ICCM 2013 Ignite Session 2

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Slides from the 2013 International Conference of Crisis Mappers in Nairobi, Kenya. Learn more at crisismappers.net

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  • Earth engine was built for science, to do global analysis to ask new questions but it has a use one step further, and use apply science apply the science of disasters at this scale.(watch up tones) (ill give you an example of a collaborative research project)-but we could leverage this technology together with science, what does that mean for crisis mapping. I’m gonna show you how we have leveraged google earth engine to answer this question,
  • One solution- use science to refine (PRACTICE SAYING ONE SENTENCE PER SLIDE). This takes years of developing and days to run the model
  • Who would need to do this on the fly? Crisis mappers- mention who this technology exists todayGoogle earth engine can take terabytes of information and can analyzed scientific methods and algorithms on a speed and scale that’s never been done before.(im using this platform in my research).
  • We pull from both social and natural science to write that algortihm. I study hydrology, and bessie, who here with me today in the front row studies social science.
  • When we run this algorithm it gives us a real time risk surface anywhere in the US, pinpointing the location and number of people most affected.
  • Make the transition to next section
  • Whatif
  • Text or phone (making the science faster and to more people) (website, or an text message), or by a more prepared red cross.When scientists, programmers, and disaster reliefe experts come together…
  • Yale and thanks this is a proof concept that we’ve built but in order to achieve its full potential we came to nairobi to find looking for collaborators at this conference- disaster relief managers, better programers, to help us test the accuracy, improving the science and find better applications for this.
  • IFRC one
  • IFRC two
  • Or process later
  • The coolest areas of AI don’t exist in reality.
  • Some of you know why someone would call Katy Perry a Prism.
  • Some of you know why someone would call Katy Perry a Prism.
  • Some of you know why someone would call Katy Perry a Prism.
  • The ignite talks before me… Wow…. Their slides , Amazing….. Now you have me!!!!! A bit of background to why this presentation is not “all singing and dancing as the professional ones before”
  • Crazy never again!!!!
  • Volunteers clicking from Mali!
  • IF YOU CAN LIKE A PIC ON FACEBOOKYOU TOO CAN BE DIGITAL HUMANITARIAN VOLUNTEERDEMOCRATIZE DIGITAL ENGAGEMENT IN SUPPORT OF DISASTER RESPONSE----- Meeting Notes (4/2/13 16:10) -----STOP AND GOPAUSEPRONOUNCESYNC GESTURESARMS OPEN WIDEPALM UP, PALM DOWNHAND CHESTINDEX FINGERSQUINT
  • IF YOU CAN LIKE A PIC ON FACEBOOKYOU TOO CAN BE DIGITAL HUMANITARIAN VOLUNTEERDEMOCRATIZE DIGITAL ENGAGEMENT IN SUPPORT OF DISASTER RESPONSE----- Meeting Notes (4/2/13 16:10) -----STOP AND GOPAUSEPRONOUNCESYNC GESTURESARMS OPEN WIDEPALM UP, PALM DOWNHAND CHESTINDEX FINGERSQUINT
  • TEXT = TWITTER, SMS, FACEBOOK UPDATES
  • PAKISTAN
  • MORE SMS IN REGION
  • IF YOU CAN LIKE A PIC ON FACEBOOKYOU TOO CAN BE DIGITAL HUMANITARIAN VOLUNTEERDEMOCRATIZE DIGITAL ENGAGEMENT IN SUPPORT OF DISASTER RESPONSE----- Meeting Notes (4/2/13 16:10) -----STOP AND GOPAUSEPRONOUNCESYNC GESTURESARMS OPEN WIDEPALM UP, PALM DOWNHAND CHESTINDEX FINGERSQUINT
  • GOOD TO MENTION THAT WE HAVE GEO CLICKERS AS WELL COMING ONLINE THAT WILL INTEGRATE DIRECTLY WITH STORY MAP. This would have helped with backlog of geo locating
  • Yolanda Output
  • In the background you will see slides of the first part of SBTF’s activation with DHN members. SBTF led this phase.The slides tell the story which I or Patrick are more than happy to elaborate on during the next few days I want to talk about he most important part of the activation.NOW TO BE SERIOUS!VOLUNTEERS ARE NOT FREE.THEY TAKE TIME,SUPPORT, TRAININGYOU DO NOT WANT TO ABUSE THEM BY JUST MAKING A PICTURE FOR THE HELL OF ITSHOW THEM HOW THEY ARE CONTRIBUTING AND WHAT THEY ARE CONTRIBUTING TOWARDS.DURING THE LAST WEEK OR SO MANY OF US HERE HAVE BEEN WORKING RATHER HARD. OUR VOLUNTEERS HAVE BEEN WORKING JUST AS MUCH IF NOT MORETHIS WAS ONE REASON THAT IS NOT SPOKEN ABOUT WHY MICROMAPPERS WAS CREATED“”””””””””””MICROMAPPING---------------- MAKING CRISIS MAPPING EASIER!””””””””””””””””””””””
