved from GalaxyZoo in 2007. Today, Zooniverse “hosts more than a dozen projects which allow volunteers to participate in scientific research” (1). So, why do I have a major “techie crush” on Zooniverse?

Oh let me count the ways. Zooniverse interfaces are absolutely gorgeous, making them a real pleasure to spend time with; they really understand user-centered design and motivations. The fact that Zooniverse is conversent in multiple disciplines is incredibly attractive. Indeed, the platform has been used to produce rich scientific data across multiple fields such as astronomy, ecology and climate science. Furthermore, this citizen science beauty has a user-base of some 800,000 registered volunteers—with an average of 500 to 1,000 new volunteers joining every day! To place this into context, the Standby Volunteer Task Force (SBTF), a digital humanitarian group has about 1,000 volunteers in total. The open source Zooniverse platform also scales like there’s no tomorrow, enabling hundreds of thousands to participate on a single deployment at any given time. In short, the software supporting these pioneering citizen science projects is well tested and rapidly customizable.

At the heart of the Zooniverse magic is microtasking. If you’re new to microtasking, which I often refer to as “smart crowdsourcing,” this blog post provides a quick introduction. In brief, Microtasking takes a large task and breaks it down into smaller microtasks. Say you were a major (like really major) astro-nomy buff and wanted to tag a million galaxies based on whether they are spiral or elliptical galaxies. The good news? The kind folks at the Sloan Digital Sky Survey have already sent you a hard disk packed full of telescope images. The not-so-good news? A quick back-of-the-envelope calculation reveals it would take 3-5 years, working 24 hours/day and 7 days/week to tag a million galaxies. Ugh!

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But you’re a smart cookie and decide to give this microtasking thing a go. So you upload the pictures to a microtasking website. You then get on Facebook, Twitter, etc., and invite (nay beg) your friends (and as many strangers as you can find on the suddenly-deserted digital streets), to help you tag a million galaxies. Naturally, you provide your friends, and the surprisingly large number good digital Samaritans who’ve just show up, with a quick 2-minute video intro on what spiral and elliptical galaxies look like. You explain that each participant will be asked to tag one galaxy image at a time by simply by clicking the “Spiral” or “Elliptical” button as needed. Inevitably, someone raises their hands to ask the obvious: “Why?! Why in the world would anyone want to tag a zillion galaxies?!”

Well, only cause analyzing the resulting data could yield significant insights that may force a major rethink of cosmology and our place in the Universe. “Good enough for us,” they say. You breathe a sigh of relief and see them off, cruising towards deep space to bolding go where no one has gone before. But before you know it, they’re back on planet Earth. To your utter astonishment, you learn that they’re done with all the tagging! So you run over and check the data to see if they’re pulling your leg; but no, not only are 1 million galaxies tagged, but the tags are highly accurate as well. If you liked this little story, you’ll be glad to know that it happened in real life. GalaxyZoo, as the project was called, was the flash of brilliance that ultimately launched the entire Zooniverse series.

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No, the second Zooniverse project was not an attempt to pull an Oceans 11 in Las Vegas. One of the most attractive features of many microtasking platforms such as Zooniverse is quality control. Think of slot machines. The only way to win big is by having three matching figures such as the three yellow bells in the picture above (righthand side). Hit the jackpot and the coins will flow. Get two out three matching figures (lefthand side), and some slot machines may toss you a few coins for your efforts. Microtasking uses the same approach. Only if three participants tag the same picture of a galaxy as being a spiral galaxy does that data point count. (Of course, you could decide to change the requirement from 3 volunteers to 5 or even 20 volunteers). This important feature allows micro-tasking initiatives to ensure a high standard of data quality, which may explain why many Zooniverse projects have resulted in major scientific break-throughs over the years.

