MicroMappers: Towards Next Generation Humanitarian Technology

The MicroMappers platform has come a long way and still has a ways to go. Our vision for MicroMappers is simple: combine human computing (smart crowd-sourcing) with machine computing (artificial intelligence) to filter, fuse and map a variety of different data types such as text, photo, video and satellite/aerial imagery. To do this, we have created a collection of “Clickers” for MicroMappers. Clickers are simply web-based crowdsourcing apps used to make sense of “Big Data”. The “Text Cicker” is used to filter tweets & SMS’s; “Photo Clicker” to filter photos; “Video Clicker” to filter videos and yes the Satellite & Aerial Clickers to filter both satellite and aerial imagery. These are the Data Clickers. We also have a collection of Geo Clickers that digital volunteers use to geo-tag tweets, photos and videos filtered by the”Data Clickers. Note that these Geo Clickers auto-matically display the results of the crowdsourced geo-tagging on our MicroMaps like the one below.

MM Ruby Tweet Map

Thanks to our Artificial Intelligence (AI) engine AIDR, the MicroMappers “Text Clicker” already combines human and machine computing. This means that tweets and text messages can be automatically filtered (classified) after some initial crowdsourced filtering. The filtered tweets are then pushed to the Geo Clickers for geo-tagging purposes. We want to do the same (semi-automation) for photos posted to social media as well as videos; although this is still a very active area of research and development in the field of computer vision.

So we are prioritizing our next hybrid human-machine computing efforts on aerial imagery instead. Just like the “Text Clicker” above, we want to semi-automate feature detection in aerial imagery by adding an AI engine to the “Aerial Clicker”. We’ve just starting to explore this with computer vision experts in Switzerland and Canada. Another development we’re eyeing vis-a-vis UAVs is live video streaming. To be sure, UAVs will increasingly be transmitting live video feeds directly to the web. This means we may eventually need to develop a “Streaming Clicker”, which would in some respects resemble our existing “Video Clicker” except that the video would be broadcasting live rather than play back from YouTube, for example. The “Streaming Clicker” is for later, however, or at least until a prospective partner organization approaches us with an immediate and compelling social innovation use-case.

In the meantime, my team & I at QCRI will continue to improve our maps (data visualizations) along with the human computing component of the Clickers. The MicroMappers smartphone apps, for example, need more work. We also need to find partners to help us develop apps for tablets like the iPad. In addition, we’re hoping to create a “Translate Clicker” with Translators Without Borders (TWB). The purpose of this Clicker would be to rapidly crowdsource the translation of tweets, text messages, etc. This could open up rather interesting possibilities for machine translation, which is certainly an exciting prospect.

MM All Map

Ultimately, we want to have one and only one map to display the data filtered via the Data and Geo Clickers. This map, using (Humanitarian) OpenStreetMap as a base layer, would display filtered tweets, SMS’s, photos, videos and relevant features from satellite and UAV imagery. Each data type would simply be a different layer on this fused “Meta-Data Crisis Map”; and end-users would simply turn individual layers on and off as needed. Note also the mainstream news feeds (CNN and BBC) depicted in the above image. We’re working with our partners at UN/OCHA, GDELT & SBTF to create a “3W Clicker” to complement our MicroMap. As noted in my forthcoming book, GDELT is the ultimate source of data for the world’s digitized news media. The 3Ws refers to Who, What, Where; an important spreadsheet that OCHA puts together and maintains in the aftermath of major disasters to support coordination efforts.

In response to Typhoon Ruby in the Philippines, Andrej Verity (OCHA) and I collaborated with Kalev Leetaru from GDELT to explore how the MicroMappers “3W Clicker” might work. The result is the Google Spreadsheet below (click to enlarge) that is automatically updated every 15 minutes with the latest news reports that refer to one or more humanitarian organizations in the Philippines. GDELT includes the original URL of the news article as well as the list of humanitarian organizations referenced in the article. In addition, GDELT automatically identifies the locations referred to in the articles, key words (tags) and the date of the news article. The spreadsheet below is already live and working. So all we need now is the “3W Clicker” to crowdsource the “What”.

MM GDELT output

The first version of the mock-up we’ve created for the “3W Clicker” is displayed below. Digital volunteers are presented with an interface that includes an news article with the names of humanitarian organizations highlighted in red for easy reference. GDELT auto-populates the URL, the organization name (or names if there are more than one) and the location. Note that both the “Who” & “Where” information can be edited directly by the volunteer incase GDELT’s automated algorithm gets those wrong. The main role of digital volunteers, however, would simply be to identify the “What” by quickly skimming the article.

