The past 20 hours have been sad, exhausting and inspiring. Sad for obvious reasons. Exhausting because many of us have been working straight through with no sleep. But inspiring because of the incredible community of Crisis Mappers.

Here’s what been happening in the community:

• Ushahidi launched a Haiti deployment
• Mikel Maron at OpenStreetMap launched this Wiki
• Andrew Turner at GeoCommons is updating CrisisCommons
• Our friends at Sahana have set up a Development Team
• Sahana has also set up a Wiki here
• Our InSTEDD friends set up a GeoChat instance
• Our friends at MapAction have deployed a team
• Einar Bjorgo at UNOSAT is keeping us posted on imagery

InSTEDD is also working on getting +46 numbers for GeoChat, the Emergency Information Service (EIS) and Ushahidi. InSTEDD is also in Santo Domingo deploying EIS. Sahana is exploring the possibility of integrating GeoChat based on some work they did at Camp Roberts a few months ago. InSTEDD is also looking to start testing a Sahana/Mesh4X sync. There are several dozen other ongoing efforts but hard to keep track.

http://www.google.com/relief/haitiearthquake/index.html
http://haiti.ushahidi.com/help
http://crisiscommons.org/wiki/index.php?title=Haiti/2010_Earthquake#Data

I first heard about the major earthquake around 7:30pm (Boston time) last night and immediately called David Kobia to get an Ushahidi deployment out. I have five close friends from The Fletcher School who have been in Haiti over the past two weeks and it wasn’t until midnight that I finally got word that they were alive.

What happened between 7:30pmm and midnight was inspiring. We went live with a basic deployment within half an hour. I called Chris Blow and got in touch with Brian Herbert. They both worked with David to continue the customization.

I then reached out to our colleagues with the International Network of Crisis Mappers (CM*Net), and their response has been superb. We’ve had over 50 emails back and forth, sharing data, maps, local contact info with regular updates.

Our colleagues from UN OCHA/Colombia were invaluable in helping us identify the appropriate indicators as were many others on CM*Net. OCHA had just carried out an earthquake simulation exercise using their own customized version of Ushahidi so were fully ready to go. They worked directly on the admin side to help us push forward. So many thanks to Jeffrey Villaveces and Luis Aguilar.

At around 3am, our Nairobi team took over with customization and we had an 8am all team meeting to assess the current deployment and evolving situation in Haiti. We now have an international number up for SMS and are working with our colleagues at InSTEDD and at CM*Net to set up a local number as well.

On a personal note, it’s just been remarkable to see so many of the organizations who participated in the International Conference on Crisis Mapping (ICCM) collaborate so pro-actively together. It was also somewhat surreal when someone from Haiti signed up to CM*Net and in their bio wrote:

“I’m in Baudin, Haiti right now ( 18.307606° -72.709935°) so won’t have cell phone service until it comes back but can be reached then at 509-3-823-6859 or michael.ritter2@gmail.com.”

I quickly added Michael to the CrisisMappers Google Group and he has been providing is some valuable information since.

Reports

Note, we’re getting a fair number of Twitter messages, but not all of them are useful reports at this time. Mobile networks are down, so the SMS reports are almost nothing. Web-based reports that are coming in seem to be of good quality, as are the few email reports we’re getting.

Special Thanks

We’re getting slammed by a bunch of traffic on the site. A big thanks goes out to Jonathan and his team at Cartika Hosting who have helped us stay up all along, have migrated servers for us and spent hours on the phone. Thanks guys!

Organizations helping to get the word out about the Haiti site:

Wall Street Journal
Google Relief
Clinton Foundation
UNDP
Cartika forums
Washington Post
Global Voices
ReliefWeb
The Guardian
New York Times Lede blog

After watching a video debate (which started off talking about cyber war, then ventured into broader discussions around the use and viability of social media during a political emergency), between Ethan Zuckerman and Evgeny Morozov, it made me think of the current book I’m reading (Wars, Guns & Votes by Paul Collier). In it Collier talks about the inverse relationship between democracy in the bottom billion and democracy in the developed world. Basically, democracy is counterproductive in most countries where people live on less than $7/day.

GDP and Government Media Censorship

This raise a question to me. Has anyone done qualitative research following the same lines of thinking within the blogging and social media space? Where they contrast the social media use, and results of that use, relative to the GDP of the country where the blogging is being done.

In particular, of course, this relates to when blogging and social media is used during an emergency where politics are at play.

