Dr. Jen Ziemke (co-founder of CrisisMappers) welcomes a room packed with a wide variety of professionals and volunteers. CrisisMappers started in 2009 as a network, designed to stay in touch
The group has grown to 5,000 members, organized on a Google Group and Ning network.
For the newbies in the room, what is CrisisMapping?
Jen breaks it down into the data coming in, the visualization of the data, and the response: how does it affect decisions on the ground?
Changing technology is clearly a primary driver of crisis mapping. Mobile technology and the ability to crowdsource shared experiences and visualize it on a map, or elsewhere, has enabled crisis mapping. Beyond mapping, this community quickly becomes a broader group of digital humanitarians, using technology to help communities affected by crisis.
Patrick Meier (the other co-founder of CrisisMappers) hops on stage. He’s currently at the Qatar Foundation Computing Research Institute, where they’re researching how to gather information from social media
In 2009, the field of crisismapping was just beginning to take shape, and it was easy to know every project and get to know all of the people behind the projects, often over drinks. The field has exploded, and matured, and the problems the field faces have grown more difficult.
The community met last year in Geneva to begin tackling some of the challenges. The computer security behind emerging humanitarian technologies was an obvious area of concern. John Crowley spearheaded this effort at the Camp Roberts event. Phoebe Winpope* has taken on issues of data privacy and security, working with professionals in that space.
Wendy Harman and her team at the American Red Cross have launched the Digital Operations Center, driving home the point that social media for disaster response is here to stay.
Andrej Verity has launched the Digital Humanitarians Network to facilitate the space between volunteer technologists and large humanitarian organizations.
Geeks WIthout Bounds and Digital Hacks of Kindness are also driving forward innovation in this space.
Disaster-affected communities are increasingly the source of big data. When Japan was struck by earthquake, tsunami, and nuclear disaster, a TON of data was shared online. Patrick argues that we need hybrid methodologies that combine crowdsourcing and the speed and scalability of advanced machine learning algorithms. We need to use multiple channels to listen to communities.
Verification remains an important challenge for aid organizations looking to make use of social media. Media organizations are actually leading the way in this department. The BBC has had a User Generated Content hub in London since 2007.
Monitoring and Evaluation are also important. Our perception of digital humanitarian technologies is high, but the real evidence supporting them is pretty thin. We need strong, independent evaluations of these technologies’ impact.
CrisisMappers 2013 will be held in Nairobi, Kenya (applause). This will be the fifth annual conference, and Jen and Patrick have decided to step down as organizers, and adopt OpenStreetMap’s model, where members of the network pitch to host and organize the annual conference.
Patrick is also inspired by TEDx, and hopes to see the CrisisMappers brand, logo, and website repurposed to support far more local events in this space.
Ignite talks!
Lin Wells (@STAR_TIDES) gives an overview of the STAR-TIDES network and its 1500 nodes. It is public-private and trans-national. They work post-disaster, post-war, impoverished, and short term and long term (disaster vs. refugees). They work in domestic or foreign situations, whether military is involved, or not. Shelter, water, power, cooking, lighting, sanitation, and ICT technologies.
Lin says technology alone is never enough. Building social networks and developing trust, as well as understanding how policy is adapted in the field, all matter.
TIDES hosts annual technology demos at Fort McMayer. They’re also present at Camp Roberts. The real world events they’ve supported include floods, wildfires, election monitoring, and more.
Jakob Rogstadius (@JakobRogstadius) introduces Crisis Tracker to crowdsource the curation of information like tweets during a crisis. Twitter poses a challenge, in that 140 characters is too short for computers to understand, but the rate of incoming tweets is too voluminous for humans to cope with.
The Crisis Tracker platform helps people sift through the noise and identify the novel information pieces in the stream, reduce the inflow rate, and enable volunteers to act on the actionable content. Similar messages are clustered, junk is filtered out. 30,000 tweets become 2,000 stories, and then 7 unique pieces of information per hour. The system looks at metadata like the timestamp, and then the crowd annotates the information with stories.
Why human involvement?
Humans can process text and images in ways computers cannot. Humans are also adaptable to rapid changes.
The system is up and running for the Syrian civil war. You can drill down into individual stories and see who shared it, links to multimedia content, and similar stories.
Volunteers have appreciated the platform’s ability to aggregate and filter. The system picks up stories and ranks and auto-sorts and filters the top stories. A 6-8 volunteer team can pull out the top items. With 40-60 volunteers, you can have a detailed log of the event at a very local level.
The project is free and open source.
Mona Chalabi (@MonaChalabi) brings us back to the challenges brought up by both slow and sudden-onset challenges. Crisis maps were unable to stop delays in aid distribution in Haiti. Have we reached a plateau in the use of GPS? FedEx uses RFID to track packages. It’s a barcode on steroids. A chip stores coded data, an antenna transfers the signal, and a computer accepts it for processing. Many subway cards use this technology.
In Haiti, hundreds of containers arrived each day, and those that were recorded were tracked using manual processes like Excel spreadsheets, leaving plenty of room for error. RFID would be much more efficient at managing the supply chain. The chips can be re-used.