MM 3W Clicker v2

The output of the “3W Clicker” would simply be another MicroMap layer. As per Andrej’s suggestion, the resulting data could also be automatically pushed to another Google Spreadsheet in HXL format. We’re excited about the possibilities and plan to move forward on this sooner rather than later. In addition to GDELT, pulling in feeds from CrisisNET may be worth exploring. I’m also really keen on exploring ways to link up with the Global Disaster Alert & Coordination System (GDACS) as well as GeoFeedia.

In the meantime, we’re hoping to pilot our “Satellite Clicker” thanks to recent conversations with Planet Labs and SkyBox Imaging. Overlaying user-generated content such as tweets and images on top of both satellite and aerial imagery can go a long way to helping verify (“ground truth”) social media during disasters and other events. This is evidenced by recent empirical studies such as this one in Germany and this one in the US. On this note, as my QCRI colleague Heather Leson recently pointed out, the above vision for MicroMappers is still missing one important data feed; namely sensors—the Internet of Things. She is absolutely spot on, so we’ll be sure to look for potential pilot projects that would allow us to explore this new data source within MicroMappers.

The above vision is a tad ambitious (understatement). We really can’t do this alone. To this end, please do get in touch if you’re interested in joining the team and getting MicroMappers to the next level. Note that MicroMappers is free and open source and in no way limited to disaster response applications. Indeed, we recently used the Aerial Clicker for this wildlife protection project in Namibia. This explains why our friends over at National Geographic have also expressed an interest in potentially piloting the MicroMappers platform for some of their projects. And of course, one need not use all the Clickers for a project, simply the one(s) that make sense. Another advantage of MicroMappers is that the Clickers (and maps) can be deployed very rapidly (since the platform was initially developed for rapid disaster response purposes). In any event, if you’d like to pilot the platform, then do get in touch.

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See also: Digital Humanitarians – The Book

Digital Jedis Complete Response to Typhoon Ruby

Thank you, Digital Jedis!

Every Click you made on MicroMappers was a gift. Typhoon Ruby (Hagupit) disrupted the lives of many and caused damage in regions already affected by previous disasters. As MicroMappers, you gave your time, clicks and skills to make a difference. Catherine, the Head of the UN’s Information Management Unit in the Philippines had this to say: “I would like to thank all the volunteers […] for their invaluable contribution over the past few days. We are lucky that Hagupit [Ruby] made less damages than expected and that the emergency quickly scaled down.”

MM Ruby Tweet Map

MicroMappers and our partners at the Standby Task Force (SBTF) were activated by the United Nations Office for the Coordination of Humanitarian Affairs (OCHA). The Mission?

To augment the situational awareness of humanitarian actors on the ground by making sense of social media generated following the Typhoon.

Over the course of 72 hours, these Digital Jedis united to MicroMap one Click at a time. By reviewing tweets and image, each MicroMapper built collective intelligence and insights that were used to build a comprehensive situational awareness reports and maps for the UN. Many hands, and in this case, Clicks, make light work.

As Catherine rightly notes, there was thankfully less damage than many feared. This explains why our MicroMaps (above and below) are thankfully not riddled with hundreds of markers. In addition, we prioritize quality over quantity at MicroMappers. Our UN partners had specifically asked for tweets related to:

(1) Requests for Help / Needs
(2) Infrastructure Damage
(3) Humanitarian Aid Provided

Together, these tweets—which are mapped above—represented less than 5% of the Ruby-related tweets that were collected during the first 72 hours of the Typhoon making landfall. This doesn’t mean that only 5% of the information on Twitter was relevant for emergency response, however. Indeed, we also tagged tweets that were not related to the above 3 categories but that were still informative. These constituted more than 20% of all tweets collected (which are not included in the map above). In the analysis provided to UN partners, we did include a review of those other relevant tweets.

MM Ruby Tweet Clicker

Some 700 Digital Jedis joined the response online, a new record for MicroMappers! An astounding 50,394 Clicks were made using the Text Clicker pictured above (each tweet was reviewed by at least 3 digital volunteers for quality assurance purposes). And a further 3,555 Clicks were carefully made by the SBTF to geo-locate (map) relevant tweets. In other words, close to 55,000 Clicks went into making the high quality map displayed above! That’s over 12 Clicks per minute non-stop for more than 4,300 consecutive minutes!

MM Ruby Image Map

The United Nations also asked Digital Jedis to identify pictures posted on Twitter that showed disaster damage. Over 30,000 Clicks went into this operation with a further 7,413 Clicks made by the SBTF to map images that showed severe and mild damage. In sum, over 40,000 Clicks went into the MicroMap above. Overall, the entire MicroMappers response was powered by close to 100,000 Clicks!