  • ICCM 2013 Ignite Session 2

    1. 1. Ignite Session 2 @CrisisMappers #ICCM
    2. 2. Beth Tellman @pazjusticiavida
    3. 3. The Opportunity: The Challenge: Making decisions from a blob Red Cross: Where are shelters? What are road conditions? Farmer Brown: Should I move my chickens to higher ground? NOAA flood risk zone on Google Crisis Maps, For South Carolina March 30th, 11:30pm
    4. 4. The Opportunity: The Potential: Science allows us to answer these questions Hydrologist from University of South Carolina: We should at least identify the floodplain Social Scientists from Charleston College: Census data indicates who is vulnerable! NOAA flood risk zone on Google Crisis Maps, For South Carolina March 30th, 11:30pm
    5. 5. High Medium Low
    6. 6. A Solution: Refining risk prediction to make it relevant on Farmer Brown: “I will not waste money moving my chickens. Phew!” time
    7. 7. The Science: Socio-ecological Approach to Vulnerability
    8. 8. Biophysical Indicators of Vulnerability 1. Low Elevation 2. Low Slope 3. High % Impervious Surface 4. Large Watershed Size Where is the flood?
    9. 9. Social Indicators of Vulnerability 1. High % of young children 2. High % of elderly 3. Poverty 4. High population density 5. Low community cohesion Dr. Susan Cutter, Social Vulnerability Index
    10. 10. EE API Code to Refine the Flood Risk Our Socio-ecological Risk Model Zone Floods in Boulder, Colorado, September 19th Total Number of Counties in High Risk Zone: 4 At risk County with most people: Weld State: Colorado Number of people affected: 88,569 High Medium Low
    11. 11. Socio-ecological Risk Surface Layer in Google Crisis Maps Vulnerability High Risk
    12. 12. High Medium Low 1,355,740 at risk for flooding
    13. 13. Typhoon Yolanda/Haiyan • Highest flood risk (3,163,156 people)
    14. 14. Safy Nurhussein @usaidoti
    15. 15. slain Mariette/AFP/Getty Images AP CONFLICTS & ALLIANCES IN MALI Violent Conflict Political Conflict Alliance Broken Alliance
    16. 16. slain Mariette/AFP/Getty Images AP CONFLICTS & ALLIANCES IN MALI Violent Conflict Political Conflict Alliance Broken Alliance
    17. 17. The Guardian
    18. 18. I N F O R M AT I O N C A M PA I G N S
    19. 19. PEACE C A R AVA N
    20. 20. ENCOURAGING PEOPLE TO VOTE
    21. 21. Al Jazeera
    22. 22. Al Jazeera
    23. 23. Xinhua
    24. 24. Reuters
    25. 25. Reuters
    26. 26. I N F O R M AT I O N S E R V I C E S W E R E MORE POPULAR THAN EXPECTED
    27. 27. HELPING VOTERS FIND THEIR BOOTHS AFP
    28. 28. Safy Nurhussein @usaidoti
    29. 29. Raquel Romano linkedin.com/in/romano
    30. 30. www.google.org/crisismap/a/.maps
    31. 31. www.google.org/crisismap/a/.maps
    32. 32. WMS Tile Cache tile request /tileset/12/35/64.png WMS Server memcache datastore
    33. 33. ~1200 replies from Sandy aftermath alone “How do I use the map? What does it mean?” “How old or new is this information?” “I see something different than what this map says.”
    34. 34. “How do I use the map?
    35. 35. “What does it mean?”
