1
Big data and climate change:
Big words or big opportunity?
Innovative approaches to disseminating CSA practices and advi...
2
1. Big data, what is it?
2. Big words only?
3. What about CCAFS?
3
4
Social data / crowdsourcing
5
6
Bioinformatics
7
8
Data journalism
9
A movie passes the Bechdel Test if women that are named
have at least one conversation that is not about a man.
10
Crowdsourcing
11
12
13
In summary
• ICT generate more and more data
• Data are going social
• Big Data is about “repurposing” in many differen...
14
Big words only?
15
16
17
18
19
20
21
Gartner’s hype cycle
22
Where is Big Data on the curve?
23
24
In summary
• Many caveats apply
• Big Data is on the Peak of Inflated Expectations
• There is a Plateau of Productivity...
25
What about CCAFS?
26
Historical data
27
28
Big data illusions
29
30
Sensors
31
32
33
Site-specific agriculture (CIAT)
+ + =
Climate Soil Crop management Productivity
% ? + % ? + % ? = To Explain (100 %)
34
Citizen science
35
36
37
Nifty statistics:
Bradley-Terry model with recursive partitioning
38
39
4. Farmers
test and
report back
by mobile
phone
2. Each farmer gets a
different combination of
varieties
3. Environment...
40
Crowdsourcing Monitoring and Evaluation?
41
42
In conclusion…
43
but some work is required to get it
44
Big data session
Two micro-presentations
•Participatory modelling with historical crop data (Dieudonne
Harahagazwe, CIP...
45
Thank you!
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Big data and climate change: Big words or big opportunity? Innovative approaches to introducing climate-smart agriculture practices and advice

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Bioversity International scientist Jacob van Etten presents on Innovative approaches to disseminating Climate-smart agricultural practices and advisories. Find out more about what we do on climate change adaptation: http://www.bioversityinternational.org/research-portfolio/adaptation-to-climate-change/

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Big data and climate change: Big words or big opportunity? Innovative approaches to introducing climate-smart agriculture practices and advice

  1. 1. 1 Big data and climate change: Big words or big opportunity? Innovative approaches to disseminating CSA practices and advisories Jacob van Etten Theme leader Climate Change Adaptation 9th April 2014
  2. 2. 2 1. Big data, what is it? 2. Big words only? 3. What about CCAFS?
  3. 3. 3
  4. 4. 4 Social data / crowdsourcing
  5. 5. 5
  6. 6. 6 Bioinformatics
  7. 7. 7
  8. 8. 8 Data journalism
  9. 9. 9 A movie passes the Bechdel Test if women that are named have at least one conversation that is not about a man.
  10. 10. 10 Crowdsourcing
  11. 11. 11
  12. 12. 12
  13. 13. 13 In summary • ICT generate more and more data • Data are going social • Big Data is about “repurposing” in many different ways • Dumb force of big n obviates precision, long waits and big $
  14. 14. 14 Big words only?
  15. 15. 15
  16. 16. 16
  17. 17. 17
  18. 18. 18
  19. 19. 19
  20. 20. 20
  21. 21. 21 Gartner’s hype cycle
  22. 22. 22 Where is Big Data on the curve?
  23. 23. 23
  24. 24. 24 In summary • Many caveats apply • Big Data is on the Peak of Inflated Expectations • There is a Plateau of Productivity ahead!
  25. 25. 25 What about CCAFS?
  26. 26. 26 Historical data
  27. 27. 27
  28. 28. 28 Big data illusions
  29. 29. 29
  30. 30. 30 Sensors
  31. 31. 31
  32. 32. 32
  33. 33. 33 Site-specific agriculture (CIAT) + + = Climate Soil Crop management Productivity % ? + % ? + % ? = To Explain (100 %)
  34. 34. 34 Citizen science
  35. 35. 35
  36. 36. 36
  37. 37. 37 Nifty statistics: Bradley-Terry model with recursive partitioning
  38. 38. 38
  39. 39. 39 4. Farmers test and report back by mobile phone 2. Each farmer gets a different combination of varieties 3. Environmental data (GPS, sensors) to assess adaptation 1. A broad set of varieties is evaluated 6. Detect demand for new varieties and traits 5. Farmers receive tailored variety recommendations and can order seeds
  40. 40. 40 Crowdsourcing Monitoring and Evaluation?
  41. 41. 41
  42. 42. 42 In conclusion…
  43. 43. 43 but some work is required to get it
  44. 44. 44 Big data session Two micro-presentations •Participatory modelling with historical crop data (Dieudonne Harahagazwe, CIP) •Big data to optimize agricultural systems through location- specific advise (Daniel Jiménez, CIAT) Group discussion
  45. 45. 45 Thank you!
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