The private sector has used RFIDs to great effect. The effective distribution of resources in a crisis can be the difference between people being fed and people being tear-gassed by UN troops afraid of a large crowd. RFID also combats information asymmetry in the space because the information is automated rather than input by one group and verified by another.
Simple supply chain logistics remain a major challenge for aid agencies and governments in crisis.
The effective distribution of resources in a crisis can be the difference between people being fed and people being tear-gassed by UN troops afraid of a large crowd.
RFID also combats information asymmetry in the space because anyone can use the information.
Simple supply chain logistics remain a major challenge for governments in crisis, and make it more difficult for corrupt officials to interfere with the chain of supplies.
Nate Smith (@nas_smith) is with Development Seed and Mapbox. There are many factors in communicating the many complicated factors that go into a crisis situation.
Context is important, like the conditions in the Horn of Africa prior to the droughts.
The Sahel Food Crisis project was much more than mapping, Nate says. Getting access to the raw data and communicating it in an appropriate way was part of the challenge.
Workflow is a problem. How we access data, and do things with it, can slow things down. Fews Net maintains their data in PDFs, which slows down developers looking to do anything with it.
What are the right colors and pieces of information in a map to express information?
We must design for shareability. Tools must be equipped for people to use them. If you’re publishing a lot of maps, your website should have the map endpoint on your site, so others can take and use it.
MapBox is also looking at building large data browsers that will support applications. The Sahel Food Crisis site is open for collaboration on Github.
Richard Stronkman (@rstronkman) is founder of Twitcident, another service to listen to the voice of the community during incidents. So much information is produced, with 400 million tweets per day. It’s a lot of noise, but when there’s a crisis, the information rates go up.
Early warning to identify increased risks and potential incidents.
And when incidents occur, they do crisis management.
In the Netherlands, they’ve worked with police forces, event security company, and the Dutch railway operator. On Queen’s Day, the Utrecht police force asked them to produce a map of incidents in a real-time dashboard. The team was able to identify threats towards the Royal family, leading to police visits.
At summer carnaval, the team worked to intervene against false rumor propagation. They found rumors at an early stage, and helped the police publicly disprove rumors early in the process before the rumors took off.
The team was able to identify a lack of drinking water at a large scale water fight early in the event, and help organizers react.
The group publishes their findings as academic research and in the technical press.
Shadrock Roberts (@Shadrocker) works at USAID’s Geo Center. The USAID Development Credit Authority uses credit guarantees to encourage local banks to lend to underserved communities. They wanted to map their work to see how they could do it better. They had a beautiful dataset of 100,000 records over the program’s 12-year history, but the location information was all over the place.
The Geo Center team cleaned up the dataset with a hybrid human-computer method. An automatic process parsed the easy fixes, but they raised a lot of eyebrows when they suggested crowdsourcing the remainder. They built an application on Data.gov. The technical infrastructure was a hurdle, but so were the legal policies restraining how the agency could use the data. They cozied up to the lawyers and received help from VTCs to clarify what volunteers would do with the data.
Involving volunteers went beyond crowdsourced tasks. Volunteers began a much broader discussion about development and the Development Credit Authority. Social media mentions of the organization went up significantly. 300 volunteers took on 10,000 records in 16 hours with 85% accuracy.
The goal wasn’t just a map, but to make the data open for others. You can find it by Googling “USAID Crowdsourcing Transparency” or tweeting at @USAID_credit.
Jerri Husch is here to talk Action Intelligence. How do we make sense of the massive amounts of data. Like electrical outlets, we have competing standards and cultural influences in different places. Jerri argues that we need an adaptable standard. If we look at societies from afar, we might make the mistake of assuming everything’s objective. But the world doesn’t work that way. A cricket is a pest in one place, and a delicacy in another.
Action Intelligence allows us to manage and analyze multiple dimensions and link data. We need to know who’s doing what, where, when. We need the data immediately in a crisis, and we need it around for the long-term as legacy data.
They can link actors to one another, or link actors to actions.
The process goes like this:
1. Collect data, often with university teams, in standardized ways
2. Classify and code that data, by place and time, at micro or macro levels
3. Visualize the data. They use free, open source tools, which allows for an adaptable standard that works anywhere in the world.
Andrew Turner (@ajturner), formerly of GeoIQ, has joined ESRI as CTO of their Research & Development Center.
“Big Data” means different things to different people, but we know it’s huge. In a crisis, with very short, life-threatening situations, data can help. In Haiti, crowdsourced information was really good, but still needed someone on the ground to act on the information.
GIS analysis lets us count and look at geospatial analysis of information. We need to evolve and build learning algorithms, because our current techniques are pretty easily fooled. @Racerboy8 provided useful data from his house during the Colorado wildfires, but his house wasn’t actually in danger. He was just being helpful.
In the NYC Marathon last year, FEMA looked at sensors throughout the crowd to visualize the crowd’s movement over time and space.
We can model situations before they occur, and detect communities in advance of a crisis.
