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Crowdsourcing
Information in the
Drylands
Nathan Jensen
ILRI
Problem Statement
Information scarcity is severely limiting development and
resource management in the drylands.
Problem Statement
Information scarcity is severely limiting development and
resource management in the drylands.
Why?
• There are few existing accurate public datasets available with which to learn
about dynamics in the drylands.
• Collecting data using conventional methods is extremely costly in these
environments.
 So we know little and it is expensive to learn more.
Problem Statement
Information scarcity is severely limiting development and
resource management in the drylands.
Solution: To develop a data collection, verification, and dissemination
platform that is:
• Structured for public use
• Cost-effective
• Flexible and highly functional-can collect different types of data
• Generates high-quality, trusted data
• Sustainable
Dryland Information System
Dryland Information System: Implementation
Key system attributes:
Front end:
• Mobile app by which data collection tasks are
pushed to contributors.
• Contributors execute on tasks, each of which
is attached to a value to a reward.
Back end:
• Task authoring & parameterizing system for
translating client requirements into specified
tasks and incentives.
• Manual and automated validation checks
• Database from which a range of data
products are delivered to clients.
Camp
Water point
Trajectories
(color varies
by household)
Progress to date
Passive data collection on migration
• GPS collar traces of 60 cattle from 20 households in 5 villages, at 5-
minute intervals over 3 years
Progress to date
Passive data collection on migration
• GPS collar traces of 60 cattle from 20 households in 5 villages, at 5-
minute intervals over 3 years
Crowdsourcing rangeland conditions from pastoralists
• Spatially and temporally varying rewards to reduce clustering
• >110,000 submissions on vegetation abundance & palatability
Progress to date
Passive data collection on migration
• GPS collar traces of 60 cattle from 20 households in 5 villages, at 5-
minute intervals over 3 years
Crowdsourcing rangeland conditions from pastoralists
• Spatially and temporally varying rewards to reduce clustering
• >110,000 submissions on vegetation abundance & palatability
Livestock market information from market regulars
• 5 weekly livestock markets for 5 months
• Used geofencing and market calendars to reduce fraud
• Multiple monitors per market for cross validation
0
15000300004500060000
PriceinKsh
22 26 30 34 38 42
Week
Fat Moderate
Thin
*Week 22 starts on May 29
*Week 42 ends on Oct 20
Based on Body Type
Median Cattle Price in all Markets from May - Oct 2017
Progress to date
Passive data collection on migration
• GPS collar traces of 60 cattle from 20 households in 5 villages, at 5-
minute intervals over 3 years
Crowdsourcing rangeland conditions from pastoralists
• Spatially and temporally varying rewards to reduce clustering
• >110,000 submissions on vegetation abundance & palatability
Livestock market information from market regulars
• 5 weekly livestock markets for 5 months
• Used geofencing and market calendars to reduce fraud
• Multiple monitors per market for cross validation
Extension & training: client/agent profiling, extension,
evaluations
Household-collected data on young child diet and health
Thank you!
bigdata.cgiar.org
n.jensen@cigar.org

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Crowdsourcing Information in the Drylands

  • 2. Problem Statement Information scarcity is severely limiting development and resource management in the drylands.
  • 3. Problem Statement Information scarcity is severely limiting development and resource management in the drylands. Why? • There are few existing accurate public datasets available with which to learn about dynamics in the drylands. • Collecting data using conventional methods is extremely costly in these environments.  So we know little and it is expensive to learn more.
  • 4. Problem Statement Information scarcity is severely limiting development and resource management in the drylands. Solution: To develop a data collection, verification, and dissemination platform that is: • Structured for public use • Cost-effective • Flexible and highly functional-can collect different types of data • Generates high-quality, trusted data • Sustainable
  • 6. Dryland Information System: Implementation Key system attributes: Front end: • Mobile app by which data collection tasks are pushed to contributors. • Contributors execute on tasks, each of which is attached to a value to a reward. Back end: • Task authoring & parameterizing system for translating client requirements into specified tasks and incentives. • Manual and automated validation checks • Database from which a range of data products are delivered to clients.
  • 7. Camp Water point Trajectories (color varies by household) Progress to date Passive data collection on migration • GPS collar traces of 60 cattle from 20 households in 5 villages, at 5- minute intervals over 3 years
  • 8. Progress to date Passive data collection on migration • GPS collar traces of 60 cattle from 20 households in 5 villages, at 5- minute intervals over 3 years Crowdsourcing rangeland conditions from pastoralists • Spatially and temporally varying rewards to reduce clustering • >110,000 submissions on vegetation abundance & palatability
  • 9. Progress to date Passive data collection on migration • GPS collar traces of 60 cattle from 20 households in 5 villages, at 5- minute intervals over 3 years Crowdsourcing rangeland conditions from pastoralists • Spatially and temporally varying rewards to reduce clustering • >110,000 submissions on vegetation abundance & palatability Livestock market information from market regulars • 5 weekly livestock markets for 5 months • Used geofencing and market calendars to reduce fraud • Multiple monitors per market for cross validation 0 15000300004500060000 PriceinKsh 22 26 30 34 38 42 Week Fat Moderate Thin *Week 22 starts on May 29 *Week 42 ends on Oct 20 Based on Body Type Median Cattle Price in all Markets from May - Oct 2017
  • 10. Progress to date Passive data collection on migration • GPS collar traces of 60 cattle from 20 households in 5 villages, at 5- minute intervals over 3 years Crowdsourcing rangeland conditions from pastoralists • Spatially and temporally varying rewards to reduce clustering • >110,000 submissions on vegetation abundance & palatability Livestock market information from market regulars • 5 weekly livestock markets for 5 months • Used geofencing and market calendars to reduce fraud • Multiple monitors per market for cross validation Extension & training: client/agent profiling, extension, evaluations Household-collected data on young child diet and health