The Zooniverse team is currently running 15 projects, with several more in the works. One of the most recent Zooniverse deployments, Planet Four, received some 15,000 visitors within the first 60 seconds of being announced on BBC TV. Guess how many weeks it took for volunteers to tag over 2,000,0000 satellite images of Mars? A total of 0.286 weeks, i.e., forty-eight hours! Since then, close to 70,000 volunteers have tagged and traced well over 6 million Martian “dunes.” For their Andromeda Project, digital volunteers classified over 7,500 star clusters per hour, even though there was no media or press announce-ment—just one newsletter sent to volunteers. Zooniverse de-ployments also involve tagging earth-based pictures (in contrast to telescope imagery). Take this Serengeti Snapshot deployment, which invited volunteers to classify animals using photographs taken by 225 motion-sensor cameras in Tanzania’s Serengeti National Park. Volunteers swarmed this project to the point that there are no longer any pictures left to tag! So Zooniverse is eagerly waiting for new images to be taken in Serengeti and sent over.

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One of my favorite Zooniverse features is Talk, an online discussion tool used for all projects to provide a real-time interface for volunteers and coordinators, which also facilitates the rapid discovery of important features. This also allows for socializing, which I’ve found to be particularly important with digital humanitarian deployments (such as these). One other major advantage of citizen science platforms like Zooniverse is that they are very easy to use and therefore do not require extensive prior-training (think slot machines). Plus, participants get to learn about new fields of science in the process. So all in all, Zooniverse makes for a great date, which is why I recently reached out to the team behind this citizen science wizardry. Would they be interested in going out (on a limb) to explore some humanitarian (and development) use cases? “Why yes!” they said.

Microtasking platforms have already been used in disaster response, such as MapMill during Hurricane SandyTomnod during the Somali Crisis and CrowdCrafting during Typhoon Pablo. So teaming up with Zooniverse makes a whole lot of sense. Their microtasking software is the most scalable one I’ve come across yet, it is open source and their 800,000 volunteer user-base is simply unparalleled. If Zooniverse volunteers can classify 2 million satellite images of Mars in 48 hours, then surely they can do the same for satellite images of disaster-affected areas on Earth. Volunteers responding to Sandy created some 80,000 assessments of infrastructure damage during the first 48 hours alone. It would have taken Zooniverse just over an hour. Of course, the fact that the hurricane affected New York City and the East Coast meant that many US-based volunteers rallied to the cause, which may explain why it only took 20 minutes to tag the first batch of 400 pictures. What if the hurricane had hit a Caribbean instead? Would the surge of volunteers may have been as high? Might Zooniverse’s 800,000+ standby volunteers also be an asset in this respect?

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Clearly, there is huge potential here, and not only vis-a-vis humanitarian use-cases but development one as well. This is precisely why I’ve already organized and coordinated a number of calls with Zooniverse and various humanitarian and development organizations. As I’ve been telling my colleagues at the United Nations, World Bank and Humanitarian OpenStreetMap, Zooniverse is the Ferrari of Microtasking, so it would be such a big shame if we didn’t take it out for a spin… you know, just a quick test-drive through the rugged terrains of humanitarian response, disaster preparedness and international development. 


Postscript: As some iRevolution readers may know, I am also collaborating with the outstanding team at  CrowdCrafting, who have also developed a free & open-source microtasking platform for citizen science projects (also for disaster response here). I see Zooniverse and CrowCrafting as highly syner-gistic and complementary. Because CrowdCrafting is still in early stages, they fill a very important gap found at the long tail. In contrast, Zooniverse has been already been around for half-a-decade and can caters to very high volume and high profile citizen science projects. This explains why we’ll all be getting on a call in the very near future. 

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.

On Technology and Building Resilient Societies to Mitigate the Impact of Disasters

I recently caught up with a colleague at the World Bank and learned that “resilience” is set to be the new “buzz word” in the international development community. I think this is very good news. Yes, discourse does matter. A single word can alter the way we frame problems. They can lead to new conceptual frameworks that inform the design and implementation of development projects and disaster risk reduction strategies.