    36. 36. “How old or new is this information?” HTTP/1.1 200 OK Date: Mon, 11 Nov 2013 03:20:15 GMT Server: Apache/2.2.15 (Red Hat) Last-Modified: Mon, 11 Nov 2013 03:19:06 GMT Accept-Ranges: bytes Content-Length: 527849 Cache-Control: maxage=300 Expires: Mon, 11 Nov 2013 03:25:15 GMT Connection: close <?xml version="1.0" encoding="UTF-8"?> <kml xmlns="http://www.opengis .net/kml/2.2"> <Placemark> <name>Google NYC/name> <description> We are here. </description> <Point> <coordinates>40.740709,74.001999,0</coordinates> </Point> </Placemark> </kml> { 'fetch_last_modified': 'Wed, 18 Sep 2013 07:52:56 GMT', 'update_time': 1379490776, 'fetch_time': 1384140805.4296601, 'md5_hash': 'ce6c149147ad9af28d611fa1acdf113 b', 'fetch_status': 304, 'fetch_length': 0, 'length': 100837 }
    37. 37. “I see something different than what this map says.”
    38. 38. “I see something different than what this map says.”
    39. 39. How should I share what's going on with my contacts outside the city? What is my employer advising us to do? What is my school or teacher advising us to do? Will I lose my job if I leave? How much will it cost to evacuate? How do I move my elderly or sick loved one? What is everyone else in my neighborhood doing? Are they evacuating? Where would I evacuate to? What do city/parish officials advise? What do trusted local newscasters think? How does this storm compare with others that I've experienced? How severe is it? What is the path of the storm? What is the status of evacuation routes? What options are there if I have no car? How should I prepare my home for a potentially long-term evacuation? What stores are still open for last-minute supplies? What supplies do I need to ride out the storm? What are the essential things I need to take for a potentially long-term evacuation? Where can I get food and supplies along my evacuation route? Where are all of my friends and family? How can we let everyone know where we ended up? And check in with those who stayed behind? What are the essential things I need to know about my destination? How to keep sick/elderly/young children safe on the road? Where can I get medical care along my evacuation route? Contact information for emergency services where I ended up. What hotels and shelters have space? Who has gas? Where are the open ATMs on my evacuation route? What is the wait time at stores and other service centers? Where are the contraflow routes? Where are the backroads and alternate routes to avoid congestion? How to tap into charities and donations to ease the cost of evacuation? How do I stay in touch with people if the phone are lines down? How can I share the news about what's happening with the outside world? Who else in my neighborhood is also staying? Where can I get news updates specific to my neighborhood? Where should I store my possessions? Are there are authorities in my area sticking around (in case I need help)? What services are still up and running (e.g. police, fire)? If my home floods, where is the nearest safe place? Is there anyone around that needs shelter? Where is everyone and what is their status? Where can I get medical help? What pharmacies are open? How do I care for the sick or injured if there aren't medical facilities near by? How can I alert the outside world to conditions in my area? What are the announcements by city/local officials? What resources does my community have so we can share? How to alert others to resources I've found? When will the national guard or police be here (for safety)? How safe are the conditions in my area? How do I keep my area safe? When will power be back on in my area? Where in the area is there still power? Where is there WiFi? My home is destroyed - where can I find shelter? Where can I get a hot shower? Where can I find ice (to keep food fresh)? Where can I find clean water? What stores are open and what supplies do they have? Where can I get food? How do I keep my food supply safe from spoilage? Where can I wash my clothes? Where can I get cleaning supplies? Where can I get coupons for food, basic necessities? What is the wait time at stores and other service centers? Where can I go to get donations (clothes, etc.)? What are the requirements and deadlines for financial aid? What kind of aid can I qualify for? How can I dispute a rejection for aid? How can I keep track of where my applications stand? If I apply for one type, will I be disqualified for another? I've lost important documents in the storm. What are the steps to building a new life elsewhere? I need to find a new job or source of income since my job went with the storm. Where can I get mental health or spiritual help for PTSD? What are the steps in rebuilding a damaged home? Are there new construction regulations? Where can I get home repair supplies? What health issues should I watch out for (bad water, chemicals in home)? How to deal with toxins and mold in my home? Who in community has working resources (washing machine, car) to share? How to get the city to resume services, e.g. garbage pick-up? If services such as schools remain closed, where do I send my kids? How can I lobby for services such as libraries and schools to be rebuilt? Where can we
