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Information system to assist survivors of disasters      Emergency information system designed to coordinate information f...
Figure 1. Information workflow       •    RSS: feeds can be checked periodically and new           the most salient ones i...
Figure 2. Sending information to citizenspeople in a desperate situation end up travelling to a distant           A comple...
Figure 3. RIFF Architecture
extracted.                                                 team managed to process the information, select relevant       ...
Figure 4. Haiti deployment ecosystem of applications around the shortcode and EIS [4]
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Information System to Assist Survivors of Disasters


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Information System to Assist Survivors of Disasters

  1. 1. Information system to assist survivors of disasters Emergency information system designed to coordinate information flow between the population and aid agencies during disasters Nicolas di Tada Timothy Large InSTEDD Thomson Reuters Foundation Palo Alto, USA London, UK timothy.large@thomsonreuters.comAbstract— This paper describes a free and open source • Reach out to affected population with useful andinformation system designed to be deployed in emergencies actionable information in a timely manner.caused by sudden onset natural disasters. The aim is tostreamline the communication flow and collaboration between III. WORKFLOWmedia, aid workers and government agencies with the affectedpopulation, to help the latter get verified, accurate and The overall goal of the designed flow is to streamline theactionable information that will enable them to make decisions creation and maximize the availability of relevant and credibleand recover from the disaster. information to communities. This implies the creation and distribution of such information. The flow improves whenThe EIS system also provides means for affected population and people have not only direct access to information, but thefield workers to channel vital data back up into aid response. benefit also of credible intermediaries to help discover, gather,This tool is part of a free information service run by Thomson compare, contextualize, and share information. [2]Reuters Foundation to help survivors of natural disasters. It will The flow (“Fig. 1”) can be divided in 4 stages:serve the affected populations, local media and relief respondersby providing fast, practical and verified information in local 1. Collection of raw reports from the field.languages through the best means available. 2. Filtering, processing and identification of important Keywords-component; Information, disaster, response, information.communication, collaboration, media, aid. 3. Editorial process including verifying the accuracy of I. INTRODUCTION information, editing and translating the information into local languages. Underlying EIS is the assumption that people caught up indisasters are not helpless victims and that life saving, 4. Inform relevant stakeholders.actionable information is as important as blankets andtarpaulin. As first responders, they need reliable information A. Subscription and Collectionto make decisions and minimize the impact. Citizens can report their location by sending an SMS to the system with the name of the village they are. That simple ‘Information is a vital form of aid in itself […] Disaster- action registers them in the system to receive alerts targeted toaffected people need information as much as water, food, that village.medicine or shelter. Information can save lives, livelihoodsand resources.’ [1] Every citizen, either registered or not, can report information to the system through SMS. II. OBJECTIVES The system allows submission of raw reports through In line with those assumptions, the design objectives have several channels:been to: • SMS: through mobile aggregators (like Clickatell) • Collect reports originated from the very first layer of or plugged-in phones. People can send information to affected population - survivors; combining that with a specific number, which then stores the message in information received from the field including aid the system. agencies, local media and government. • Twitter: both streams from particular users or • Provide fast and reliable means to filter, search and certain hash-tags can be imported. detect important information in the pool of reports. • Streamline the flow of information inside a • Email: any number of email addresses can be checked by the system and directed to specific distributed editorial team including local translators. collection baskets or inboxes
  2. 2. Figure 1. Information workflow • RSS: feeds can be checked periodically and new the most salient ones in these kinds of scenarios. These tools articles will appear in the system. include search, tagging and automatic extraction of the location the text refers to. Other features that can be added to • Web: any user with permissions can post customize the experience and workflow include flagging information using the web interface. documents, hiding them, commenting and relating them. The 1) Bounded and Unbounded Crowd-sourcing objective of these features is to aid in the process of Through the use of a feature we called "Working groups" collaboratively selecting useful information to initiate theand in combination with the "Baskets", both bounded and editing workflow.unbounded crowd-sourcing processes can coexist in the C. Editingstream. A module called “Baskets” allows the configuration of a Identified users can be assigned to "Working Groups" and custom workflow tailored to the specific team and situation.the reports coming from those groups, can be configured to go The module works based on the idea of baskets. Each basketto specific baskets. Therefore, some baskets can be monitored is a collection of pieces of information (items), that acts bothmore often or by different people, depending on the working as inbox and outbox. Each user in the system is givengroups (bounded crowd) putting reports there. An unbounded permissions to read, write, move in or move out items frombasket could be even configured to be self-filtered by the one or more baskets.same unbounded crowd and items with 10 or more peoplemarking them as "alert" or a specific tag could then be pulled Typically, a user would monitor one or more baskets basedby another basket, which is monitored by some agency. on his role. As new items appear, he will decide what to do, act on the item, flag it as urgent, write a comment, create a Using this combination of features a group of users can new alert or translate it to another language. He would thencollaborate around a pool or flow of information sifting useful put the new item or the edited one in another basket forinformation, tagging (or correcting tags suggested by the someone else to do his part of the job.system), classifying as urgent or alerts, adding geographicinformation (or correcting the one suggested by the system) D. Informingand several other types of metadata that modules provide. Once an alert is ready to be sent out to relevant recipients, the system allows the user to target affected population byB. Selection location through a map with references of clusters of citizens. Through a number of different tools, users monitoring the The user sees a map with the different groups of citizens andpool of raw reports can filter important information. The goal the number of citizens in each group. “Fig. 2”in this stage is to try to deal with as many situation awareness“demons” [3] as possible, being data overload and stressors The objective of targeting by location is not only to keep the information relevant to everyone, but also to avoid that