The term resilience is important because it focuses not on us, the development and disaster community, but rather on local at-risk communities. The terms “vulnerability” and “fragility” were used in past discourse but they focus on the negative and seem to invoke the need for external protection, overlooking the possibility that local coping mechanisms do exist. From the perspective of this top-down approach, international organizations are the rescuers and aid does not arrive until they arrive.

Resilience, in contrast, implies radical self-sufficiency, and self-sufficien-cy suggests a degree of autonomy; self-dependence rather than dependence on an external entity that may or may not arrive, that may or may not be effective, and that may or may not stay the course. In the field of ecology, the term resilience is defined as “the capacity of an ecosystem to respond to a perturbation or disturbance by resisting damage and recovering quickly.” There are thus at least two ways for “social ecosystems” to be resilient:

  1. Resist damage by absorbing and dampening the perturbation.
  2. Recover quickly by bouncing back.

So how does a society resist damage from a disaster? As noted in an earlier blog post, “Disaster Theory for Techies“, there is no such thing as a “natural disaster”. There are natural hazards and there are social systems. If social systems are not sufficiently resilient to absorb the impact of a natural hazard such as an earthquake, then disaster unfolds. In other words, hazards are exogenous while disasters are the result of endogenous political, economic, social and cultural processes. Indeed, “it is generally accepted among environmental geographers that there is no such thing as a natural disaster. In every phase and aspect of a disaster—causes, vulnerability, preparedness, results and response, and reconstruction—the contours of disaster and the difference between who lives and dies is to a greater or lesser extent a social calculus” (Smith 2006).

So how do we take this understanding of disasters and apply it to building more resilient communities? Focusing on people-centered early warning systems is one way to do this. In 2006, the UN’s International Strategy for Disaster Reduction (ISDR) recognized that top-down early warning systems for disaster response were increasingly ineffective. They therefore called for a more bottom-up approach in the form of people-centered early warning systems. The UN ISDR’s Global Survey of Early Warning Systems (PDF), defines the purpose of people-centered early warning systems as follows:

“… to empower individuals and communities threatened by hazards to act in sufficient time and in an appropriate manner so as to reduce the possibility of personal injury, loss of life, damage to property and the environment, and loss of livelihoods.”

Information plays a central role here. Acting in sufficient time requires having timely information about (1) the hazard(s) and (2) how to respond. As some scholars have argued, a disaster is first of all “a crisis in communicating within a community—that is, a difficulty for someone to get informed and to inform other people” (Gilbert 1998). Improving ways for local communities to communicate internally is thus an important part of building more resilient societies. This is where information and communication technologies (ICTs) play an important role. Free and open source software like Ushahidi can also be used (the subject of a future blog post).

Open data is equally important. Local communities need to access data that will enable them to make more effective decisions on how to best minimize the impact of certain hazards on their livelihoods. This means accessing both internal community data in real time (the previous paragraph) and data external to the community that bears relevance to the decision-making calculus at the local level. This is why I’m particularly interested in the Open Data for Resilience Initiative (OpenDRI) spearheaded by the World Bank’s Global Facility for Disaster Reduction and Recovery (GFDRR). Institutionalizing OpenDRI at the state level will no doubt be a challenge in and of itself, but I do hope the initiative will also be localized using a people-centered approach like the one described above.

The second way to grow more resilient societies is by enabling them to recover quickly following a disaster. As Manyena wrote in 2006, “increasing attention is now paid to the capacity of disaster-affected communities to ‘bounce back’ or to recover with little or no external assistance following a disaster.” So what factors accelerate recovery in ecosystems in general? “To recover itself, a forest ecosystem needs suitable interactions among climate conditions and bio-actions, and enough area.” In terms of social ecosystems, these interactions can take the form of information exchange.

Identifying needs following a disaster and matching them to available resources is an important part of the process. Accelerating the rate of (1) identification; (2) matching and, (3) allocation, is one way to speed up overall recovery. In ecological terms, how quickly the damaged part of an ecosystem can repair itself depends on how many feedback loops (network connections) it has to the non- (or less-) damaged parts of the ecosystem(s). Some call this an adaptive system. This is where crowdfeeding comes in, as I’ve blogged about here (The Crowd is Always There: A Marketplace for Crowdsourcing Crisis Response) and here (Why Crowdsourcing and Crowdfeeding May be the Answer to Crisis Response).