Screen Shot 2014-12-10 at 8.36.04 AMMM Infographic 2MM Infographic 3

Digital Jedis have yet again shown that together, we can help people get positively involved in their world, even when half-a-globe and many timezones away. Yes, we can and should donate $$ to support relief efforts and good causes around the world but we can also get directly involved by donating our time, or what we call M&M’s, Minutes and Mouse clicks. This year MicroMappers have mobilized to support wildlife protection in Namibia, food security efforts in the Philippines and of course this most recent response to Typhoon Ruby. On that note, thanks again to all volunteers who supported the MicroMappers response to the Typhoon in partnership with the United Nations. You truly are Digital Jedis! And the UK Guardian certainly agrees, check out their article on our digital response.

So what’s next? We will continue to solicit your feedback on how to improve the Clickers and will get started right away. (Add your MicroMappers feedback here). In the meantime, we will leave the Clickers online for newcomers who wish to practice. We are also in touch with the UN and UAV partners in the Philippines as they may soon fly their small, remote-control planes to take aerial photographs over disaster affected areas. If they do, they will send us the photographs for analysis via MicroMappers, so stay tuned.

In closing, MicroMappers was developed by QCRI in partnership SBTF/OCHA. So a million thanks to the QCRI team and SBTF for deploying MicroMappers in support of these digital humanitarian efforts. Special thanks go to Ji Lucas, Jus Mackinnon, ChaTo Castillo, Muhammad Imran, Heather Leson, Sarah Vieweg and last but certainly not least Peter Mosur.

(Ed. note: Blog post was cross-posted from MicroMappers.org. Infrographic uses Infogr.am software)

Calling All Digital Jedis: Support UN Response to Super Typhoon Ruby!

The United Nations has officially activated the Digital Humanitarian Network (DHN) in response to Typhoon Ruby. The DHN serves as the official interface between formal humanitarian organizations and digital volunteer groups from all around the world. These digital volunteers—also known as Digital Jedis— provide humanitarian organizations like the UN and the Red Cross with the “surge” capacity they need to make sense of the “Big Data” that gets generated during disasters. This “Big Data” includes large volumes of social media reports and satellite imagery, for example. And there is a lot of this data being generated right now as a result of Super Typhoon Ruby.

Typhoon Ruby

To make sense of this flash flood of information, Digital Jedis use crowdsourcing platforms like MicroMappers, which was developed in partnership with the UN Office for the Coordination of Humanitarian Affairs (OCHA). In their activation of the Digital Humanitarian Network, the UN has requested that Digital Jedis look for Ruby-related tweets that refer to needs, damage & response efforts. They have also asked digital volunteers to identify pictures of damage caused by the Typhoon. These tweets and pictures will then to be added to a live crisis map to augment the UN’s own disaster damage and needs assessment efforts.

You too can be a Digital Jedi. Trust me, MicroMappers is far easier to use than a lightsaber. All it takes is a single Click of the mouse. Yes, it really is that simple. So, if a Digital Jedi you want to be, let your first Click be this one! Following that click will set you on the path to help the United Nation’s important relief efforts in the Philippines. So if you’ve got a bit of time on your hands—even 2 minutes goes a long way—then help us make a meaningful difference in the world, join the Force! And may the Crowd be with Us!

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See also: Digital Humanitarians – The Path of the Digtal Jedis

Social Media Generates Social Capital: Implications for City Resilience and Disaster Response

A new empirical and peer-reviewed study provides “the first evidence that online networks are able to produce social capital. In the case of bonding social capital, online ties are more effective in forming close networks than theory predicts.” Entitled, “Tweeting Alone? An Analysis of Bridging and Bonding Social Capital in Online Networks,” the study analyzes Twitter data generated during three large events: “the Occupy movement in 2011, the IF Campaign in 2013, and the Chilean Presidential Election of the same year.”

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What is the relationship between social media and social capital formation? More specifically, how do connections established via social media—in this case Twitter—lead to the formation of two specific forms of social capital, bridging and bonding capital? Does the interplay between bridging and bonding capital online differ to what we see in face-to-face world interactions?

“Bonding social capital exists in the strong ties occurring within, often homogeneous, groups—families, friendship circles, work teams, choirs, criminal gangs, and bowling clubs, for example. Bonding social capital acts as a social glue, building trust and norms within groups, but also potentially increasing intolerance and distrust of out-group members. Bridging social capital exists in the ties that link otherwise separate, often heterogeneous, groups—so for example, individuals with ties to other groups, messengers, or more generically the notion of brokers. Bridging social capital allows different groups to share and exchange information, resources, and help coordinate action across diverse interests.” The authors emphasize that “these are not either/or categories, but that in well-functioning societies the two types or dimensions develop together.”