The reason I ask is because of the comparisons that are brought up by Ethan and Evgeny, with Honduras, Iran, Xinjiang (China), Russian and South Ossetia parading through the conversation. It’s an interesting contrast listening to the takeaways by each of them, in relation to the outcomes (some of which are still unfolding). I wound up Wolfram Alpha to take a quick look at the GDP of these countries, knowing well and good that more sound research would have to be done to do this properly.

What other factors would seem to play an overly effective part in this space? The first ones that jumps out at me are:

• GDP
• Technology penetration
• Democracy rating
• Openness of society
• Government censorship (media/internet/mobile)

I’m guessing that GDP alone isn’t enough to make an educated prediction on the impact of the use of social media in politically charged societies. It probably has as much to do with the proclivity of government media censorship within a country as well. What is the past history of the government to censor media, and which channels do they block?

If you look at China (16), Iran (16), Russia (12), Georgia (8) and Honduras (6) – as compared in the CIRI Human Rights Database of Government Media Censorship 2000-2007, this is what you find. It seems that there might be some correlation in the numbers, but deeper research would have to be done to truly determine if that is true or not.

Searching for information

I’ve just begun exploring this question, so if someone has done any work in studying this area, please let me know. If not, I’d be interested in seeing some basic research into any of the sub-categories mentioned.

I’m quite interested in finding out what determines an effective (or failed) social media campaign during a period of political unrest.

It was that crisis that started two members of the Ushahidi dev community (Chris Blow and Kaushal Jhalla) thinking about what needs to be done when you have massive amounts of information flying around. We’re at that point where the barriers for any ordinary person sharing valuable tactical and strategic information openly is at hand. How do you ferret the good data from the bad?

When the noise is overwhelming the signal, what do you do?

Thus began project “Swift River” at Ushahidi, which for 3 months now has been thought through, wireframed, re-thought and prototyped. Chris and Kaushal started asking, what can we do that most significantly effects quality of information in the first 3 hours of a crisis? And then answered, what if we created a swift river of information that gets quickly edited? Events like US Airways Flight 1549 and the inauguration gave us real-time live events that also had massive amounts of data to test things out on.

And, after all that, we’re not done, but we do have some solid ideas on what needs to be done. We think of it as using a crowd to filter, or edit, the already crowdsourced information coming through tools like Ushahidi, Twitter, Flickr and YouTube. To us, Swift River is “Crowdsourcing the Filter”.

How does it work? (non-tech version)

Since we don’t believe there will ever be one tool that everyone uses for gathering information on global crisis, we see a future where a tool like Swift River aggregates data from tools such as the aforementioned Twitter, Ushahidi, Flickr, YouTube, local mobile and web social networks. At this point what you have is a whole lot of noise and very little signal as to what the value is of the data you’re seeing.

Anyone who has access to a computer (and possibly just a mobile phone in the future), can then go and rate information as it comes in. This is classic “crowdsourcing”, where the more people you have weighing in on any specific data point raises the probability of the finding the right answer. The information with greater veracity is highlighted and bubbles to the top, weighted also by proximity, severity and category of the incident.

At this point we have successfully filtered a large amount of data. Something difficult to do with a small team of experts, which can be accomplished by a large number of non-experts and experts combined.

What Next?

So far we have some comps and David created a rough prototype of the engine driving it for the US inauguration. If this type of tool interests you, and you’d like to help, then do let us know. Here’s a glimpse at some of the idea flows that spur on our conversation at Ushahidi. This was created by Chris Blow, using the assumption that the user of this tool and protocol was a Twitter user:

The tool is really quite simple, and can be made better by clustering “like” incidents and reports, rating of the users on proximity, history and expertise and by developing a general protocol so that any other developer can expand on it as well.

Many others are talking about the citizen reporting, and it’s value and challenges. Mainstream media is concerned, as are many experts and government officials, about how empowered ordinary people are in gathering, providing and amplifying information in ways that just weren’t possible before.

There is no stopping this change in information dynamics, there is only harnessing it in ways that add more value to the good guys than the bad (when you can figure out which is which). At the very least, we need to figure out how greater information flow and transparency can be leveraged to help in emergencies, especially when there are negative forces at work who have equal accessibility to the same tools.

Aggregation vs early warning

During, or after, a conflict there are a lot of tools available and already being used, especially in technologically advanced countries like India. Technically, it’s fairly easy to aggregate Twitter, Wikipedia, Flickr and YouTube videos. That should be done, and we are creating the superstructure for this to happen easily worldwide. (note: Twitter is useful in India, the US and Canada, but what about all those areas of the world where it was turned off?)