Internal connectivity and communication is important for crowdfeeding to work, as is preparedness. This is why ICTs are central to growing more resilient societies. They can accelerate the identification of needs, matching and allocation of resources. Free and open source platforms like Ushahidi can also play a role in this respect, as per my recent blog post entitled “Check-In’s With a Purpose: Applications for Disaster Response.” But without sufficient focus on disaster preparedness, these technologies are more likely to facilitate spontaneous response rather than a planned and thus efficient response. As Louis Pas-teur famously noted, “Chance favors the prepared mind.” Hence the rationale for the Standby Volunteer Task Force for Live Mapping (SBTF), for example. Open data is also important in this respect. The OpenDRI initiative is thus important for both damage resistance and quick recovery.

I’m enjoying the process of thinking through these issues again. It’s been a while since I published and presented on the topic of resilience and adaptation. So I plan to read through some of my papers from a while back that addressed these issues in the context of violent conflict and climate change. What I need to do is update them based on what I’ve learned over the past four or five years.

If you’re curious and feel like jumping into some of these papers yourself, I recommend these two as a start:

  • Meier, Patrick. 2007. “New Strategies for Effective Early Response: Insights from Complexity Science.” Paper prepared for the 48th Annual Convention of the International Studies Association (ISA) in Chicago. Available online.
  • Meier, Patrick. 2007. “Networking Disaster and Conflict Early Warning Systems.” Paper prepared for the 48th Annual Convention of the Int’l Studies Association (ISA) in Chicago.  Available online.

More papers are available on my Publications page. This earlier blog post on “Failing Gracefully in Complex Systems: A Note on Resilience” may also be of interest to some readers.

Crowdsourcing Disaster Preparedness: Time for Some Disruption

We’re well into hurricane season here in Haiti but good luck finding a map on hurricane shelters and evacuation routes. One UN agency was supposed to update a 2007 map but then dropped the ball. Another agency thought they’d take on the task but now there are legal concerns since only the government has the right to decide on official emergency routes and shelters. The result? A highly vulnerable population remains largely unprepared for what many expect will be a busy hurricane season.

Creating country wide maps of hurricane shelters and evacuation routes is obviously no easy task. Or is it? If we adopt the typical top down mentality, then yes, we’re talking about just a handful of people being charged with a huge project that will take them weeks to carry out. With this approach, the maps will completed well after the end of hurricane season. Great.

What if we distributed the task and crowdsourced the maps? We could use the 2007 map of hurricane shelters as a starting point and send out targeted text messages to hundreds of mobile phone users near each of these shelters asking them to report on the condition of each shelter and the access routes. We could triangulate the responses for validation purposes. This could be done tomorrow by using a free short code just like we did during the disaster response operations earlier this year. Since the lottery is big in Haiti, this could serve as an incentive: “timely and accurate replies will qualify you for a raffle.” DigiCel has already conducted SMS raffles in the past, so there is a precedent.

The SMS replies could then be analyzed over the weekend and the results shared with local radio stations early next week. The latter could then broadcast this information on a daily basis. In the meantime, government and UN officials could conduct site visits to improve the shelters and evacuation routes.

An on-line competition could also be launched to have volunteers use Google Earth and other web-based resources to identify areas of land that are elevated in case of flooding. These volunteers could also trace viable roads/paths that lead to and from these areas and mark places that may be vulnerable to landslides and other hazards.

What about the fact that only the government has the legal right to do this? Big deal. The system is not working so it’s time to disrupt it. Would you rather have a crowdsourced disaster preparedness plan now or a government certified plan after the hurricane season? I’m tempted to ask this during tomorrow’s BarCamp Haiti which I am co-organizing with the Haitian tech company Solutions and the Ushahidi Haiti Project.

Patrick Philippe Meier