    40. 40. bit.ly/create-a-map www.google.org/crisismap/a/.maps
    41. 41. Kim Scriven @kimscriven
    42. 42. RAPIT FTR UNICEF – RAPID FTR
    43. 43. IFRC Two
    44. 44. Traditional methods still have relevance WASH for Children
    45. 45. Innovation not synonymous with technology
    46. 46. How we see innovation flickr/masondan
    47. 47. Donor governments Private donors UN agencies 3rd party military Government agencies Red Cross Movement International NGOs Recipient country National Rec Cross/Crescent Affected population General public (recipient countries) Local NGOs Information Resources Donor organisations
    48. 48. Donor governments Private donors UN agencies 3rd party military Government agencies Red Cross Movement International NGOs Recipient country National Rec Cross/Crescent Affected population General public (recipient countries) Local NGOs Information Resources Donor organisations
    49. 49. The system does have enormous capacity to deliver and save lives
    50. 50. The system needs to continue to evolve In response ton increasing hazards an needs… …and changes in the nature and contexts of response
    51. 51. Sphere HIVAIDS ICVA HAP Gender JSI Quality, learning, ac countability and advocacy Rights Thematic development ALNAP How it tries to change WEF Business practices Capacity build HC Joint action & partnerships Clusters Decentra lisation CERF Structure ECB Media
    52. 52. “If you always do what you always did, you will always get what you always got”
    53. 53. How we see innovation flickr/masondan
    54. 54. Skunkworks Hugely successful Closed, protected team of dedicated experts, separate from core business High financial investment in Research and & Development (based on use of patents)
    55. 55. O p e n n n wo v a t i o n Sku Ikn orks flickr/cattoo
    56. 56. Open Innovation Drawing on the edges See risk and high levels of failure as inevitable and better shared Reduced cost of conducting research and development) flickr/cattoo
    57. 57. Answers Actually, more questions…
    58. 58. Have a go at these THREE Collaboration Engaging users Accepting failure and risk
    59. 59. Thank you! Kim Scriven www.humanitarianinnovation.org @kimscriven
    60. 60. Mutitu Raphael @mutituR
    61. 61. GIS (GEOGRAPHIC INFORMATION SYSTEM) applications in smart phones and open source mapping soft wares for DRR(DISASTER RISK REDUCTION)…
    62. 62. NAIROBI VS KENYA MAPPING COMPARISON
    63. 63. What Mapping strategy???? Populating maps with data for DRR
    64. 64. CHEAP QUICK EFFECTIVE
    65. 65. + +
    66. 66. TRAININGS
    67. 67. GIS APPS IN SMART PHONES: Data collection
    68. 68. OPEN SOURCE MAPPING SOFT WARES: DATA ANALYSIS
    69. 69. Database Web-platform
    70. 70. FOLLOW UP:
    71. 71. FRONT LINE SMS(TRIGGER ZONES)
    72. 72. TRIGGER ZONES ZONE 1 ZONE 2 Sms ZONE 3 ZONE 4
    73. 73. FIRE RISK STUDY IN KIANDUTU SLUMS THIKA.
    74. 74. APPLICATIONS Decision making. Informational purposes. Academic work and research.
    75. 75. EXTENSIVE MAPPING FOR FREE OPEN MAPS FOR ALL.
    76. 76. THANK YOU 
    77. 77. Helena Puig Larrauri @helenapuigl
    78. 78. Mapping tools for field teams Iraq Dispute Monitoring System Libya Protection Monitoring System
    79. 79. Mapping tools for field teams Iraq Dispute Monitoring System Libya Protection Monitoring System
    80. 80. Iraqi Centre for Negotiation and Conflict Management
    81. 81. Dispute monitoring
    82. 82. Analysing patterns of disputes
    83. 83. Analysing patterns of disputes
    84. 84. Crowdmap + Excel
    85. 85. Crowdmap + Excel
    86. 86. Libya Protection Monitoring Team (Mercy Corps and LibAid)
    87. 87. Libya Protection Monitoring Team (Mercy Corps and LibAid)
    88. 88. Analysing patterns of need
    89. 89. Analysing patterns of need
    90. 90. Google Fusion Tables and Google Crisis Map
    91. 91. Google Fusion Tables and Google Crisis Map
    92. 92. Making maps for programming Make less work!
    93. 93. Making maps for programming Make less work! And make it super cool.
