Data analyses of Rio Markers

for the UNCCD 5th reporting

and review cycle

• Statistics, planned work and goals

• Dr. Philippe Saner (University of Zürich) and Matthias Haeni (ETH Zürich)

June 3, 2014

Optimize reporting by cross-evaluating ODA and

UNCCD data sets

• Create an easy-to-understand statistical overview of activities under Rio

Marker 3: Principal and significant score of aid, targeting “desertification”

June 3, 2014 Page 1

Introduce multilevel sankey diagrams

• Multidimensional and historical overview of data by sectors, countries,

continents, etc.

• In addition, focus on sectoral (water/sanitation, agriculture, forestry) and

non-sectoral activities (environmental policy/administrative management,

education/training and research)

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0.0

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3500.0

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Perform statistical analyses and visualizations in R

• Access MySQL database directly through R statistical software (no

exports or Excel files required)

• Interactive visualizations from R statistical software with for example

rCharts() or googleVis(), docking to javascript language (D3.js)

• Statistical analyses of non-linear trends with for example nlme()

• Source code readily available to ensure transparency (once script is

written and compiled, use automatically)

• Easy to include more data and re-run the code for future analyses

• Publication quality graphics

June 3, 2014 Page 3

Questions or comments? Please contact us:

• Dr. Philippe Saner, University of Zürich, Switzerland

philippe.saner@uzh.ch

+41 76 581 81 88

• Matthias Haeni, ETH Zürich, Switzerland

matthias@treenet.info

+41 79 511 51 83

Thank you for your attention!

June 3, 2014 Page 4