Anahi Ayala (@anahi_ayala) works for Internews, which supports local media across the globe to empower communities. Anahi’s at the Center for Innovation and Learning, looking at how to incorporate new technologies.
Merging crowdsourced data with official information has proven difficult because of the difficult of verification. In the Ukrainian elections, they’re collecting information not only from social media, but also trained electoral monitors and journalists. Users can see verified reports vs. untrusted sources on a map.
The team dissects all of the information that comes in in an attempt to verify. They look at the context, the content, and the source of the information. There are digital traces everywhere online. Who are you already friends with, followed by, directly engaging with?
The content itself can be verified. We can crowdsource, triangulate, follow up with the source, and look at the weather in the video you submitted.
Every event occurs in a context in a country. Reports can be verified based on knowledge of the existing situation in a place and time.
Everyone’s adopting their own verification methods. Yes, falsification of information is always possible. But so is verification. Machine learning makes verification faster and cheaper for organizations. The question today is not whether or not you can verify information, but how to make it of high enough quality and timely enough to be acted upon.
Kuo-Yu Slayer Chuang (@darkensiva) goes by Slayer. He brings us back to the Titanic, which sank in a time when SOS technology wasn’t standardized. Open GeoSMS is a standard that combines SMS and location. Smartphones can embed all sorts of geo information in messages. They are designing a user-centric application to make collaboration easier.
Lars Peter Nissen (@ACAPSproject)
How do we make sure the data we collect actually becomes useful for decisionmakers?
Mistakes happen in large-scale, multi-agency responses. Potential impact is stymied.
In Haiti, we only used 1/3 of the data gathered. That’s a waste of the effort exerted collecting that data.
Disasters are never what we expect. Decisions are made when they have to be made, not at some ideal point in time. And we’ll always have massive information gaps, with plenty of known unknowns and unknown unknowns.
Three principles:
1. Know what you need to know. It sounds obvious, but do you?
2. Make sense, not data. Don’t collect data if you don’t know what you’ll use it for.
3. Don’t be precisely right, be approximately right.
With Internews, they designed the GEO, Global Emergency Overview. A snapshot gives you a quick overview of what’s happening, globally. Short summaries provide a basic understanding of specific crises. Then, you can drill down into 20-page analyses that help you discriminate between different types of needs in the fields.
Sara Farmer (@bodaceacat) is a core team member at Standby Task Force. It’s 2 years old with 1,000 volunteers. They’re generally known for turning social media feeds into maps. But they’re not just about information; they’re also about knowledge and analysis. They support HXL and other standards.
Their Disaster Needs Analysis (DNA) reports provide information about locales before disasters occur. Teams investigated and mapped available data for countries. They created baseline indicator sets, and set up a workflow to collect, store, and distribute the data. A fleet of scrapers converted online data into machine-readable tables. The data was cleaned into standard formats for country names, dates, and geo references. Gaps are filled in with estimates and proxies. Expert (Hunchworks) also help fill in the data.
Phil Harris (@geofeedia) sees every demographic using social media more and more. It’s not just Facebook and Twitter – there are image-rich services that didn’t exist two years ago. Smartphones drive more user generated content.
They set geofences on London and monitored the Olympics, aggregating 175,000 posts from YouTube, Twitter, Flickr, Picasa, and Instagram. Instagram’s a surprisingly large source of posts (36%). Only 31% of the posts contain keywords like London or Olympics. The majority of these pots wouldn’t have been tracked by traditional keyword search methods. Geofeedia sells a service to monitor social media.
Colleen McCue (@geoeye) works in geospatial predictive analytics. Again, we can learn a lot from private sector marketers. Product positioning in the supermarket is critical. Location also matters when you’re talking about bad actors in the humanitarian world. The Lord’s Resistance Army has struck over the borders of several African nations. We can target them based on past behavior. And we can segment the population by crime types, like marketers. Looting, abduction, incidental homicides, and murders produce different geospatial patterns. Individual factors can influence violent crimes. Roads and porters are critical to a successful abduction. IDP camps and other population clusters are attractive to the LRA, just as banks are attractive to thieves.
“Distance from murders” turns out to be a major factor in instances of isolated murders, suggesting a key behavioral difference from incidental homicides that occur over the course of another crime. The group is compiling signature profiles of different behaviors, and using advanced analytics to produce actionable recommendations prior to events occurring.
Kalev Leetaru brings us back to 38,000 years ago, where we find the first written records. 550 years ago, we get the printing press. Today, we’re producing incredible amounts of information and written records as a species.
The history of conflict can teach us about the present. We can visualize NGO reports and the global media tone towards a nation like Egypt or a leader like Mubarak to see when they’ve lost global credibility. We can track geographic affinity for a leader like Osama bin Laden. We can map conflicts within a nation by various factors.
Dave Warner is “dangerously over-educated and works in a memo-free environment.” He wants to make smart people smarter and explode the dots on the map into more complicated pins that contain significantly more information. His maps look much more like something out of a strategy video game than GIS software.
Dave mapped an audience by their WIkipedia entries, and academics by geography across the country.