Scaling Crisismapping

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SMERST keynote, April 2013

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Scaling Crisismapping

  1. 1. Scaling CrisismappingSara-Jayne FarmerChange Assembly
  2. 2. WHERE WE’VE BEEN: WHY
  3. 3. Why
  4. 4. Broken Systems• Communities• Processes• Tech• Innovation
  5. 5. (Some of) What Broke• Crisis Data– Remote vs Ground disconnect– Crisis vs Development disconnect– Deployment lead overload• Development Data– Broken data formats, access, coverage, standards– Ignored data sources– Human vs Data disconnect• Communities– Stovepipes, fiefdoms, imperialism, finding…
  6. 6. I’ve tried to help fix that from…• CrisisCamp London• Crisiscommons projects• Standby Task Force• Humanity Road• United Nations – EOSG/ Global Pulse• Ushahidi developers• (pacifist) military system design• NY VOST• Crisismappers NYC• ICT4D London• ICCM• Humanitarian systems consultancy• Also been in one tornado, two hurricanes, snowstorms, floods, 1 nuclearalert, 1 conflict, 1 cold war, but never as an on-the-ground responder
  7. 7. WHERE WE’VE BEEN: CRISIS DATA
  8. 8. Typical Workflow
  9. 9. Find…
  10. 10. Listen…
  11. 11. Estimate…
  12. 12. Geolocate…
  13. 13. Erm… you also need a map…
  14. 14. Analyse
  15. 15. Use
  16. 16. WHERE WE’VE BEEN:DEVELOPMENT DATA
  17. 17. Typical WorkflowWebsites:HTML, XLS,CSV,APIs etcCSV stores(online andoffline)Partially-filledspreadsheetCompletedspreadsheetDNAScrapers& APIsTemplateCreatorVolunteerResearchersAnalysts
  18. 18. Data AccessOnline, under an open licenseStructured (e.g. Excel, not PDF)Non-proprietary (e.g. CSV, not Arcgis)URI / API (so people can point at it)Linked to other data (to give context)
  19. 19. Clean
  20. 20. StandardiseDR Congo in Data.UN.Org:• “Congo, Democratic Republic of the”, “Congo Democratic”,“Democratic Republic of the Congo”, “Congo (Democratic Republicof the)”, “Congo, Dem. Rep.”, “Congo Dem. Rep.”, “Congo,Democratic Republic of”, “Dem. Rep. of Congo”, “Dem. Rep. of theCongo”DR Congo in common standards:• “Democratic Republic of the Congo” (UN Stats), “Congo, TheDemocratic Republic of the” (ISO3166), “Congo, DemocraticRepublic of the” (FIPS10, Stanag), “180” (UN Stats), “COD”(ISO3166, Stanag), “CG” (FIPS10)
  21. 21. Analyse
  22. 22. Use
  23. 23. WHERE WE’VE BEEN:KNOWLEDGE SHARING
  24. 24. Knowledge Aggregators
  25. 25. Knowledge Aggregators
  26. 26. Knowledge Aggregators
  27. 27. Connectors
  28. 28. Specialisations
  29. 29. Training
  30. 30. Technologies• Hackathons (H4D2, RHOK, Space Apps Challenge)• Open source codebases(Ushahidi, Sahana, Taarifa, ckan, OpenStreetMap etc)• Commercial software(ESRI, Google, dropbox, skype, Crowdflower, ning, sparkrelief, recovers.org, many startups etc.)• Academic experiments (e.g. TweakTheTweet)• I.e. code and work from many of you…
  31. 31. Evolving Technologies
  32. 32. AT THE SAME TIME: BIG DATA
  33. 33. Enthusiastic Sponsor
  34. 34. Knowledge Aggregators
  35. 35. Specialisations & Embedding
  36. 36. Industry & Tool Maps
  37. 37. Formal (Free) Training
  38. 38. Knowledge Sharing
  39. 39. Targetted Volunteering
  40. 40. AT THE SAME TIME:CITIZEN SCIENCE
  41. 41. Grassroots Communities
  42. 42. Communities of Communities
  43. 43. Mixing Communities and Commerce
  44. 44. WHERE WE’RE GOING
  45. 45. These things are good• Crisismapping established as a field• Talented individuals have new routes into humanitarianwork• Academic and VTC communities formed• Healthy open-source software environment• Changed UN from broadcast to (partly) listen• Added surge capacity and social media analysis to crises• Encouraged other communities-for-good
  46. 46. But Some Differences• No big publisher-sponsors• Less focus on grassroots capabilities• European communities still disconnected• Little formal training• Almost no meetups• No visible benefits to companies (but insurance?)• Few volunteer reward systems• Unformed markets for systems and services• Very little knowledge curation• No “in a box” kit for countries/ cities/ communities
  47. 47. What could we do?• Catalogue what we have– Encourage visible knowledge aggregators– Map what we have (e.g. Mendelay, tools, companies)– Populate datastores• Apply data & citizen science business patterns– Adjust patterns to our environment– Check whats there, whats missing, whats unique
  48. 48. e.g. these patterns• Build better connectors– Reach out to stakeholders– Make the commercial case for mapping– Create and equip local communities– Embed mappers in organisations• Understand roles– Describe specialisations• Build better tools– Fit tools to people’s problems– Create tools for non-specialists• Etc.
  49. 49. e.g. Build better EU Connectors• NGOs• Emergency services• Military• Academics• Local organisations• Local people• Hackers• VTCs• Etc.
  50. 50. e.g. Reach out to Stakeholders• Map the stakeholders• Make the commercial case for mapping• Embed mappers in organisations• Create and equip local communities• Start meetupsEtc.
  51. 51. e.g. Describe Specialisations• Turksourcer• Specialist volunteer• Community lead• Designer• SMEM specialist• Etc.
  52. 52. sara@changeassembly.com@bodaceacatwww.ChangeAssembly.comwww.opencrisis.netwww.overcognition.comicanhazdatascience.blogspot.comwww.meetup.com/crisismappersnyc

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