14 crowdsourcinggi

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14 crowdsourcinggi

  1. 1. CROWDSOURCING AND GI JAVIER MORALES
  2. 2. AGENDACROWDSOURCING AND SPATIAL DATA INFRASTRUCTURES Background Crowdsourcing Principles Examples Conclusions © Manuel Ramos © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 2
  3. 3. BACKGROUNDTHE ROLE OF GI Geographic information (GI) was for generations produced and consumed by professionals Societal processes  land transfer,  planning and development,  risk management  … that affect organisations and individuals. Trend to develop mechanisms to bring GI closer to non-professional users © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 3
  4. 4. BACKGROUNDMODERN TOOLS Web 2.0  high interactivity,  sharing and collaboration,  Interoperability, and  real-time user-generated content Web 2.0 apps  social networking,  blogging,  wikis,  video sharing, and  Mashups © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 4
  5. 5. BACKGROUNDWEB 2.0 The users’ role has changed from looking for and retrieving content  to active participation © www.techscreens.com everyone contributes to the common knowledge of the group they interact with Wikipedia, YouTube, Flickr, Wikimedia © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 5
  6. 6. CROWDSOURCINGWHY? Organisations today have to operate in information-rich environments  They can no longer afford to rely entirely on their own ideas  They cannot bet their success to a single product to the market Traditional development which largely focused on  intra-organisational skills,  closed off from outside ideas and technologies is becoming obsolete © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 6
  7. 7. CROWD-WHAT? Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call. Jeff Howe © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 7
  8. 8. CROW-WHAT? The crowdsourcing approach  a recognised entity posts a problem online  a large number of individuals reacts  they provide a small part of the solution to the problem  solutions offered are exhaustive and not disjoint This approach is popular because  web-based social technology makes it feasible & affordable to collect data using groups of individuals  such data is often more accurate indicator of current conditions in the real world than what can be obtained from data stored in databases © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 8
  9. 9. CROWDSOURCING PRINCIPLES1. Formulate the problem properly  Scope & purpose2. State deliverables concretely (quality)  let the crowd know exactly what is expected from them  leave space for their creativity3. Connect with the right crowd  diversity (the question is answered from multiple points of view)  scientists or specialists and a significant number of hobbyists with knowledge in the problem domain4. Deploy the appropriate crowd management scheme  moderate discussion boards  post provocative challenges & publish milestones © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 9
  10. 10. EXAMPLES Ushahidi GeoNames Geonode Google MapMaker OpenStreetMaps Aim at providing open data through the Creative Commons Attribution – ShareAlike license data can be used freely and if you alter or build upon it, you need to share those alterations back to the community © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 10
  11. 11. OPEN DATAData is considered to be open if  it is and publish online,  updated as often as possible,  provided in a way that allows for its legal use for any purpose, and  that allows easy processing with any arbitrary software program © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 11
  12. 12. OPENSTREETMAP The OpenStreetMap project is a crowdsourced geospatial data repository, with a global cast of volunteers. With the mission to create a free editable dataset of the world It has been very successful especially  In producing data fro places where it was very scarce (rural & peri-urban areas)  In keeping up-to-date datasets of rapidly evolving urban areas © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 12
  13. 13. OPENSTREETMAPA YEAR OF EDITS © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 13
  14. 14. OPENSTREETMAPPROJECT HAITI - 2010 © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 14
  15. 15. OPENSTREETMAP © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 15
  16. 16. SPATIAL DATASETSCROWDSOURCING IMPACT Chia, Colombia Maps © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 16
  17. 17. OPENSTREETMAPCOMPARISON Enschede © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 17
  18. 18. OPENSTREETMAPCOMPARISON Guatemala City © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 18
  19. 19. SPATIAL DATASETSCROWDSOURCING IMPACT Lahore, Pakistan in Lahore, Pakistan in Google Maps Google Maps (before MapMaker) (after MapMaker) © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 19
  20. 20. SPATIAL DATASETSCROWDSOURCING IMPACT Bolivia © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 20
  21. 21. USHAHIDIHISTORY © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 21
  22. 22. USHAHIDIWORKING APPROACH © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 22
  23. 23. USHAHIDIDATA INPUTS © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 23
  24. 24. USHAHIDIEXPLOITATION Disaster Response © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 24
  25. 25. USHAHIDIEXAMPLES http://ushahidi.internewskenya.org/ © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 25
  26. 26. USHAHIDIEXAMPLES http://haiti.ushahidi.com/ © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 26
  27. 27. CONCLUSIONSCROWDS & SDI Work on something relevant (or at least has the promise of being useful relatively soon) Put the users at the center  View users as important contributors  Give them responsibility  Enable ratings  Derive metadata from usage Make customization as easy as possible  Enable mashups  Unlock the visualizations Index your data and become searchable © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 27
  28. 28. CHALLENGESRESEARCH ISSUES Automatic validation an filtering of data inputs Indirect geo-tagging (mining of social networks) Automatic aggregation & summarizing of similar data entries © Community FixIt © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 28
  29. 29. © Department of Geo-information Processing (GIP) – 27-Oct-2011 – 29

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