    94. 94. Making maps for programming Adapt to what already works
    95. 95. Making maps for programming Adapt to what already works And demonstrate added value.
    96. 96. Making maps for programming Start a conversation
    97. 97. Making maps for programming Start a conversation And challenge assumptions
    98. 98. Abeer Khairy @beeromagied
    99. 99. • 9.1% of gov. expenditure on Education • 20% Illiterate Man. • 38% Illiterate Woman. • The Background Picture Are a Black board and desks! Education Without Borders
    100. 100. Challenges: • Introducing Crowdsourcing Model. • Internet Access • Mapping Skills • Verification for inaccessible areas. • Engaging Actors with the platform. Education Without Borders
    101. 101. Sudanese teachers in Darfur
    102. 102. irevolution.net/2009/04/09/threat-and-risk-mapping-analysis-in-sudan
    103. 103. Japanese Project for the improvement of water sanitation at schools in Sudan
    104. 104. Education Without Borders community after „hit and run‟ school maintenance
    105. 105. Child Friendly Cities UNICEF Sudan
    106. 106. Johanna Khisa @jvkenya @peacegeeks
    107. 107. AMANI
    108. 108. MAPS TEXT LAYOUT REPLICABLE STANDARDIZED EASY INTERFACE
    109. 109. OUR CHALLENGE Create 1-click install CMS and mapping tool
    110. 110. PARTNER NEEDS EASE LOCALE UPGRADES CMS REPORTING MOBILE MAPS CONTACTS SPEED
    111. 111. PLAN B
    112. 112. CMS DASHBOARD
    113. 113. MAP DATA
    114. 114. CUSTOMIZATION
    115. 115. AMANI KESHO
    116. 116. FORWARD LOOKING
    117. 117. WE ARE READY TO Collaborate Develop Partner Implement
    118. 118. Amani demo at the Tech Fair github.com/peacegeeks/amani wiki.peacegeeks.org.org peacegeeks.org @peacegeeks @jvkhisa
    119. 119. Kepha Ngito @Ngitok
    120. 120. Map Kibera
    121. 121. Voice of Kibera
    122. 122. Mathare Voice of Mathare
    123. 123. Kenya Elections 2013
    124. 124. Elections monitoring Methodology a.) Planning and training b.) Data collection and editing (OSM) c.) Mapping - Boundaries - Polling stations - Police posts/stations - Emergency Humanitarian centers d.) Map printing and distribution e.) SMS and video reporting. f.) Offline engagement (wall paintings etc)
    125. 125. Elections monitoring Methodology a.) Planning and training b.) Data collection and editing (OSM) c.) Mapping - Boundaries - Polling stations - Police posts/stations - Emergency Humanitarian centers d.) Map printing and distribution e.) SMS and video reporting. f.) Offline engagement (wall paintings etc)
    126. 126. Civic engagement Map Kibera joined other organizations to form the Kibera Civic Watch Consortium which among other things; a.) Organized the first Kibera Parliamentary Candidates debate and b.) Interviewed all political candidates on camera about their commitments and promises.
    127. 127. Community engagement a.) Regular community screening forums where short films were watched and debated by participants. b.) Feed back forums where data and blog stories are shared offline to invited community members and leaders. c.) Map printing and distribution to organizations and agencies that need them. d.) Map painting on community walls and open spaces.
    128. 128. Community engagement a.) Regular community screening forums where short films were watched and debated by participants. b.) Feed back forums where data and blog stories are shared offline to invited community members and leaders. c.) Map printing and distribution to organizations and agencies that need them. d.) Map painting on community walls and open spaces.
    129. 129. Collaborations Map Kibera collaborated with the Uchaguzi elections Monitoring project and Ushahidi. a.) Sharing workspaces b.) Verifying information together and working with each other’s sources. c.) Sharing data-bases of Humanitarian intervention institutions/agencies
    130. 130. Collaborations Map Kibera collaborated with the Uchaguzi elections Monitoring project and Ushahidi. a.) Sharing workspaces b.) Verifying information together and working with each other’s sources. c.) Sharing data-bases of Humanitarian intervention institutions/agencies
    131. 131. Success stories • Map Kibera’s Security maps used by Police and Peace builders to enhance security and promote peace in the local neighborhoods. Printed Maps were distributed to the Police, The local administration and the District Peace Committees in both locations.
