A presentation prepared by Ric Coe

1. What data, from where? Presented by Ric Coe (ICRAF/ILRI Research Methods Group, r.coe@cgiar.org) at the Workshop on Dealing with Drivers of Rapid Change in Africa: Integration of Lessons from Long-term Research on INRM, ILRI, Nairobi, June 12-13, 2008

4. National coverage, some international standardisation

5. Increasing international coverage and compliance

6. Initiatives to increase integration

7. Paris21

8. Marrakech Action Plan for Stats

9. Initiatives to increase availability of disaggregate data

10. International Household Survey Network

11. Much still of doubtful quality

12. IP culture at national finer scales still rewards data ownership not data supply

13. Coverage patchy

15. raw and processed layers

16. multiple scales

17. multiple time points

18. standardisation in formats

20. 90 data sets compiled

21. meta data available, searchable

22. Protocols

24. including complex questions

25. one-off, rarely repeated

26. limited geographic scope

27. even if multi-country

28. little standardisation in indicators and definitions

29. Often very small sample size with poorly defined sampling frame

31. between short term funded projects and their host organisations

32. Note OECD standards for public availability of data from public funded research

33. Few incentives for ensuring long term security and access

34. Few quality assurance and documentation standards

35. Limited repositories

36. A outdated culture of data ownership rather than provision

38. Inter-centre Research Data Management Workshop agreed

39. Data provision and sharing should become an objective of the CG centres

40. Incentives to share data to be developed

42. Maximise value of other initiatives to collate studies by providing a facility for long term archiving and access

43. Provide links to other data sources, particularly those that put agriculture in context (environmental, social, economic)

44. Develop methods to increase data generation efficiency

45. Support development of national and regional data generation and integration services

48. Minimum data sets

49. Definitions

50. Longitudinal and panel dataNatural resources Consumption and welfare Production and markets Standards and methods Intersector integration Archiving and access

52. Methods that build on other wide scale surveys

53. Rapid methods for key indicators (avoiding the 40 page questionnaire)Standards and methods Intersector integration Archiving and access

55. Codebooks

56. Quality assurance

57. Linking to other data sourcesStandards and methods Intersector integration Archiving and access

59. Confidentiality

60. Ownership and other IP issuesPhysical archive and means of access Long term secure archive Catalogues, visualisation of coverages Retrieval and dissemination Natural resources Consumption and welfare Production and markets Standards and methods Intersector integration Archiving and access

63. Problems:

64. confounders

65. multiple causes

66. proximal and underlying

67. feedback and time scalesAt-1 At A At+1 Bt-1 Bt B Bt+1 C Ct-1 Ct Ct+1

69. II. CASE STUDIES A. Rangeland Management Australia / NSW: = Sheep # = Social drivers & responses Global Sub-regional Networking (reciprocity, knowledge exchange) Political organizing Scale of Drivers & Responses Expansion of watering points to access new rangeland; reduced stocking density Local 1860 Time 2000

70. II. CASE STUDIES A. Rangeland Management Australia / NSW: = Sheep # Korean War (wool $$) = Political-economic drivers & responses Global Price support ends Rural political dominance Urban dominance, “Closer Settlement” Scale of Drivers & Responses Strong economy Publicly funded water supplies / stock routes Local 1860 Time 2000

72. Starts with the conceptual frame…

73. Leads to numerous proposed components, links, processes