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Leave no one behindThe in-country professionals responsible for monitoring such indicators need to understand how they are defined, how data can be collected to assess them, and how to produce information on them that supports policy-makers in the pursuit of improving the indicator scores. In many cases, maps and associated tables can tell the immediate story and are the best candidate to do so.

In this two-weeks course, the attendants learned how to make such information products, including maps. We based the course on a data workflow developed and kindly provided by colleague Andy Nelson. That workflow was fine-tuned to the Bhutan case (higher resolution, more topography sensitive), and expanded to include the creation of policy support documents. Generally, the course provided a quality boost in professional data practice. The hands-on training (and supported lectures) equipped the participants with methods that can be adopted by their organizations, and allow introduction to management and staff. Our choice of SDG indicators was such that work on other indicators can follow similar routines, that is, the course attendants obtained a good understanding of the examples and can apply these as templates to follow.
Thu 30 Jan 2020
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VENI grant for Monika KufferThe UT researcher Monika Kuffer receives a Veni grant from the Netherlands Organisation for Scientific Research (NWO). Dr Kuffer works at the Department of Urban and Regional Planning and Geo-Information Management of Faculty ITC. This VENI grant allows her to work out her own research ideas for three years. Monika Kuffer is developing a machine-learning based framework to map the disadvantaged neighbourhoods in developing countries.
Wed 17 Jul 2019
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