21 Dec 2017 10:15 to 11:15
Session ID: OF89
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Moderator Ms Nadia Isler, the director of the SDG Lab at the UN Office in Geneva, reminded the audience of the context of the discussion. She argued that when we speak about data, we need to remember that data is not uniform. Rather, we need to be aware that data is used in diverse ways by the various organisations. She also challenged the audience to keep some of the key questions surrounding data in mind: what data are we collecting; how is it collected and analysed; who collects it, and how do we format data in such a way that it supports and feeds into policy making.
The first speaker Ms Barbara Rosen Jacobson, a programme manager at DiploFoundation & the Geneva Internet Platform, began by stressing that ‘the importance of data is now very obvious and well reflected on the agenda of this IGF’. Further, she highlighted that more and more data is being generated, increasing the opportunities for better-informed policy. Yet, this also places additional demands on the monitoring processes, especially in the area of development. She then described the outcomes of her research into the debates around data and the SDGs of the High-Level Political Forum on Sustainable Development (HLPF). She highlighted that in past HLPF debates there has been an overwhelming focus on data disaggregation as the key challenges for SDG implementation and monitoring. Other challenges have related to capacity development and the question of making the data relevant for decision-making. However, she also pointed out that although more and more data is being collected, discussions around data privacy and making sure that data is used for good are not yet taking place. She concluded by arguing that ‘modern goals need a modern measurement system’ and that ‘now the opportunity has arisen to turn the hype into real action and real impact’.
Dr Linus Bengtsson, executive director at Flowminder Foundation, gave insights into the work of Flowminder. He began by cautioning that data visualisation can now create very beautiful images, but that we need to do better in making sure that these images correspond to the situation on the ground. For this, validation will be crucial. He described the kinds of data his organisation draws on, ranging from traditional to newer sources of data: household surveys, mobile phone data, and geospatial data. Bengtsson stressed that some of these sources can be ‘very biased as a proxy for what we want to capture’. However, he also pointed out that there are ways of adjusting for the biases to get to a better measurement. He then gave examples of the high-resolution maps for low- and middle-income countries that Flowminder is producing such as a high-resolution maps of female literacy rates. He concluded by pointing out that this data now finds its ‘way into international reports, and that this is no longer and academic exercise’.
Ms Rosy Mondardini, managing director of the ETH/UZH Citizen Science Center, focused her intervention on the data generated by citizens and how this kind of data can play a role for the SDGs. She explained that citizen science describes the collaboration between citizens and scientists on scientific research. Traditionally, scientists define the project, citizens are involved in data collection, and scientists then do the data analysis. However, now citizens are more and more involved in the data analysis and throughout the overall process. She gave examples of citizen science from the areas of biology and physics, such as involving citizens in checking water quality and classifying galaxies. Mondardini then gave examples of three projects that put citizens ‘at the heart of the activity and the data collection’ in the area of development: safecast which saw citizens monitor radiation levels after the 2011 earthquake and Fukushima accident in Japan; foldit an online puzzle video game about protein folding; and hot, a humanitarian open street map team which engaged volunteers in checking satellite images to identify damages to buildings and other infrastructure in the aftermath of major disasters. Mondardini argued that projects like these fill gaps in science and provide substance to make informed decisions to support development and monitoring as part of the SDGs.
Mr John Crowley, manager of knowledge and learning at the International Federation of Red Cross and Red Crescent Societies (IFRC), began by stressing that ‘because the reality is changing so fast, the data we are collecting describes a dynamic reality and has to be constantly updated’. He argued that open data is critical for monitoring and achieving the sustainable development goals (SDGs). With regard to that he stressed the importance of legal openness, which relates to licences for the data in order to distribute it, and technical openness, which relates to having data in a usable format, and navigating proprietary data issues. Further, governments hold many very useful data sets for development, but it is hard to get them released. Crowley also reminded us to look carefully at the level at which we are carrying out data collection and analysis and suggested that the national level is not good enough for generating a useful picture of a situation and that data needs to be a lot more specific. Finally, he gave a very concrete example of using maps for development. In order to eradicate measles, a 95% vaccination rate is needed. People on the ground can be mobilised to trace where vaccinations have already taken place. On the basis of this, volunteers will know which buildings and streets to go to, to administer vaccinations. He concluded by looking at the need to increase data literacy at all levels and argued that ‘if we want to use these datasets and turn them into programmes and decisions, we are going to have to learn like a musician that wants to join a choir. We have to learn to sing and we have to be able to learn to use these datasets in our decisions. Otherwise, we will be out of tune”.
During the question and answer session, some of the key questions related to data for the SDGs such as data quality, data security and data privacy were put into sharper focus.
By Manyi Arrey