What is more interesting to me, especially about Mumbai and Jos, is the fact that if a tool like Ushahidi was available globally beforehand, then it would have provided a place for people to send in anonymous information and tips before anything happened. After all, even if the local law enforcement isn’t aware of what is happening, someone within the community does. Of course, this begs the question, “how would they know of it?” To which I don’t have any more of a complete answer other than if it was up and live, it would gain traction over time, just as any effective web/mobile service does.

The “right” and “best” tool

The best tool in any given crisis is what ever is available. There isn’t any time to deploy something then, you have to use devices and services that people are already using. Chris Albon noted that there was a lot of information and data flying around during the crisis in Mumbai, and that Ushahidi wasn’t present. Instead, it was a mixture of Wikipedia editing and Google maps that people were using. For a major global city, these two tools makes sense. But what about places like Jos?

This reminds me of a what I wrote about on holistically dealing with disaster scenarios during the hurricanes in the US earlier this year. The value of the current Ushahidi Engine is good for information gathering and visualization, but there is a definite need of a more wiki-like functionality in these tools. Both the hurricanes and these other conflicts have been rapidly collaborated and edited into Wikipedia, so the usefulness of that type of tool is shown. I’m very interested in getting something like this figured out, if we had the resources internally, we’d be doing it already.

What about when the ‘bad’ guys use it?

The other questions were hard, but this ones even harder. As much as mainstream media and experts are up in arms over the way that the terrorists in Mumbai could use information coming in from these new digital channels to monitor their own situation, we have to remember this isn’t new. Groups like this have been able to do this with mainstream TV and radio for years. What’s disturbing is that not even the government can stop it now.

The problem is that it’s no longer one-to-many mass broadcast, it’s now mass-broadcast to mast-broadcast. How do you stop 6 million SMS messages without crippling your own infrastructure and ability to get work done?

I think one answer might be found in figuring out a way to harness information from an even greater number of people. The more data that is collected, the less chance that bad data can have an adverse effect. For instance, if 2 reports come in that widely differ from the reports by 10 other people, then we can assume that they are false. That at least helps us solve for a greater probability of good info being available and can help with the adverse use of it by the “bad guys”.

What it doesn’t do is solve for the problem of the “bad guys” having more information available at their fingertips. Nothing will solve that now. What it does do is mean those opposing them will have equal access to the same information, and possibly even more than is currently available on the “bad guys” movements and operations by tapping into the greater public.

Just more questions…

This all left me with a no final answer, just more questions.

• How does the transparency of a tool help and hinder during hot-flash conflicts?
• Beyond Ushahidi, what are the best tools to use in hot-flashes?
• How does rural, and conflicts with greater geographic distribution than one city, differ in coverage and information?
• What is Ushahidi’s role?

It’s really an interesting device, that is all open source – both hardware and software.

Included in the first prototypes are webcams, radio transmitters and ultra-low-power computers. These components are run with open-source software designed to support the efforts of field workers and partners, and to be locally adapted for ongoing use.

One can imagine devices like this, syncing with InSTEDD’s Mesh4x and even incorporating some of Ushahidi’s visualization tools. It has huge potential for being used when trying to match up and find missing family members – especially children, thus UNICEF’s involvement. The Bee system is intended to help field workers quickly and effectively register children in emergencies.

The Bee means that there is now a mobile hub that can quickly be deployed as nexus points in emergency settings in areas well removed from normal power and connectivity grids. It has multiple ways to use power, including solar, car battery and conventional power.

The Bee is also able to connect to global telecommunications networks using a satellite receiver or a mobile phone, or through its built-in, long-distance WiFi capacity.

“In a natural disaster, government agencies and international organisations are usually relatively comfortable to share information about the situation – but in a conflict, they clam up tighter than my wallet around Christmas. This is because natural disasters have fewer political implications than complex emergencies; while in a natural disaster the worst thing you can say about a government is that they’re negligent, in a conflict situation the government is usually a belligerent. This means that timely / reliable / accurate information is hard to come by in Georgia…”

When people look at situations like Georgia, Kenya, Zimbabwe or Sudan everything becomes a little more fuzzy than in a post-hurricane or tsunami incident. No one wants to say anything publicly because they’re worried about upsetting the wrong people and getting kicked out, shut down or silenced.

It’s no wonder that guys like Paul are frustrated, just a little cooperation would go a long way, yet so little of that happens when it’s needed most – from aid organizations or from the government.