  3. 3. Figure 2. Sending information to citizenspeople in a desperate situation end up travelling to a distant A complete picture of the platform architecture andlocation just because they received a message saying there is interactions can be seen in Figure or blankets there. The choice of creating a new tool was based on the The alert can be sent through SMS and Email, and can following observations:also be addressed to specific working groups, like aidworkers, local media or government agencies. 8. Existing free open source information aggregators were based on more generic solutions like content IV. TECHNOLOGY management systems. This creates the problem of a platform too generic and abstract to provide a productive The EIS system was built on top of RIFF (, an InSTEDD platform tool developed as and friendly environment to develop extensions. Riff isa general collaboration environment for content creation, collaboration tool based around information aggregationsocial metadata annotation, and automated analysis with and provides specific extension points that allow thepotential applicability in a wide range of areas. developer to focus only in the intended task or feature. RIFF is a modular and extensible free open source 9. Machine learning classifiers are usually stand-alone ad-platform built in C#. The platform tool was developed during hoc applications or libraries, without a context integrated2008 and 2009 as an effort to provide an environment that with information aggregation and collective analytics.could collect heterogeneous information sources and leverage 10. Many powerful analytic environments are eitherthe power of human expert collaboration with machinelearning and visualization aids. proprietary or commercial. RIFF is extensible through several different means: EIS was designed and implemented as a set of extensions to RIFF that allow receiving SMS messages, creating custom5. Developers can add new types of information sources, workflows for information and targeting outgoing SMS even custom or proprietary messages by location and working groups.6. Modules can be developed to add new filters, provide The choice of SMS as a communication channel was based additional functionality around classifying or tagging on: items, extend the model of each item by adding new fields or properties, create new visualizations and • Provides a two-way channel: citizens can report as automatically extract information during the import well as receive information. phase. Most of the basic functionality is developed • Allows for information to be targeted to citizens through modules. based on their reported location and needs, while still allowing for bulk sending.7. Plugging the output of RIFF to another system. The tool allows the extraction of tailored and filtered RSS feeds, • Allows for semi-structured reports to be parsed: email subscriptions or push selected data to custom locations can be extracted, keywords can be identified endpoints. and other entities like names or organizations can be
  4. 4. Figure 3. RIFF Architecture
  5. 5. extracted. team managed to process the information, select relevant topics and going through a quick but reliable loop with localA. Server Deployment translators could provide alerts with verified data. EIS is running right now on an Amazon EC2 instance,providing a very easy way for 3rd parties to quickly deploy A short summary of the pilot can be seen at: http://and manage their own instances. V. RESULTS VI. CONCLUSION As of the moment of presenting this paper, the system was We believe that we have built a tool that can handledeployed with much success in Haiti: information collection, flow and reach out in a wide range of deployment scenarios in disaster situations, providing the • The population response was very high, getting support for channeling information up and down as needed more than 5.000 subscribers in less than 10 days. among a heterogeneous ecosystem of stakeholders. The Currently above 15.000. system will serve as the basis for further learning, • More than 1.000 incoming SMS per day from the development and work on the subject. survivors, including emergencies, needs or VII. ACKNOWLEDGMENTS information requests to a total of more than 50.000 We would like to thank to all the people that worked in the messages processed inside the system. inception, design, development and testing of the system: • Several agencies, under the UN umbrella, are both Monique Villa, Timothy Large, Astrid Zweynert, Joanne receiving targeted information from citizens, and Tomkinson, Thin Lei Win (Thomson Reuters Foundation); sending out messages regarding where to find food, Eric Rasmussen, Robert Kirkpatrick, Eduardo Jezierski, Luke register missing people, get shelter and health Beckman (InSTEDD); Juan Wajnerman, Brian Cardiff, Martín measures. Verzilli, Ary Borenszweig, Andres Taraciuk, Mariana Galvan, Martin Scebba (Manas Technology Solutions). • More than 20 users from different agencies and groups. The help and feedback of the Palang Merah Indonesia (Indonesian Red Cross) was essential to conduct the pilot and Within hours of the earthquake, most of Haiti’s cell phone improve the system.towers were still operational and text messages were gettingthough in most of the country but Port-Au-Prince. After 2 or A special thank to Willie Smits who hosted us and helped3 days of work, the 2 main telephone companies could get us with the logistics in North Sulawesi.most of the capital antennas back to work. VIII. REFERENCES The EIS team was deployed less than 48hs after theearthquake and, in partnership with other organizations like 1. International Federation of Red Cross and Red CrescentUshahidi and FronlineSMS:Medic, quickly began (2005) World Disasters Report 2005: Focus onnegotiations with the telephone companies to establish a information in disasters, Kumarian Press, http://shortcode for citizens to text-in and for the system to be able send messages out. A diagram of the final ecosystem 2. The Knight Comission (2009) Informing Communities:architecture of applications and organizations interacting Sustaining Democracy in the Digital Age, http://around the shortcode and EIS can be seen in Figure 4. at: 3. Mica R. Endsley (2003) Designing for Situation 1564/2010/00/24-120746-1.htm Awareness: An approach to user-centered design, CRC Before the Haiti deployment, a pilot of the system was 4. Ushahidi: Project 4636 revisited, http://conducted in Tomohon, North Sulawesi Indonesia, in with the Local Red Cross and the local Search and revisited-the-updated-info-graphic/Rescue Team, has proved the validity of our assumptions.Even if the incoming stream of reports from the fieldcontained (by design) a low signal to noise ratio, the editorial
  6. 6. Figure 4. Haiti deployment ecosystem of applications around the shortcode and EIS [4]