The study uses social network analysis to measure bonding and bridging social capital. More specifically, they use two associated metrics as indicators of social capital: closure and brokerage. “Closure refers to the level of connectedness between particular groups of members within a broader network and encourages the formation of trust and collaboration. Brokerage refers to the existence of structural holes within a network that are ’bridged’ by a particular member of the network. Brokerage permits the transmission of information across the entire network. Social capital, then, is comprised of the combination of these two elements, which interact over time.”

The authors thus analyze the “observed values for closure and brokerage over time and compare them with different simulations based on theoretical network models to show how they compare to what we would expect offline. From this, [they provide an evaluation of the existence and formation of social capital in online networks.”

The results demonstrate that “online networks show evidence of social capital and these networks exhibit higher levels of closure than what would be expected based on theoretical models. However, the presence of organizations and professional brokers is key to the formation of bridging social capital. Similar to traditional (offline) conditions, bridging social capital in online networks does not exist organically and requires the purposive efforts of network members to connect across different groups. Finally, the data show interaction between closure and brokerage goes in the right direction, moving and growing together.”

These conclusions suggest that the same metrics—closure and brokerage—can be used to monitor “City Resilience” before, during and after major disasters. This is of particular interest to me since my team and I at QCRI are collaborating with the Rockefeller Foundation’s 100 Resilient Cities initiative to determine whether social media can indeed help monitor (proxy indicators of) resilience. Recent studies have shown that changes in employment, economic activity and mobility—each of which is are drivers of resilience—can be gleamed from social media.

While more research is needed, the above findings are compelling enough for us to move forward with Rockefeller on our joint project. So we’ll be launching AIRS in early 2015. AIRS, which stands for “Artificial Intelligence for Resilient Societies” is a free and open source platform specifically designed to enable Rockefeller’s partners cities to monitor proxy indicators of resilience on Twitter.

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See also:

  • Using Social Media to Predict Disaster Resilience [link]
  • Social Media = Social Capital = Disaster Resilience? [link]
  • Does Social Capital Drive Disaster Resilience? [link]
  • Digital Social Capital Matters for Resilience & Response [link]

Using Social Media to Anticipate Human Mobility and Resilience During Disasters

The analysis of cell phone data can already be used to predict mobility patterns after major natural disasters. Now, a new peer-reviewed scientific study suggests that travel patterns may also be predictable using tweets generated following large disasters. In “Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy,” co-authors Qi Wang and John Taylor analyze some 700,000 geo-tagged tweets posted by ~53,000 individuals as they moved around over the course of 12 days. Results of the analysis confirm that “Sandy did impact the mobility patterns of individuals in New York City,” but this “perturbation was surprisingly brief and the mobility patterns encouragingly resilient. This resilience occurred even in the large-scale absence of mobility infrastructure.”

Twitter Mobility

In sum, this new study suggests that “Human mobility appears to possess an inherent resilience—even in perturbed states—such that movement deviations, in aggregate, follow predictable patterns in hurricanes. Therefore, it may be possible to use human mobility data collected in steady states to predict perturbation states during extreme events and, as a result, develop strategies to improve evacuation effectiveness & speed critical disaster response to minimize loss of life and human suffering.”

Authors Wang and Taylor are now turning their attention to “10 other storms and typhoons that they’ve collected data on.” They hope to further demonstrate that quantifying mobility patterns before and after disasters will eventually help cities “predict mobility in the face of a future disaster, and thereby protect and serve residents better.” They also want to “understand where the ‘upper limit’ of resilience lies. ‘After Haiyan,’—the deadliest-ever Philippine Typhoon that struck last November—’there was a total breakdown in mobility patterns,’ says Taylor.”

Of course, Twitter data comes with well-known limitations such as demographic bias, for example. This explains why said data must be interpreted carefully and why the results simply augment rather than replace the analysis of traditional data sources used for damage after needs assessments after disasters.

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See also:

  • Social Media & Emergency Management: Supply and Demand [link]
  • Using AIDR to Automatically Classify Disaster Tweets [link]
  • Visualization of Photos Posted to Instagram During Sandy [link]
  • Using Twitter to Map Blackouts During Hurricane Sandy [link]
  • Analyzing Foursquare Check-Ins During Hurricane Sandy [link]

Digital Jedis: There Has Been An Awakening…

Crowdsourcing and Humanitarian Action: Analysis of the Literature

Raphael Hörler from Zurich’s ETH University has just completed his thesis on the role of crowdsourcing in humanitarian action. His valuable research offers one of the most up-to-date and comprehensive reviews of the principal players and humanitarian technologies in action today. In short, I highly recommend this important resource. Raphael’s full thesis is available here (PDF).

Crowdsourcing Yolanda Response

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