    132. 132. • Map Kibera successfully used its methodology and tools to monitor the 2013 general elections in Kibera, Mathare and partially in Mukuru slums reducing likelihood of violence to almost zero in these election hotspot locations.
    133. 133. • Since Map Kibera began focusing on dangerous or ‘black spots’ and mapping them in Kibera and Mathare, New police posts have been constructed in response.
    134. 134. • Kibera and Mathare slums are now open more open and accessible than before. Generated map data has made development agencies and devolved government committees enhance their intervention approaches to minimize duplication of projects and design more relevant interventions.
    135. 135. • Several agencies, researchers and organizations continue to approach Map Kibera for more data on various thematic subjects covered by Map Kibera’s mapping.
    136. 136. “Your maps have saved my life, You should do this allover the country!” Kilimani Police Station OCPD on receiving a copy of the new elections map in Kibera. February 2013.
    137. 137. CONTACT US Email: contact@mapkibera.org www.voiceofkibera.org www.voiceofmathare.org www.voiceofmukuru.org www.mapkibera.org
    138. 138. Carlos Castillo @ChaToX @QatarComputing
    139. 139. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    140. 140. Goal: to sort tweets into different categories in real-time AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    141. 141. How do you classify 200+ tweets/minute? Option 1: process what you can AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    142. 142. How do you classify 200+ tweets/minute? Option 2: lists of keywords “Disaster” or “Damage” or … or “Bridge” but not “Game” or … “Donation” and “Money” but not … or “Missing person” or “Missing people” or “Missing” and “child” … and “Tornado alert” and “Tsunami alert” and … and … or … and … but not … AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    143. 143. Artificial Intelligence … … … Supervised Learning
    144. 144. Supervised Learning • Label a small number of tweets – Crowdsourcing • Convert tweets to numerical vectors – Feature extraction: not seen by the user • Create a mathematical model of each class – Statistical learning: not seen by the user • Automatically categorize new elements – Output to be used by maps, reports, etc. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    145. 145. Supervised learning for Twitter AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    146. 146. Challenges • Effectiveness and generality – Classify accurately for each crisis – Work well across crises • Easy to use! AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    147. 147. Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it may perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a webbased interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for betatesting ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ All work and no play makes Jack a dull boy ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it might go bananas or stop working during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets
    148. 148. Collector: easily create Twitter collection processes by geographical coordinates, keywords or #hashtags.
    149. 149. Changes to keywords or geo region are stored for future reference. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    150. 150. Tagger: easily create automatic classifiers for your collection. Each classifier has its own set of categories. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    151. 151. 1 2 You can ask volunteers to provide training labels 1 , or create them yourself 2 . AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    152. 152. Clickers: AIDR automatically creates a publicly-visible landing page for volunteers. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    153. 153. This is what volunteers see: one tweet after another, with a series of options. Tweets to classify are selected by AIDR to maximize accuracy gains. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    154. 154. Behind the scenes, AIDR learns words and how to use them to classify tweets, e.g. “katyperry” => ~no, “secrecy” => ~yes, etc. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    155. 155. Experiments AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    156. 156. Output • Export to .csv from the Collector – For off-line analysis • Live data feed in JSON format – For creating crisis maps, reports, etc. AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    157. 157. Example application: Crisis Tracker AIDR: Artificial Intelligence for Disaster Response http://aidr.qcri.org/
    158. 158. Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to useto the AIDR team: Muhammad Imran, Jakob∙ As most Thanks through a web-based interface ∙ Available for beta-testing systems it may perform poorly or not at all during the testing phase ∙ Free and open Rogstadious, Ji Lucas & Patrick Meier. Qatar Computing source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will Research Institute. perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a webbased interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for betatesting ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it will perform poorly or not at all during the testing phase ∙ Free and open source software ∙ http://aidr.qcri.org/ Implements supervised learning for disaster-related tweets ∙ All work and no play makes Jack a dull boy ∙ Easy to use through a web-based interface ∙ Available for beta-testing ∙ As most systems it might go bananas or stop working during the testing phase ∙ Free and open source software ∙ Implements supervised learning for disaster-related tweets
    159. 159. Justine Mackinnon @fidget02
    160. 160. MicroMappers.com Photo Video Text   
    161. 161. MicroMappers.com
    162. 162. Hospital devastated #Tacloban
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